An efficient and safe approach of radar signal capturing and processing : Page 5 of 7

June 04, 2015 // By Peter Aberl, Texas Instruments
On the way to autonomous driving advanced driver assistance systems (ADAS) based on vision, LIDAR and radar have to gradually supersede the driver’s visual sense. To achieve this challenging goal ADAS sensors have to further evolve to become more reliable, more accurate, safer and more efficient. This article focuses on automotive radar and specifically discusses signal processing steps of a modern fast chirp radar system. An example shows how radar signal capturing and processing can be realized in an efficient and safe way. Additional automotive radar aspects like low power, small form factor and scalability are also touched.
The OS-CFAR detector is applied to each element of the range-Doppler-azimuth power array. The output is a sparse three dimensional target array that is passed on to an application-specific tracking algorithm. This tracker is an estimator that uses the target array as reference input in order to correlate the target information with existing tracks, i.e. objects. Moreover the tracker also takes care of removing old tracks and creating new tracks.

Additional Key Requirements in Automotive Radar

As mentioned in the beginning, besides a superior radar signal processing performance, other aspects like functional safety, low power and smaller sensor size are gaining importance in Automotive. Radar sensors are providing safety-critical commands to chassis systems like anti-lock braking, electrical power steering or active suspension that impact the dynamics of a car. E.g. a false positive autonomous emergency brake command can be fatal and hence is rated as safety critical. A power efficient implementation helps to reduce carbon dioxide emissions, simplifies the thermal design of the sensor and may allow using cheaper housing material. Furthermore a low power design makes it easier to reduce the form factor of the sensor due to relaxed power dissipation constraints.

Example of a Radar Capture and Processing Hardware

Now let’s look at an actual example that is based on the AFE5401-Q1 and the TDA3xR System-on-Chip (SoC) from Texas Instruments as depicted in Figure 4. This exemplary implementation has 4 receive channels. The TDA3xR device family facilitates up to 8 receive channels allowing the implementation of a scalable set of radar sensors.

Figure 4: System Block Diagram for Radar Baseband Processing (Example). Click image for full resolution.

Both devices are or will be Automotive qualified and are optimized for radar applications. The AFE5401-Q1 is a high-performance analog front-end with 4 identical channels supporting simultaneous conversion. Each channel comprises a low-noise amplifier (LNA), an optional equalizer, a programmable gain amplifier (PGA) and an anti-aliasing filter followed by a high-speed 12-bit analog-to-digital converter (ADC) at up to 25 MSPS per channel. The exhaustive pre-conditioning considerably reduces the need for additional external components. The equalizer can compensate range dependent losses.

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