Wednesday, February 27, 2013

Automotive RADAR Application and Design


AFE for auto radar provides signal path: 6-channel mux, PGA, LNA, filter, and 14-bit, 80-MapsADC

Bill Schweber, Planet Analog 
5/25/2011 12:01 AM EDT
If you think cars already have "lots" of electronics, look out: there's more coming, as IC vendors increasingly integrate functionality into smaller packages, thus enabling even more functions to be packed into the vehicle at tolerable prices.
Consider the just announced AD8283 analog front end for automotive radar from Analog Devices, Inc. This IC comprises much of the radar-return receive path, after initial down-conversion from the radar antenna. It feeds the 14-bit, 80 Msps analog/digital converter via six-channel multiplexer (mux) each preceded by its own low-noise amplifier (LNA), corresponding programmable gain amplifiers (PGA), and programmable filters, with an internal reference. Control I/O is via the SPI bus and the 3.3 V CMOS parallel data I/O is designed to interface with a DSP or FPGA.
Key functional-block specifications of the AD8283 include:
  • Low noise amplifier with input referred voltage noise below 3.5 nv/√Hz, at maximum gain of 34 dB and sampling rate of 80 Msps
  • Programmable gain , SPI programmable in 6 dB steps, over a 16 to 34 dB range
  • Anti-aliasing filter, 3rd order elliptic, cutoff programmable from 1 to 12 MHz
  • 12-bit, 80 Msps ADC with 67 dB SNR and 68 dB SFDR
  • Channel to channel gain matching of ±0.5 dB and phase matching of ±5⁰, over the specified operating temperate range of  -40 to +105⁰C
  • Input impedance of 200 Ω or 200 kΩ, user selectable
  • Power dissipation of 170 mW per channel
Price, packaging, and availability: The AD8283 is $12.00 in 1000-piece lots, and is available now. It is housed in a 72-lead LFCSO packag

Freescale Automotive Radar Millimeter-Wave Technology

Beyond passive safety systems, active safety systems play a major role in reducing traffic fatalities. Active safety systems include adaptive cruise control and collision warning systems with automatic steering and braking intervention.
In a collision warning system, a 77 GHz transmitter emits signals reflected from objects ahead, at the side and to the rear of the vehicle and are captured by multiple receivers integrated throughout the vehicle. The radar system can detect and track objects in the frequency domain triggering a driver warning of an imminent collision and initiate electronic stability control intervention.

Millimeter-Wave Technology

Advancements in SiGe:C HBT technology pushed the emerging arena of high-frequency (>60 GHz) millimeter-wave (mm-wave) applications such as WLAN (60 GHz) and automotive radar (77 GHz) circuits into the reach of low-cost silicon technology.
Freescale’s expertise in SiGe:C bipolar development has been leveraged to provide a mm-wave-capable variation of the 180 nm SiGe:C BiCMOS platform. Announced in 2006, this technology features bipolar transistors with a 300 GHz maximum oscillation frequency and active and passive models optimized for mm-wave applications.

Freescale 77 GHz Technology Advantages

Multi-mode, multi-application capability
  • Simultaneous long- and mid-range functionality
    • Allows one radar to be used for multiple safety systems:
      • Adaptive cruise control
      • Headway alert
      • Collision warning
      • Mitigation and brake support
Solid-state technology
  • Highest level integration
    • Most advanced SiGe technology with multi-channel transmitter and receiver chips
  • No moving parts
  • Extremely reliable
Class-leading performance and durability
  • Resistant to vibration and extremely robust
  • Innovative design provides excellent multi-target discrimination
    • Including precise range, approach speed and angle data
  • High speed FMCW waveform combined with 2D-FFT algorithm
    • Provides independent measurements of range and range rate
    • Provides superior detection of clustered stationary objects

Automotive Radar Applications

ApplicationDetection RangeSafety AspectTechnology
Adaptive Cruise Control200 metersNormal driving; accident avoidance77 GHz Radar
Pre-Crash30 metersAccident; mitigation of impact77 GHz Radar / 24 GHz Radar 76 / 81 GHz Radar
Blind Spot Detection20 metersNormal driving; accident avoidance24 GHz Radar/ Vision sensor
Lane Departure Warning60 metersNormal driving; accident avoidanceVision sensor
Stop and Go30 metersNormal driving; accident avoidance77 GHz + 24 GHz Radar 76/81 GHz Radar

On-Demand Training

Automotive Front-End Radar and Associated Signal Processing
Course Description
Advanced Driver Assistance Systems (ADAS) use a variety of surround sensing techniques. Focusing on radar, we will show the basic design challenges and system architectures, and will propose complete solutions from the front-end components to signal processing and system control. This session will cover current status, architectures and development strategy for the SiGe automotive radar front-end components as well.
**Presented during the 2008 Freescale Technology Forum in Orlando, Florida.
Course Outline
  • Freescale RF technology used in radar application
  • Supported radar architectures
  • Radar transmission and receiver structure
What You’ll Learn
  • Identify the advantages of SiGe for Radar Applications
  • Compare and contrast monostatic and bistatic radar
  • Describe radar modulation techniques and engine control unit structures for adaptive cruise control
  • Describe the basic processing steps which include windowing, detecting targets, clustering and tracking
  • Describe features of Freescale’s MPC5561 automotive




ADVANCED AUTOMOTIVE RADAR HELPS CAR MAKERS INCREASE DRIVER SAFETY THROUGH INTELLIGENT VEHICLE DESIGN

Analog Devices’ analog front-end for automotive radar enables adaptive cruise control and blind spot detection in a single, cost-competitive IC.
Advanced Automotive Radar Helps Car Makers Increase Driver Safety
Norwood, MA (05/25/2011) - Automotive safety is evolving from passive systems such as seat belts, airbags and crash detection to active sensing networks capable of collision avoidance and accident prevention. Radar is an especially promising active safety improvement and has the potential to significantly reduce the number and severity of distracted driving accidents. Analog Devices, Inc. (NYSE: ADI), whose integrated inertial sensingiMEMS® technology helped make airbags a standard automotive safety feature over 15 years ago, is introducing an affordable, high-performance, radar AFE (analog front-end) IC today. Watch this video to learn more about automotive radar and the AD8283 Radar AFE: http://www.youtube.com/watch?v=Jh7bspSF_PE
ADI’s highly integrated AD8283 automotive radar AFE IC includes the receive path signal conditioning and data capture circuitry to enable end systems for adaptive cruise control, blind spot detection and other radar-based detection and avoidance applications.
“Thanks to national vehicle safety legislation, such as the introduction of legislation requiring mandatory installation of ADAS (Advanced Driver Assistance Systems), fewer drivers died on US roads last year than at any time since 1949*,” said Thomas Wessel, vice president, automotive group, Analog Devices. “This is largely due to the fact that automotive safety has entered the era of the intelligent vehicle, and affordable in-car radar systems with excellent target classification and range resolution are a key feature of that. As in-car radar moves from a luxury option to a standard safety feature, the AD8283 automotive radar AFE will allow designers to program the settings they need for different operating conditions and meet the automotive industry’s exacting quality and cost requirements.”

Performance Radar in an AEC-Q100 Qualified IC

The six-channel AD8283 is AEC-Q100 qualified and operates over the -40°C to +105°C automotive temperature range. The new device allows a radar system to receive a higher number of transmitted signals and decode them for target identification and classification. This translates to more time on target, which improves the radar’s ability to resolve the approximate size of the target.
The AD8283 integrates a 12-bit, 80-MSPS (million samples per second) A/D converter with 67-dB SNR (signal-to-noise ratio) and 68-dB SFDR (spurious-free dynamic range). It features on-chip signal conditioning, including a programmable-gain amplifier, low-noise amplifier, and a programmable, third-order, low-pass elliptic filter. The AD8283 is gain-programmable via an SPI port in 6-dB steps from 16 dB to 34 dB and has <3.5nV/rtHz input-referred voltage noise at maximum gain. The new AFE has 200-Ω or 200-kΩ selectable input impedance and consumes only 170-mW per channel.
ProductSample AvailabilityFull VolumePrice Each In 1,000Packaging
AD8283YESYES$12.0072-lead LFCSP
As part of a complete radar implementation, the AD8283 can be paired with ADI’s ADF4158 PLL (phase locked loop).

About Analog Devices

Innovation, performance, and excellence are the cultural pillars on which Analog Devices has built one of the longest standing, highest growth companies within the technology sector. Acknowledged industry-wide as the world leader in data conversion and signal conditioning technology, Analog Devices serves over 60,000 customers, representing virtually all types of electronic equipment. Analog Devices is headquartered in Norwood, Massachusetts, with design and manufacturing facilities throughout the world. Analog Devices is included in the S&P 500 Index.



Automotive

Design engineers in the automotive industry look to Emerson & Cuming Microwave Products for cost effective solutions for their interference control problems in today’s high performance automotive electronics.
Using technology developed decades ago for military and aerospace applications, today’s automotive engineer relies on radar technology to develop microwave electronics for collision avoidance and adaptive cruise control, blind spot detection, parking assist functions and tire pressure monitoring among other applications.
Radar systems such as these often require microwave absorbing materials, low loss dielectrics or in some cases EMI shielding products to optimize performance.
Emerson & Cuming meets the challenge by offering products with the highest quality and reliability in the industry.

Links



Automotive Radar Millimeter-Wave Technology


Beyond passive safety systems, active safety systems play a major role in reducing traffic fatalities. Active safety systems include adaptive cruise control and collision warning systems with automatic steering and braking intervention.
In a collision warning system, a 77 GHz transmitter emits signals reflected from objects ahead, at the side and to the rear of the vehicle and are captured by multiple receivers integrated throughout the vehicle. The radar system can detect and track objects in the frequency domain triggering a driver warning of an imminent collision and initiate electronic stability control intervention.

Millimeter-Wave Technology

Advancements in SiGe:C HBT technology pushed the emerging arena of high-frequency (>60 GHz) millimeter-wave (mm-wave) applications such as WLAN (60 GHz) and automotive radar (77 GHz) circuits into the reach of low-cost silicon technology.
Freescale's expertise in SiGe:C bipolar development has been leveraged to provide a mm-wave-capable variation of the 180 nm SiGe:C BiCMOS platform. Announced in 2006, this technology features bipolar transistors with a 300 GHz maximum oscillation frequency and active and passive models optimized for mm-wave applications.

Freescale 77 GHz Technology Advantages

Multi-mode, multi-application capability

  • Simultaneous long- and mid-range functionality
    • Allows one radar to be used for multiple safety systems:
      • Adaptive cruise control
      • Headway alert
      • Collision warning
      • Mitigation and brake support

Automotive Radar Applications

Freescale 77 GHz Technology Advantages Cont.

Solid-state technology

  • Highest level integration
    • Most advanced SiGe technology with multi-channel transmitter and receiver chips
  • No moving parts
  • Extremely reliable

Class-leading performance and durability

  • Resistant to vibration and extremely robust
  • Innovative design provides excellent multi-target discrimination
    • Including precise range, approach speed and angle data
  • High speed FMCW waveform combined with 2D-FFT algorithm
    • Provides independent measurements of range and range rate
    • Provides superior detection of clustered stationary objects

Automotive Radar Applications

ApplicationDetection RangeSafety AspectTechnology
Adaptive Cruise Control200 metersNormal driving; accident avoidance77 GHz Radar
Pre-Crash30 metersAccident; mitigation of impact77 GHz Radar / 24 GHz Radar 76 / 81 GHz Radar
Blind Spot Detection20 metersNormal driving; accident avoidance24 GHz Radar/ Vision sensor
Lane Departure Warning60 metersNormal driving; accident avoidanceVision sensor
Stop and Go30 metersNormal driving; accident avoidance77 GHz + 24 GHz Radar 76/81 GHz Radar



















































































































Radar Solutions for Automotive

Select a Subcategory

RASIC™ Front-End IC's for Automotive RADARs

 Front-End ICs for Automotive RADARs
The Radar System IC (RASIC™) series from Infineon is made up by a group of highly integrated functions for the 76-77GHz range like Transceiver (sender/receiver), Oscillators (VCO) and Dielectric Resonator Oscillators (DRO) for all kinds of automotive and industrial radar applications. The ICs built in Infineon’s SiGe process offer a high level of integration at a lower cost compared to existing Gallium-Arsenide (GaAs) products. They are available as unpackaged bare-die.
Automotive Applications:
  • Adaptive Cruise Control
  • Collision Mitigation Systems 
  • Collision Warning Systems
  • Lane Change Assist
  • BackUp Radar




Long-Distance Car Radar

Affordable radar will let every car see through fog, brake on its own, and track other vehicles hundreds of meters ahead

By RICHARD STEVENSON  /  OCTOBER 2011
Photo: John Warden/Getty Images
To find out what driving's like when you have a sixth sense, I took a radar-equippedAudi A8 around the highways and byways of Stuttgart, Germany. It was great.
I couldn't help but smile when I pulled behind a huge truck and, resisting the temptation to hit the brakes, focused on steering. The adaptive cruise-control system, which uses a new radar from Robert Bosch that can see hundreds of meters ahead, did the rest. The system gently nestled the car behind the juggernaut and accelerated at my command, so I was able to pull out into the passing lane, all the while getting the most out of the 4.2-liter diesel, which rapidly propelled me to the speed I'd selected.
The system did have its foibles. Once the radar locked onto the car in front of me, and when the car turned hard to the right and then hard to the left, the radar came unlocked. So I took control, applying the brakes well before the emergency braking would have kicked in. That episode was a little disconcerting. Still, I could easily get used to this gizmo.
Most people who have driven for a while using such a radar are loath to ever give it up. And the number of such devotees will only grow as this technology—which now adds about US $1000 to the price of the car—becomes more affordable. The first commercial system appeared in Japan in 1997, on the Toyota Celsior; others soon followed in some top-of-the-line models from the likes of BMW, Jaguar, Lexus, Nissan, and Mercedes. The market has been expanding at about 40 percent a year, and as prices fall, that rate should rise.
Today's systems can dramatically reduce your risk of rear-ending someone else's car, and when most cars have such radars, they will also be much less likely to rear-end you. Once every vehicle on the road is able to sense and avoid others, there'll be no reason why they won't be able to negotiate tailing distances among themselves. Eventually, they might even be sending radio messages about their intentions to one another and to monitors on the roadway over ad hoc communication networks. Smart roads may thus emerge organically.
The first step in that evolution, the democratization of radar, is clearly under way. Next year Bosch will release a less expensive version of its radar, with a range of 160 meters, two-thirds that of the one I tested. This won't be a problem, though, because it's intended for cars that don't go nearly as fast.
Falling costs are the key, but of course, costs don't fall by themselves. Engineers have done their part by ditching the expensive compound semiconductors in their radar sets in favor of the old standby, silicon—but a special form of silicon that's been speeded up.
Illustration: Emily Cooper
I SPY...TROUBLE! Radar senses the car up ahead, calculates relative motion, and anticipates a collision. At first the system flashes a light and sounds a buzzer while readying the brakes; if the driver doesn't respond, it strengthens the alert with a jerk of the car. If after all that warning the car still enters the danger zone, the radar system takes charge and slams on the brakes.
In the late 1960s workers at Mullard Research Laboratories, in England, developed a car radar system that operated at 10 gigahertz, and RCA used the same frequency in its 1972 system. To make the next step and cram such a radar into a small space—such as under the hood of a car—manufacturers had to shrink the array of antennas, keeping each antenna far enough from its neighbors to allow for good resolution of detail. They accomplished this task by moving first to 34 GHz, then to 50 GHz, and recently to 77 GHz. The choice of frequency has something to do with the absorption of microwaves in the air and a lot to do with legislation: The law places strict limits on power for the lower frequencies, which is why systems in the lower bands can look forward just a few meters, only enough to avoid fender benders in stop-and-go traffic.
To manage the higher frequencies, long-range auto radars have until recently required seven or more gallium arsenide–based chips to generate, amplify, and detect the microwave signals. That set of chips costs from $20 to $60—not all that much, it might seem. But those chips have to be connected and tested, and if one fails to work, it must be rooted out and replaced. This labor adds substantially to the cost of any radar based on gallium arsenide technology.
In 2009, the German chipmaker Infineon Technologies, based in Neubiberg, produced a system designed around a single silicon-based chip. Then it teamed up with Bosch and started supplying a more flexible, two-chip variant for radar systems in 2010 models of the Audi A8, Porsche Panamera, and Volkswagen Touareg. Not only are these new systems less expensive, they also have significantly better performance, allowing them to cover more than four times the area in front of the car, four times as accurately.
Even specialists in the gallium arsenide industry expect that silicon chips will grab most of the car radar market. Asif Anwar, director of the program for gallium arsenide and compound-semiconductors technologies at the market-research firm Strategy Analytics, in England, predicts that over the next three years, silicon's share of the chip market for automotive radar will grow from nearly nothing to perhaps 60 percent. Although Infineon will then have captured most of the resulting $120 million market for silicon-based radar chips, it already faces the first signs of serious competition: U.S. chipmaker Freescale Semiconductor, in Austin, Texas, has just started sending samples of its silicon-based chip to automotive radar makers. Other companies are surely following suit.
Infineon has thus overturned the conventional view that silicon chips would never be able to generate, detect, and amplify high frequencies. The problem is that electrons move slowly through those chips—which is why a decade ago Infineon and a handful of other companies were using the faster gallium arsenide to build automotive radar chips. But in mid-2002 Infineon got out of the gallium arsenide business. A year later it was in discussions with Bosch about automotive radar chips based on silicon.
"At that time everybody thought this was not possible to do with silicon-based technologies," recollects Rudolf Lachner, Infineon's program manager for radar technologies. "But we did some high-speed circuits, such as voltage-controlled oscillators, which worked at 77 GHz."
To realize such high speeds in a silicon transistor, Infineon's engineers inserted into the heart of the device a thin layer that was four parts silicon and one part germanium. The idea was hardly new. Indeed, it can be traced to theoretical work that Nobel Prize–winning physicist Herbert Kroemer, now at the University of California, Santa Barbara, did way back in the 1950s. However, the world had to wait until 1975 for the first real device, made at AEG Research Center (now part of Daimler) in Ulm, Germany. Infineon's claim to fame comes from boosting this kind of transistor to record speeds, thanks to improvements in internal configuration and material quality.
graphic illustration, evolution of a radar
Photos: Bosch
EVOLUTION OF A RADAR Bosch's latest long-range system greatly simplifies the radar's printed circuit board. Instead of a handful of gallium arsenide chips to generate, amplify, and detect the 77-gigahertz microwaves, the system uses just one or two (as shown) of Infineon's silicon germanium chips. Click on image for enlargement.
Adding that layer of silicon germanium alloy introduces electric fields that present the moving electron with the equivalent of a downhill path, speeding it up automatically. Now even transistors with 50-nanometer-thick base layers can reach the speeds demanded by 77-GHz automotive radar.
Switching to the new transistor delivers another benefit—very low noise levels. You can speed up conventional silicon transistors by thinning the base layer, but you'll just impede the flow of electrons and increase background noise. To muffle it, you could try to reduce the resistance of the base by doping the silicon with traces of boron, whose atoms each have three electrons in the outer shell, rather than silicon's four. Because there aren't enough electrons to form all the covalent bonds required, you get a "hole," or virtual positive particle, which moves freely through the crystal, increasing its conductivity. Unfortunately, increasing the base doping this way reduces the amplification, or gain. Working with a silicon germanium base layer gets around this problem because it makes its own contribution to the gain, offsetting the losses caused by doping. You can make the base doping very high, explains Lachner. "And by making it very high, you get a very low base resistance, which improves the noise behavior of your transistor," he says.
The fundamental insight stemmed from work Infineon did in the early 1990s while developing chips for next-generation mainframe computers. That project never took off. Nor was the company able to market its chips to mobile-phone vendors: As conventional transistors shrank, their lower cost proved more important than the lower power consumption of Infineon's chips. But soon after, it became clear to Infineon that this technology was a perfect fit for auto radar.
Perhaps it's the fiendishly high speeds of the autobahns that have made Germany so keen on technology to avoid collisions. Or it could be government aid. In 2004, Infineon began a three-year automotive radar program with 10 million in subsidies from the German government. That project allowed the company to collaborate with automotive radar system makers Bosch and Continental and carmakers BMW and Daimler.
Infineon's prototype could operate up to only about 80 GHz, good enough for use in an oscillator but not in the amplifier. That's because for a transistor to deliver reasonable gain at a given frequency, it needs to top out at about three times that value. In 2007, by improving the quality of the boron-doped silicon germanium in the base, Infineon's engineers increased the transistor's maximum operating frequency to the requisite level and soon went on to produce the first commercial silicon germanium automotive radar chips, which ran at 77 GHz. Four years later, Infineon continues to churn out the chips at its huge fab in Regensburg, Germany.
Inserting the silicon germanium layer into the device requires no exotic techniques or extraordinary tools: Infineon simply uses 200-millimeter silicon wafers and grows thin silicon films on top using conventional chemical-vapor deposition. At the appropriate point during the process, a valve opens, germanium-based gases flow into the growth chamber, and a silicon germanium film forms.
One such wafer can yield thousands of chips. "This gives us enough headroom to produce as many automotive radar systems as we would like," explains Lachner. In fact, most of the fab's output of 10 000 wafers goes to other purposes. If Infineon somehow captured the entire automotive market overnight, it could easily satisfy the demand.
So why do other companies, such as TriQuint Semiconductor, in Hillsboro, Ore., and United Monolithic Semiconductors, in Orsay, France, still produce automotive radar chips based on pricey gallium arsenide? For one thing, gallium arsenide is still the biggest player in the radar market at the moment, and these firms can sell a lot of chips, at least for a few years. Also, these companies don't necessarily have silicon production lines to switch to, nor would it make sense to build a full-blown silicon fab for car radar alone.
Photo: Bosch
COURTING DANGER: On a Bosch test track, the black demo car approaches the dummy car too quickly, alerting the radar system, which applies the brakes in time to prevent or at least soften the crash.
Cost isn't the only thing driving change. It's not only cheaper to use one Infineon chip (or two, in the fancier system); it's also more effective than the handful of gallium arsenide chips it replaces. When Bosch upgraded Infineon's product during the development of its third-generation long-range radar (dubbed, unimaginatively, the LRR3), both the minimum and maximum ranges of its system got better: The minimum range dropped from 2 meters to half a meter, and the maximum range shot from 150 to 250 meters. At the same time, the detection angle doubled to 30 degrees, and the accuracy of angle and distance measurements increased fourfold. The superiority stems from the significantly higher radar bandwidth used in the systems containing the silicon-based chips, says Thomas Fuehrer, Bosch's senior manager for strategic marketing for driver assistance: "It is around 200 megahertz on the LRR2, and we are now using 500 MHz on the LRR3."
Another selling point is the new system's compact size—just 7.4 by 7 by 5.8 centimeters. "If you are comparing it with the competitor's systems, this really is a very small masterpiece," Fuehrer says. What it means is that automobile designers can stick this thing just about anywhere—even in the headlamp assembly.
The system employs four antennas and a big plastic lens to shoot microwaves forward and also detect the echoes, all the while ramping the emission frequency back and forth over that big fat 500-MHz band. (Because the ramping is so fast, the chance of two or more radars interfering is extraordinarily low.) The system compares the amplitudes and phases of the echoes, pinpointing each car within range to within 10 cm in distance and 0.1 degree in displacement from the axis of motion. Then it works out which cars are getting closer or farther away by using the Doppler effect—the change in frequency associated with motion that also causes us to perceive a train whistle to rise in pitch as it approaches us and fall as it pulls away. In all, the radar can track 33 objects at a time.
On the Audi A8, you receive two separate warnings when you get worryingly close to the car in front. First, a high-pitched alarm sounds, and a light appears on the dashboard. If that sound-and-light show doesn't work, then comes a short, sharp brake to snap you out of your stupor. "Tests and studies show that most drivers will then immediately look forward at the road and notice if they are too close," says Bernhard Lucas, head of Bosch's department for developing car radar hardware.
Even braking may not prevent a collision: Statistics gathered by Bosch show that nearly half of rear-end crashes are caused by drivers pressing the brake pedal too softly. But if that happened in the radar-equipped Audi A8, additional braking would be applied automatically.
If worse comes to worst, the braking system goes into action by itself. "In rare cases where the driver is completely unable to do anything—he is helpless or half dead—full emergency braking is applied when the crash is really unavoidable," says Lucas. Then the car decelerates abruptly, throwing the driver forward into the safety belt with up to six times the force of gravity but minimizing what would otherwise be a catastrophic impact with the car in front.
Of course, you'll probably never have to call on such emergency powers to save your life. Few people even consider such features when purchasing a car. That's why the day-to-day operation of the system is important for winning over the driver. Today, the benefits come mainly in the form of a radar-enhanced cruise control. You can set your radar to lock onto the vehicle in front and keep pace with it, braking and speeding up appropriately. You specify the following distance and the maximum allowable speed, which can be as high as 250 kilometers per hour (155 miles per hour).
It is interesting that when Audi, Porsche, and VW started making radar-ready cars last year, all three companies chose to use the radar as a driving aid rather than afull-blown autopilot. They thus reduced their liability for any accidents that might ensue. Today, it's clear that the main roadblock for a software-based chauffeur are legal worries and perhaps the fear of the unknown. Should any automaker dare to take the plunge, the technology will not be lacking.



Statistical Signal Processing – Automotive Radar (Praktische Übung im Labor)

We offer the Lab Course “Statistical Signal Processing - Automotive Radar” (PÜL) for master students.
The task is to apply methods from statistical signal processing to radar signals in order to estimate the distances, the velocities as well as the angles of surrounding objects. Thereby you will create a complete radar signal processing chain, which could be used in automobiles.
Modern automobiles are already equipped with radar systems. Thereby comfort functions like for example Adaptive Cruise Control (ACC) can be offered. ACC refers to a system, which adjusts the own speed accordingly to the preceding cars. The radar systems are also used as security systems, e.g. they warn the driver of critical situations.
The goal of this course is to solve a challenging practical task from statistical signal processing while working in a team of two or three students. You will acquire and apply methods to real problems, based on simulated and measured data. Finally the results will be documented in a report (in english or german) and presented in a correct and understandable way. The methods you learn are also used in many other fields, e.g. audio signal processing and image processing of medical data, like computed tomography (CT) or magnetic resonance tomography (MRT).

Dates, Registration

please use ILIAS for more information on the dates and the registration (you have to be logged in to ILIAS).

Contact

Dipl.-Phys. Kilian Rambach


Radar-On-A-Chip (ROACH)

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roachRadar-On-A-Chip (ROACH) is a small, low cost, single chip automotive radar build on 65nm CMOS process for operating in the 76 - 77 GHz frequency band for both long range and short range automotive radar applications, such as Adaptive Cruise Control, Collision Mitigation, Blind Sport detections, Stop & Go Functions, etc., with a maximum detection range around 200 meters.  It is a highly integrated transceiver containing multiple transmit and receive chains operating in an array processing mode and supporting fully digital waveform generation and receive signal processing.  The system employes real-time adaptive waveform scheduling and adaptive antenna array processing, so as to adapt to different environments and applications.

An overview of ROACH is available here.

Collaboration
NICTA in partnership with the University of Melbourne, and supported by the Victorian Government, IBM, Cadence, and GM Holden, has established an experienced highly focused commercialisation orientated R&D team with skills in CMOS RF design, signal processing, antenna systems and radar technology, to develop ROACH sample prototype by mid of 2013.




Automotive Safety Development using radar spectrum

The European Union has cleared the way forward for expansion of important automotive safety techniques, by approving further use of automotive 24 GHz Ultra-Wide Band radar technology.
This decision was published in the Official Journal on July 30 after being approved at a meeting of the EU Radio Spectrum Committee in Brussels, on July 6-7. The EU had first approved the use of this technology in a decision taken in 2005. That decision was scheduled to expire in 2013, however, which would have left industry without suitable tools to provide for a range of advanced systems, such as automatic emergency braking, blind spot monitoring and pre-crash measures, such as automatic seat belt tensioners.

The new decision permits use of radar frequencies in the 24 Gigahertz range until 2018, with a phase out for existing car lines until 2022. All cars equipped with the radar by that date can stay on the market.
The automotive consortium SARA (Strategic Automotive Radar Frequency Allocation group) was the main proponent of the change. In an August 1 press release, the group said “this EU action resolved numerous technical details related to the use of radar frequencies, based on regulations that avoid interference from the radar to other spectrum users.” Dr. Gerhard Rollmann, chairman of SARA, said ”these technical issues were very controversial at the beginning due to interference issues. After over three years of debate we were able to resolve problems raised by other administrations and continue the use of this important technology.“ 
Studies by SARA member Mercedes-Benz have shown that 20 percent of rear-end collisions in Germany could be prevented using radar-based Brake Assist systems and accident severity could be reduced in a further 25 percent of collisions. The safety benefit was demonstrated in an analysis of the repair part statistics. Radar technology also is used to monitor driver blind spots. In 2010, Mercedes-Benz received the prestigious “Gelber Engel” (“Yellow Angel”) award for this application from the German automotive association ADAC. In its July 29 press release on the new decision, the Commission said “Widespread fitting of short range radar systems in cars could significantly enhance road safety for all road users and pedestrians."
Hogan Lovells worked closely with SARA to achieve both the 2005 decision and this latest amendment.




Distance Sensors - RADAR

Basic Description
Some cars and trucks are equipped with headway sensors that detect the distance between a vehicle and any vehicles or large objects in front of the vehicle. These sensors are used by adaptive cruise control and/or collision avoidance systems. Most existing headway sensors use a 76.5 GHz radar, but other frequencies (e.g. 24 GHz, 35 GHz and 79 GHz) are also in use. Some systems use infra-red sensors instead of (or in addition to) the RADAR sensors.
There are two primary methods of measuring distance using radar. The first is known as the direct propagation method and measures the delay associated with reception of the reflected signal which can be correlated to the distance of the reflecting object as a function of the speed of light and the period or rather, the time delay in the transmission and receiving of the waves. The second method is known as the indirect propagation method or the Frequency Modulated Continuous Wave (FMCW) method. For indirect propagation, a modulated frequency is sent and received, the difference in the frequency can be used to directly determine the distance as well as the relative speed of the object.
Radar signals are very good at detecting objects that strongly reflect electromagnetic radiation (e.g. metal objects). Because they operate at wavelengths on the order of a few millimeters, automotive radar systems are pretty good at detecting objects that are several centimeters or larger. They are also good at looking through (i.e. ignoring objects that are small relative to a wavelength (e.g. the water droplets in fog).
Possible application of a radar sensor
Possible automotive applications of radar sensors.
Other automotive systems that use radar distance sensors include collision avoidance systems, blind spot detection systems and automated parking systems.
Manufacturers
Autoliv, Bosch, Continental, Delphi, Freescale, Infineon, Mitsubishi Electric, SaberTek, Smartmicro, TRW
For More Information
[1] How Radar Works, Marshall Brain, HowStuffWorks.com, April 2000.
[2] Bosch's Adaptive Cruise Control , YouTube, August 2012.
[3] VW Passat CC Park Assist Vision , YouTube, April 2008.
[4] Seeing Past the Blind Spot , YouTube, March 2008.
[5] Infineon SiGe IC used in Bosch Automotive Radar System, Semiconductor Today, Dec. 2, 2008.
[6] Radar, Wikipedia.
[7] Long-Distance Car Radar, Richard Stevenson, IEEE Spectrum, Oct. 2011.
[8] Millimeter-Wave Technology for Automotive Application, Shinichi Honma & Naohisa Uehara, Mitsubishi Electric.
[9] Bosch Introducing New Mid-Range Radar Sensor, Stereo-Video Sensor in 2014, Green Car Congress, Oct. 30, 2012.



http://www.analog.com/en/press-release/5_25_11_Advanced_Automotive_Radar/press.html
http://www.infineon.com/cms/en/product/sensors-and-wireless-control/radar-solutions-in-automotive/channel.html?channel=db3a30431ddc9372011e213568da414b
http://www.nicta.com.au/research/projects/radar-on-a-chip_roach
http://www.eccosorb.com.hk/?q=industries-served/automotive
http://www.findmems.com/uncategorized/freescale-automotive-radar-millimeter-wave-technology
http://www.eetimes.com/electronics-products/electronic-product-reviews/analog-products/4216267/AFE-for-auto-radar-provides-signal-path--6-channel-mux--PGA--LNA--filter--and-14-bit--80-MapsADC/
http://www.hlspectrumreview.com/2011/08/articles/short-range-and-unlicensed-devices/automotive-safety-development-using-radar-spectrum/
http://www.iss.uni-stuttgart.de/lehre/masterLabRadar/index.html
http://spectrum.ieee.org/green-tech/advanced-cars/longdistance-car-radar/0#
http://www.freescale.com/webapp/sps/site/overview.jsp?code=AUTRMWT

Cloud computing Windriver Hypervisor vmware xen

 a hypervisor or virtual machine manager (VMM) is a piece of computer software, firmware or hardware that creates and runs virtual machines.



Thin client


Hypervior


Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet). The name comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts remote services with a user's data, software and computation.



There are many types of public cloud computing:[1]






Consolidate to Multi-core with Wind River Hypervisor

Unlock Performance. Bolster Security. Slash Hardware Costs.


Blow away your requirements for performance, cost, size, and power with Wind River® Hypervisor, a Type 1 embedded hypervisor that's built from the ground up for low latency, determinism, and multi-core performance—all in the smallest possible footprint. You'll increase product security by consolidating multiple operating systems of mixed levels of criticality onto the same single-core or multi-core processor without the burden of complete re-certification. And Hypervisor is a complete solution, integrating with Wind River operating systems, embracing the broadest hardware support, and backed by an award-winning global and local support team.





Introduction
“Cloud Computing,” to put it simply, means “Internet Computing.” The Internet is commonly visualized as clouds; hence the term “cloud computing” for computation done through the Internet. With Cloud Computing users can access database resources 


















via the Internet from anywhere, for as long as they need, without worrying about any maintenance or management of actual resources. Besides, databases in cloud are very dynamic and scalable.
Cloud computing is unlike grid computing, utility computing, or autonomic computing. In fact, it is a very independent platform in terms of computing. The best example of cloud computing is Google Apps where any application can be accessed using a browser and it can be deployed on thousands of computer through the Internet.
Key Characteristics
Cloud computing is cost-effective. Here, cost is greatly reduced as initial expense and recurring expenses are much lower than traditional computing. Maintenance cost is reduced as a third party maintains everything from running the cloud to storing data. Cloud is characterized by features such as platform, location and device independency, which make it easily adoptable for all sizes of businesses, in particular small and mid-sized. However, owing to redundancy of computer system networks and storage system cloud may not be reliable for data, but it scores well as far as security is concerned. In cloud computing, security is tremendously improved because of a superior technology security system, which is now easily available and affordable. Yet another important characteristic of cloud is scalability, which is achieved through server virtualization.
In a nutshell, cloud computing means getting the best performing system with the best value for money.
Cloud Computing Architecture
Cloud computing architecture, just like any other system, is categorized into two main sections: Front End and Back End. Front End can be end user or client or any application (i.e. web browser etc.) which is using cloud services. Back End is the network of servers with any computer program and data storage system. It is usually assumed that cloud contains infinite storage capacity for any software available in market. Cloud has different applications that are hosted on their own dedicated server farms.
Cloud has centralized server administration system. Centralized server administers the system, balances client supply, adjusts demands, monitors traffic and avoids congestion. This server follows protocols, commonly known as middleware. Middleware controls the communication of cloud network among them.
Cloud Architecture runs on a very important assumption, which is mostly true. The assumption is that the demand for resources is not always consistent from client to cloud. Because of this reason the servers of cloud are unable to run at their full capacity. To avoid this scenario, server virtualization technique is applied. In sever virtualization, all physical servers are virtualized and they run multiple servers with either same or different application. As one physical server acts as multiple physical servers, it curtails the need for more physical machines.
As a matter of fact, data is the most important part of cloud computing; thus, data security is the top most priority in all the data operations of cloud. Here, all the data are backed up at multiple locations. This astoundingly increases the data storage to multiple times in cloud compared with a regular system. Redundancy of data is crucial, which is a must-have attribute of cloud computing.
Different forms of Cloud Computing
Google Apps., Salesforce.com, Zoho Office and various other online applications use cloud computing as Software-As-Service (SAAS) model. These applications are delivered through browser, and multiple customers can access it from various locations. This model has become the most common form of cloud computing because it is beneficial and practical for both the customers and the services providers. For customers, there is no upfront investment and they can Pay-As-They-Go and Pay-As-They-Grow. On the other hand, the service providers, can grow easily as their customer base grows.
Aamzon.com, Sun and IBM offer on-demand storage and computing resources. Web service and APIs enable developers to use all the cloud from internet and allow them to create large-scale, full-featured application. Cloud is not simply limited to providing data storage or computing resources, it can also provide managed services or specific application services through web.
Cloud Computing Concerns
Security of confidential data (e.g., SSN or Credit Card Numbers) is a very important area of concern as it can make way for very big problems if unauthorized users get access to it. Misuse of data can create big issues; hence, in cloud computing it is very important to be aware of data administrators and their extent of data access rights. Large organizations dealing with sensitive data often have well laid out regulatory compliance policies. However, these polices should be verified prior to engaging them in cloud computing. There is a possibility that in cloud computing network, sometimes the network utilizes resources from another country or they might not be fully protected; hence, the need arises for appropriate regulatory compliance policies.
In cloud computing, it is very common to store data of multiple customers at one common location. Cloud computing should have proper techniques where data is segregated properly for data security and confidentiality. Care must be taken to ensure that one customer’s data does not affect another customer’s data. In addition, Cloud computing providers must be equipped with proper disaster recovery policies to deal with any unfortunate event.
Selection of Provider
A good service provider is the key to good service. So, it is imperative to select the right service provider. One must make sure that the provider is reliable, well-reputed for their customer service and should have a proven track record in IT- related ventures. The Cloud Computing Incidents Database(CCID) records and monitors verifiable, noteworthy events that impact cloud computing providers. Visit the following Wikipedia link to obtain the list all such events. http://wiki.cloudcommunity.org/wiki/CCID
Relational Database and Cloud Computing
Comparison has often been drawn between Relational Database and Cloud Computing. They are related for sure but they should not be confused for being the same thing. In actual fact, they are not really competing with each other. There are some unique requirements of applications when they do not call for any advance query techniques but rather need fast access to database. In such scenarios cloud computing should be used. In cloud, data is stored across myriad geographic locations, and processing data from different geographic database leads to delay in receiving data. In case of applications where there is the need of processing huge database using complex queries, traditional relational database is best suited. Cloud has its limitations. As for now, it only supports distributed computing; transactional operations are not currently supported in cloud computing.
Summary
Cloud Computing is the next big thing in the arena of computing and storage. There are some concerns about security and its availability. However, different service providers are coming up with various solutions and suggestions in response to customers’ concerns. In any case, cloud is getting bigger and better, and as long as they are available through web services, without capital infrastructure investment at reasonable price, it is for sure going to proliferate and create robust demand in times to come.




Cloud computing , cloud computing.ppt , all about Cloud computing

Definition:-

                      Cloud computing is a technology that uses the internet and central remote servers to maintain data and applications. Cloud computing allows consumers and businesses to use applications without installation and access their personal files at any computer with internet access. This technology allows for much more efficient computing by centralizing storage, memory, processing and bandwidth.






 Advantages  of Cloud Computing:-

  • Reduced CostCloud technology is paid incrementally, saving organizations money.
  • Increased StorageOrganizations can store more data than on private computer systems.
  • Highly Automated
    No longer do IT personnel need to worry about keeping software up to date.
  • FlexibilityCloud computing offers much more flexibility than past computing methods.
  • More Mobility
    Employees can access information wherever they are, rather than having to remain at their desks.
  • Allows IT to Shift Focus
    No longer having to worry about constant server updates and other computing issues, government organizations will be free to concentrate on innovation. 





 Disadvantages  of Cloud Computing:-

1.Security & Privacy

The biggest concerns about cloud computing are security and privacy. Users might not be comfortable handing over their data to a third party. This is an even greater concern when it comes to companies that wish to keep their sensitive information on cloud servers. While most service vendors would ensure that their servers are kept free from viral infection and malware, it Is still a concern considering the fact that a number of users from around the world are accessing the server. Privacy is another issue with cloud servers. Ensuring that a client’s data is not accessed by any unauthorized users is of great importance for any cloud service. To make their servers more secure, cloud service vendors have developed password protected accounts, security servers through which all data being transferred must pass and data encryption techniques. After all, the success of a cloud service depends on its reputation, and any sign of a security breach would result in a loss of clients and business.

2.Dependency (loss of control):

  • Quality problems with CSP(Cloud Service Providers).No influence on maintenance levels and fix frequency when using cloud services from a CSP.
  • No or little insight in CSP contingency procedures. Especially backup, restore and disaster recovery.
  • No easy migration to an other CSP.
  • Measurement of resource usage and end user activities lies in the hands of the CSP
  • Tied to the financial health of another Company.

3.Cost

Higher costs. While in the long run, cloud hosting is a lot cheaper than traditional technologies, the fact that it’s currently new and has to be researched and improved actually makes it more expensive. Data centers have to buy or develop the software that’ll run the cloud, rewire the machines and fix unforeseen problems (which are always there). This makes their initial cloud offers more expensive. Like in all other industries, the first customers pay a higher price and have to deal with more issues than those who switch later (although it would be very hard to create and improve new technologies without these initial adopters).

4.Decreased flexibility

This is only a temporary problem (as the others on this list), but current technologies are still in the testing stages, so they don’t really offer the flexibility they promise. Of course, that’ll change in the future, but some of the current users might have to deal with the facts that their cloud server is difficult or impossible to upgrade without losing some data, for example.

5.Knowledge  And Integration.

Knowledge:
More and deeper knowledge is required for implementing and managing SLA contracts with CSP’s ,Since all knowledge about the working of the cloud (e.g. hardware, software, virtualization, deployment) is concentrated at the CSP, it is hard to get grip on the CSP.
Integration:
Integration with equipment hosted in other data centers is difficult to achieve. Peripherals integration. (Bulk)Printers and local security IT equipment (e.g. access systems) is difficult to integrate. But also (personal) USB devices or smart phones or groupware and email systems are difficult to integrate.
- See more at: http://technicalfire.blogspot.in/2012/05/cloud-computing-cloud-computingppt-all.html#sthash.xzf1jiTt.dpuf

http://abhinavgoyal01.wordpress.com/2009/06/29/lets-learn-cloud-computing-in-very-simple-language/

http://thebowditchgroup.com/17-cloud-computing-applications-small-business/

http://en.wikipedia.org/wiki/Cloud_computing


http://www.cc.iitd.ernet.in/misc/cloud/hypervisor_performance.pdf


http://www.windriver.com/products/hypervisor/











http://thecustomizewindows.com/wp-content/uploads/2012/12/A-Basic-Real-Time-Audio-Processing-Instance-on-Cloud-of-Your-Own.png
http://learningaloud.com/blog/2008/10/13/thin-client-cloud-computing-whats-the-difference/

http://xen.org/products/xenhyp.html
http://www.windriver.com/products/hypervisor/
















http://www.atoziq.com/2012/06/cloud-computing-multiple-choice.html
http://questions-interviews.blogspot.de/2012/05/cloud-computing-interview-questions-and.html

http://www.questions-interviews.com/cloud-computing/basic.aspx

http://www.questions-interviews.com/cloud-computing/architecture.aspx

http://www.questions-interviews.com/cloud-computing/architecture.aspx

http://en.wikipedia.org/wiki/Apache_Hadoop

THIN CLIENT, CLOUD COMPUTING, WHAT’S THE DIFFERENCE
The relatively recent focus on “cloud computing” has a vaguely familiar feel to those of us who have been involved with technology for a while. Some of my early ed tech research was conducted with a PDP 11/34 mini computer “serving” a dozen “dumb terminals”. The terminals were basically a keyboard and monitor and everyone connected to the same “remote” computer. Remote in this case meant “in another room”.

A recent NY Times article indicates that “thin client” computing may be on the rebound. The “hook” is often financial assuming that many users can share programs (software) and hardware (server) with the result that the work stations can be less powerful and thus less expensive.

Cloud computing is very similar. For example, many users with low end hardware can connect via the Internet and use Google docs rather than invest in many copies of Microsoft Word.

What is the difference? One difference might be the openness/extensiveness of the network. A thin client architecture serving a company is different than an Internet-based service available to everyone. Perhaps a second difference is how completely “clients” must subject themselves to “the system”. One model of the thin client approach assumes users are connecting with the bare minimum of hardware and software and cannot perform actions that allow independence – e.g., storing local copies of work completed. In contrast, Google Apps allows local storage of resources and through the use of Google Gears independence from the Internet.

While some are concerned that cloud computing is a trap, I am concerned only to the extent the options are few and inexpensive opportunities come at the expense of becoming dependent on one or two providers.

Saturday, February 23, 2013

RADAR SVC Decoder buffer MP BP IBP frame CBR VBR vectoer and piexl


Decoder Buffer Requirements

http://www.bretl.com/mpeghtml/bufreq.HTM

http://www.scribd.com/doc/24435505/31/Conditions-for-Preventing-Decoder-Buffer-Underflow





Laptop Radar
http://www.egr.msu.edu/classes/ece480/capstone/fall11/group07/file/Document.html

Super hetrodyne Reciever
https://www.google.co.in/#hl=en&tbo=d&sclient=psy-ab&q=superheterodyne%20receiver%20ppt&oq=&gs_l=&pbx=1&fp=1&biw=1366&bih=643&pf=p&pdl=300&cad=b&bav=on.2,or.r_gc.r_pw.r_cp.r_qf.







SVC coding
http://en.wikipedia.org/wiki/Scalable_Video_Coding
https://www.google.co.in/search?q=sVC+ipc+&rlz=1C1IRFF_enIN511IN511&oq=sVC+ipc+&aqs=chrome.0.57j0l3j62l2.5235&sourceid=chrome&ie=UTF-8#hl=en&sugexp=les%3Bcappsweb&gs_rn=3&gs_ri=psy-ab&tok=c0BLdypv9nefqyxKEf_TMA&pq=svc%20ipc%20&cp=11&gs_id=v&xhr=t&q=svc+video+codec&es_nrs=true&pf=p&tbo=d&rlz=1C1IRFF_enIN511IN511&sclient=psy-ab&oq=sVC++video+&gs_l=&pbx=1&bav=on.2,or.r_gc.r_pw.r_cp.r_qf.&bvm=bv.42553238,d.bmk&fp=ec0d1b87f8876f13&biw=1066&bih=716



http://en.wikipedia.org/wiki/File:Digital_video_resolutions_(VCD_to_4K).svg
http://hometheater.about.com/od/hometheaterglossary/g/4k-Resolution.htm
http://en.wikipedia.org/wiki/8K_resolution#Resolutions
http://en.wikipedia.org/wiki/Ultra_High_Definition_Television
http://en.wikipedia.org/wiki/4K_resolution#Resolutions


main profile and base profile


http://blog.davidesp.com/archives/559

https://www.google.co.in/search?hl=en&tbo=d&rlz=1C1IRFF_enIN511IN511&biw=1066&bih=716&q=main+profile+vs+high+profile&revid=462554895&sa=X&ei=ehsjUeC6N4rUrQf1moGwCg&ved=0CJQBENUCKAE


I_B_P frame


How will i calculate VBR and CBR
http://en.wikipedia.org/wiki/Variable_bitrate


Vector graphics
http://designshack.net/articles/layouts/vector-vs-raster-what-do-i-use/
http://en.wikipedia.org/wiki/Vector_graphics
http://graphicssoft.about.com/od/aboutgraphics/a/bitmapvector.htm

Friday, February 22, 2013

Multimedia Streaming Protocols: RTP/RTCP, RTSP, SDP


Multimedia Streaming Protocols: RTP/RTCP, RTSP, SDP


 

Presentation: Streaming Audio and Video

Video Streaming Presentation (Final) Ppt

RTSP – Real Time Streaming Protocol

RTP/RTCP and RTSP multimedia streaming protocols for ... - BNR

 

PPT

Media Streaming Protocols

The Real Time Streaming Protocol (RTSP)

 

 

RTSP – Real Time Streaming Protocol

] 

Real Time Streaming Protocol - Columbia University

RTSP – Real Time Streaming Protocol

 

The Real Time Streaming Protocol (RTSP)

RTSP.ppt - Openloop

Presentation: Streaming Audio and Video

 

 

 

 

 

 

 

 

 

 

 

 





okRTP/RTCP – Real Time Transport Protocol/ Real Time Control ..

okRTP/RTCP and RTSP multimedia streaming protocols for ... - BNRG

okRTP/RTCP multimedia protocols for the Internet - BITS Pilani

 

ok6. RTCP - Department Of Computer Science

okRTP: Real-time Transport Protocol - Multimedia Communications ...

 

Real-time Transport Protocol

RTP: A Transport Protocol for Real-Time Applications

Real-time Transport Protocol (RTP) - Wiki - Columbia University

RTP: A Transport Protocol for Real-Time Applications

RTP: Real-time Transport Protocol - Multimedia Communications ...

RTP.ppt

An Introduction to RTP

Real-Time Transport Protocol (RTP)

 

 

 

 

RTP, RTCP, and RTSP - Internet Protocols for Real-Time Multimedi

RTP/RTCP and RTSP multimedia streaming protocols for ... - BNRG

 

Multimedia Over IP: RSVP, RTP, RTCP, RTSP - KIV

RTP/RTCP and RTSP multimedia protocols for the Internet

RTP vs RTCP

 

 

 

 

 

 

 


RTP / RTCP - Douglas Reeves

(RTP, RTCP, SIP, RSTP)

RTP, RTCP, and RTSP - Internet Protocols for Real-Time Multimed

 

6. RTCP - Department Of Computer Science

Protocollo RTP/RTCP - Sebastiano Vascon

] 

Real Time Protocol (RTP) - EPFL

Multimedia Over IP: RSVP, RTP, RTCP, RTSP - KIV

 

Real-time protocols – RTP/RTCP - CiteSeerX

RTP: A Transport Protocol for Real-Time Applications ... - IETF Tools

 

 

 

 

 

 

 

 

http://www.slideshare.net/Ronny72/rtprtcp-ppt
www.cs.fsu.edu/~xyuan/cis6930_ipqos/voip2.ppt

Friday, February 1, 2013

multimedia video architecture / framework




TMS320DM6437 DaVinci Technology One-Day Workshop


http://processors.wiki.ti.com/index.php/TMS320DM6437_DaVinci_Technology_One-Day_Workshop
http://software-dl.ti.com/trainingTTO/trainingTTO_public_sw/dm643x1day/DM643x1day%20COLOR.pdf
http://www.ti.com/tool/dspbios
http://www.kanecomputing.co.uk/pdfs/tmdsevm6446%20getting%20started%20guide.pdf


http://www.embedded-systems-portal.com/CTB/ALU__Arithmetic_Logic__Unit,10051.html


http://www.ti.com/lit/ug/sprueg8/sprueg8.pdf
http://www.ti.com/lsds/ti/tools-software/rtos.page
http://en.wikipedia.org/wiki/SYS/BIOS
http://www.eetimes.com/design/signal-processing-dsp/4017478/Real-Time-Operating-Systems-for-DSP-part-3


Android Multimedia Framework Overview
http://www.windriver.com.cn/mobile/pdf/08_Android_Multimedia_Framework_Overview.pdf
http://library.developer.nokia.com/index.jsp?topic=/GUID-E35887BB-7E58-438C-AA27-97B2CDE7E069/GUID-6E52C463-5489-591F-859D-68EAD5BA80FD.html

http://www.google.co.in/imgres?imgurl=http://www.freedesktop.org/wiki/GstOpenMAX%3Faction%3DAttachFile%26do%3Dget%26target%3Dgst-openmax.png&imgrefurl=http://kcchao.wikidot.com/multimedia-framework&h=502&w=801&sz=103&tbnid=KPYkFCNyCJ0mDM:&tbnh=79&tbnw=126&prev=/search%3Fq%3Dmultimedia%2Bframework%26tbm%3Disch%26tbo%3Du&zoom=1&q=multimedia+framework&usg=__QN2OYUrrr8Kp9Qnmk0Fj57m7wmg=&docid=XObn-J1_Qx9kfM&hl=en&sa=X&ei=CwoJUcOKM8TMswam34CADg&sqi=2&ved=0CDoQ9QEwAw

http://www.arm.com/community/partners/product_images/4725.jpg
http://meegoworld.blogspot.in/2010/12/gist-on-multimedia-framework-in-meego.html





video processing Arc
http://www.arm.com/community/partners/product_images/3092.jpg

http://www.arm.com/community/partners/display_product/rw/ProductId/3099/

http://www.iwavesystems.com/direct-show-multimedia-on-i-mx6





http://www.ti.com/lit/ug/sprue66e/sprue66e.pdf
http://www.ti.com/lit/ds/symlink/tms320dm6437.pdf










An operating system abstraction layer (OSAL) provides an application programming interface (API) to an abstract operating system making it easier and quicker to develop code for multiple software or hardware platforms.












http://www.adeneo-embedded.com/Services/BSP-and-Driver-Development
http://en.wikipedia.org/wiki/Operating_system_abstraction_layer
http://en.wikipedia.org/wiki/Board_support_package
http://www.ti.com/tool/dspbios
http://www.qnx.com/developers/docs/6.3.2/photon/multimedia2/overview.html


DSP/BIOS™ kernel is a scalable real-time multi-tasking kernel, designed specifically for the TMS320C6000™, TMS320C55x™, and TMS320C28x™ DSP platforms. Together with its associated networking, microprocessor-DSP communications, and driver modules, DSP/BIOS kernel provides a solid foundation for even the most sophisticated DSP applications. DSP/BIOS kernel has been proven in thousands of customer designs and is one of the world’s mostly widely used real-time operating systems. DSP/BIOS kernel requires no runtime license fees and is backed by Texas Instruments worldwide training and support organizations.


DSP/BIOS Multithreading
To provide the fast response required by DSP applications, DSP/BIOS kernel augments the traditional tasking model with additional threading mechanisms. Software Interrupts are lightweight pre-emptible threads that share a common stack. This results in lower memory overhead and faster context switch times, as there is no need to save and restore a task stack. Periodic Functions are time-triggered high-priority threads that can be easily set up to process samples of data arriving at fixed time intervals, simplifying the design of multirate systems.
DSP/BIOS IPC Mechanisms
DSP/BIOS kernel offers several IPC mechanisms for interthread communication. Semaphores and Locks provide basic synchronization and resource locking. Mailboxes enable synchronous transfer of fixed sized messages between tasks. Message queues enable zero copy, variable-length message passing between any DSP/BIOS kernel thread type. The exact memory for each message is allocated when the message needs to be sent. Message passing is transparent at the application level and can be within a single DSP or between multiple DSPs. For inter-DSP communication, a Message Queue Transport is required. Some of these (for example, Serial RapidIO®) are available pre-tested from TI.
DSP/BIOS Multicore Support
DSP/BIOS kernel fully supports TI’s multicore DSP solutions. For devices designed to execute the same image on multiple cores, DSP/BIOS kernel provides shared image support, maximizing the amount of local core memory available for data. In addition, a shared memory transport is provided to enable core-to-core communication using the DSP/BIOS MSGQ module. This transport utilizes the underlying hardware features such as atomic access monitors or hardware semaphores to provide the most efficient implementation.
DSP/BIOS Interrupt Management
DSP/BIOS kernel includes a comprehensive set of services for interrupt management. The interrupt dispatcher enables developers to write ISRs in C by performing low-level operations such as context save/restore and temporary disabling of the scheduler. This approach reduces code size by eliminating the need to specifically add such code to each ISR. To reduce data memory requirements, all ISRs use a common stack rather than the stack of the task they interrupt, with the exception of the first interrupt context, which is stored on the task stack for performance reasons. The HWI and Event Combiner modules provide additional APIs for enabling/disabling interrupts and multiplexing multiple interrupt sources on to a single pin.
DSP/BIOS Power Management
For TI DSPs used in portable applications where power consumption is a key consideration, such as the TMS320C5509 DSP, DSP/BIOS kernel offers a range of power management features. These may include automatically idling the CPU when in the IDL task, voltage and frequency scaling APIs, sleep or hibernate APIs, automated idling of peripherals when the peripheral domain is not in use, and a register/notify mechanism for coordinating complex system-wide power management.
DSP/BIOS OS-Aware Analysis & Debug
In conjunction with Code Composer Studio™ IDE, DSP/BIOS kernel provides several tools to aid debugging and optimization of multithreaded applications. The Kernel Object Viewer enables a developer to check the status of OS objects such as tasks, mailboxes, and semaphores, including whether a task is ready, running, or blocked, and which tasks are blocked on an IPC. The Real-Time Analysis tools display the thread execution and switching sequence, average and maximum execution times for a thread, and system CPU load, as well as providing a very low overhead printf capability.

DSP/BIOS Link

Many DSP-based applications, ranging from digital cameras to communications switches, use a microprocessor (GPP) to control one or more DSPs. To meet this need, TI is increasingly delivering devices that offer an ARM® and DSP core in the same package. DSP/BIOS Link is software designed to facilitate communication between the ARM and the DSP in SoC devices.
To develop applications that reside on GPP+DSP solutions, developers must implement communications software that enables data and control information to be exchanged between the GPP and the DSP. In addition, the GPP must also boot the DSP and often control which algorithms the DSP executes for a specific task. DSP/BIOS Link eliminates the need to create these functions from scratch by providing a robust set of MCU-DSP communications services including:
  • Variable-length messaging between the GPP and DSP
  • Ring buffer communication between GPP and DSP
  • Point-to-point, asynchronous data streaming between the GPP and DSP
  • Bootload the DSP from GPP
  • Pre-tested GPP-DSP communications driver support for select devices
DSP/BIOS Link is available for both SoC devices, such as DaVinci™, where the ARM and DSP communicate using shared memory, and discrete DSPs offering a PCI interface. DSP/BIOS Link is provided as a source code porting kit and includes pre-tested ports for some versions of embedded Linux.



Multimedia Framework Overview


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Multimedia Framework Overview

This chapter provides an overview of the Multimedia Framework, and covers:

Multimedia architecture

The Multimedia library architecture is modular, meaning that it consists of units that can be interchanged with each other to provide only the functionality you need. In addition, because it uses the Addon Interfaces library to define its standard interfaces, you can write new components (such as codecs), and easily incorporate new components written by QNX or third parties as they become available, in some cases without having to recompile your application.
A filter is the basic building block of the Multimedia framework. Multimedia Filters:
  • are compiled as DLLs or libraries. The DLL versions of the filters are located by default in lib/dll/mmedia (on the target). The library versions are used at compile-time if your application is linking against them statically.
  • perform a specific task on multimedia data, such as reading a file from disk, parsing, decoding, or writing data to an audio device
  • are plugins, and therefore implement a standard interface that the Multimedia library understands. The interfaces are defined in the Addon Interface library, aoi.
To process a multimedia file, your application uses only the filters it needs to get the multimedia data, process it, and send it to a target device. We classify filters based on their specific task. A filter can be a:
Reader
Reads data from a source. Examples are audio card readers, data stream readers, and video capture card readers.
Parser
Parses a stream of data into component parts. Examples are MPEG bitstream parsers, WAV format parsers, and AVI format parsers.
Decoder
Decodes compressed or encoded data. Examples are mpeg audio & video decoders, and divx decoders.
Encoder
Encodes raw data into a specific format. Examples are mpeg audio & video encoders.
Writer
Sends data to a destination. Examples are audio card writers, video output writers, and output file writers.
A filter is a generic object. Its functionality is determined by the way it processes data, and the interfaces it implements. A Multimedia library interface defines the set of methods that the library expects filters of a specific type to have. For example, all filters must implement the create and destroy methods defined in the AODeConstructor interface so that the library can create and destroy them, while only filters that read data from a source need to implement the MediaReader interface. The implementation of an interface is declared as a structure of pointers to implemented functions in a defined order.
Each filter can have multiple input and output channels, so if you have a file format that's interleaved with more than one data stream, you can have as many output data channels as the input data stream contains. This is how the MPEG System parser works, for example -- it parses MPEG System data into two streams, video and sound. An MPEG System encoder filter works the opposite way; it has separate input channels for sound and video, and one output channel.
We already provide a number of filters written for the Multimedia framework, but if you need a new one, you have to write only the decoder, parser, or other filter that hasn't already been written. Because the multimedia architecture uses a "plugin" framework, each filter component can easily be integrated (plugged in) with existing filters.
To use the Multimedia library, your application sets up a graph, an abstract object that encapsulates the multimedia filters needed to process a multimedia stream. A graph is stored as a MmGraph_t structure. It's built and destroyed at run time by the player application, and is specific to a particular media stream. Your application adds to the graph all the filters required to process multimedia data from source to destination.
If you know the specific filter required to process the multimedia stream, you can add it to the graph by name. However, a more flexible approach is to use functions that query the library and find the best filter for the data. In this way your application can handle any media type that the library's filters can handle, and use any new filters added to the library without being recompiled.
In the example below, six filters are used to read, parse, decode, and present an MPEG media stream. Each filter has an input channel and at least one output channel, except for special purpose "media reader" and "media writer" filters, which are at the beginning and end of the filter chain.

Multimedia graph example

Multimedia graph example.
In the filters we provide, multimedia streams are synchronized by the audio stream, if present. In the MPEG example above, the writer filters don't communicate directly. Instead, they use the audio writer filter MediaClock interface to the Multimedia library (all filters have hooks to the library) to determine the correct media time. In this way, the video writer continuously checks its media time against the audio writer, and synchronizes its playback accordingly.




A multimedia framework is a software framework that handles media on a computer and through a network. A good multimedia framework offers an intuitive API and a modular architecture to easily add support for new audio, video and container formats and transmission protocols. It is meant to be used by applications such as media players and audio or video editors, but can also be used to build videoconferencing applications, media converters and other multimedia tools.
In contrast to function libraries, a multimedia framework provides a run time environment for the media processing. Ideally such an environment provides execution contexts for the media processing blocks separated from the application using the framework. The separation supports the independent processing of multimedia data in a timely manner. These separate contexts can be implemented as threads.

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