Sequential-Compressive-Range Azimuth Estimation in Radar Signal Processing

Research in the field of radar signal processing including the one on target detection algorithm continuously attracts a lot of interest from signal processing community. One interesting contribution is the applications of compressive sensing (CS) algorithm in radar signal processing by exploiting the existence of sparsity in some domains such as spatial, azimuth, range, and time domain. This exploitation allows the reduction of the number of receiver elements and the amount of time samples. We investigate the application of CS in frequency modulated continuous wave (FMCW) radar to detect multiple targets and estimates the azimuth and range parameters sequentially to estimate the target location. The azimuth angle estimation is performed at the radio frequency (RF) stage by exploiting spatial-domain CS to permit the reduction of the number of receiver elements. Next, in the intermediate frequency (IF) stage, the time-domain CS is conducted to reduce the number of time samples in each chirp before the range estimation is performed. The simulation study shows that, by using this sequential compressive range-azimuth estimation, a single chirp is sufficient to accurately estimate the azimuth angles without error and to estimate the range of the targets, where the average tolerated errors is 1.6 km, which is slightly larger than the range resolution of 1.2 km.