3D motion-based high-resolution imaging techniques for automotive radar

Autonomous driving is one of the most popular research topics. Radar technology is used for many applications of ADAS and is considered one of the key technologies for HAD. It has unique advantages compared with other sensors, especially its capabilities during adverse weather conditions and Doppler information extraction. Required by autonomous applications, radar has to change its historical role from a simple detector to an imaging sensor, which requires not only the range and Doppler resolution ability but also a high spatial resolution, i.e., the azimuth and the elevation angle resolution. To address this problem, in this thesis, new signal processing algorithms are proposed, which pave the way to improved performance of the automotive radar sensor.
The FMCW waveform is widely used in current automotive applications due to its low cost and simplicity. MIMO array techniques exploit the spatial diversity of transmit and receive antenna arrays and have been exploited in current automotive radar because of their ability to achieve high angular resolution with a few antennas. Platform movement is one of themain characteristics of automotive radar, which introduces movement uncertainty compared with radars at fixed locations but provides an opportunity to use the movement to boost the angular resolution. Thus, FMCW waveform and MIMO antenna array are the main research subjects in this thesis.....