Influence of Channel Count and Array Sparsity on the Detection Performance of 4D Imaging Radars

Separability, detection capability, and height estimation performance are key measures of high performance 4D imaging radars. While many different sensors have been presented in recent years, no sensor-independent comparison of the performance achievable with differing array realizations was given. Therefore, in this work in total 113 sub-arrays of one large uniform rectangular array are analyzed. Measurements of real-world scenarios are performed with a high-resolution 4D imaging radar system with 1728 virtual channels on the static edge case to assess the performance in the angular domain. Regarding the above-mentioned performance criteria, three main conclusions can be derived from the performed analysis: Although the angular resolution depends on the array size, the separation capability of objects with small radar cross section from stronger ones depends on the channel count and not the aperture size. In scenarios with many targets located in the mid-range of the sensor, the detection capability increases at a constant channel count for smaller arrays with a lower sparsity in contrast to larger ones with less channels. Hereby, increasing the fill factor while keeping the aperture size constant is more beneficial to the performance than increasing the aperture size while keeping the fill factor constant.