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Accelerate ADAS dev't with radar signal analysis

Posted: 30 Jul 2014  Print Version  Bookmark and Share

Keywords:advanced driving assistance systems  ADAS  parking-assistance system  Radar  LFMCW 

According to a study by the Audi Accident Research Unit, more than 90 per cent of all accidents on the road can be attributed to human error. Furthermore, the accident rate could be drastically reduced by implementing advanced driving assistance systems (ADAS), which are similar to the autopilot systems used in aircraft. Although it might sound like something from a science-fiction novel, automated driving has already become reality in many cars in the luxury class and now increasingly in the medium-price class too. Besides the now classic parking-assistance system, there are other functions to help with everyday driving such as a lane-change assistant, blind-spot detection and adaptive cruise control. While a parking-assistance system is based on a clear yes/no procedure where information is paramount, adaptive cruise control can involve modifying the driving speed in response to the vehicle in front, for example.

Maintaining the flow of traffic
Another reason why automated driving has become such an important topic is related to the rapid development of megacities. The International Energy Agency has noted that as cities like Moscow, Shanghai, Tokyo and Mexico City attain populations of 20 or even 30 million, they are experiencing a dramatic increase in vehicle usage. Today, there are already more than one billion vehicles in the world. In 2025, there will be 1.5 billion vehicles, including 400 million in China alone, where they will be concentrated in metropolitan areas. In such a context, automated driving will no longer be merely a question of road safety and convenience. Instead, it will offer the only way to keep traffic flowing in cities, where the average speed is already less than 20 km/h due to extreme road usage.

Radar technology for automotive applications
Radar technology for use in cars differs in several ways from the military applications for which radar was originally developed. Firstly, the automotive industry is subject to enormous cost pressures, so components must be much more economical. In addition, due to the very limited space for radar sensors behind plastic bumpers, the sensors must be extremely compact.

Compared with camera and ultrasonic applications, radar has a major advantage in that no visual contact is required between the radar sensor and the object to be detected. This saves costs in the production of bumpers and can also be exploited in the vehicle design. However, it is still a challenge to compensate for the attenuation of the transmit and receive signals as they pass through the different layers of material in the bumper as well as the (metallic) paint. Such compensation is implemented with postprocessing in the radar sensor.

For automotive applications, vehicle manufacturers can currently make use of four frequency bands at 24GHz and 77GHz with different bandwidths. While the 24GHz ISM band has a maximum bandwidth of 250MHz, the 24GHz ultrawideband (UWB) already offers up to 5GHz; however, this is allowed only until the end of 2022 due to international regulations. The band that will be available past this date with up to 4GHz bandwidth lies between the frequencies of 77GHz and 81GHz. It is already used for forward-looking applications. Since the signal bandwidth determines the range resolution, it is very important in radar applications. Accordingly, the other allocated frequencies of 122GHz and 244GHz for this application with a bandwidth of only 1GHz will see little use in the automotive industry and are restricted to research projects until further notice.

Speed plus distance
When using radar signals in such applications, developers generally want to simultaneously determine the speed and distance of multiple objects within a single measurement cycle. However, ordinary pulse radar cannot easily handle such a task. Based on the timing offset between the transmit and receive signals within a cycle, only the distance can be determined. If the speed must also be determined, a frequency-modulated signal is used, e.g. a linear frequency-modulated continuous-wave (LFMCW) signal.


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