A novel maximum likelihood target detection with antenna selection for active phased array radar system

Abstract

Active phased array radar is currently the development trend of radar system. It consists of thousands of separate Transmit/Receive (T/R) modules with the power transmission function to achieve the phase and amplitude modulation. For a radar system, target detection is always the most important issue. Basically, some antennas perform the tracking task, while the remaining antennas conduct the search function after a radar system detects the targets. With such multiple T/R modules or namely, the multiple input multiple output (MIMO) scheme, the radar can have larger radar gain advantage to increase its search region or capacity. However, as the increase of antennas adopted by the active phased array radar, the required hardware and computational complexity also becomes a serious concern for the radar system in practical realizations. In literatures, one of the solutions for avoiding such drawback is to select the antennas properly and effectively for target detection and tracking. In this paper, we proposed a novel target detection method based on the maximum likelihood (ML) criterion to predict and locate the targets correctly and optimally for active phased array radar system. Besides, an antenna selection method is also proposed and combined to the target detection in reducing the required hardware and computational complexity. The simulation results show that the proposed methods can not only take the advantage of reducing hardware and computational complexity, but also maintain the performances of the radar system.