AI-Based Multi-Target Localization with Multi-Tx and Single-Rx Frequency Diverse Array Radar

Recently, frequency diverse array (FDA) systems have gained attention in target localization due to their time-varying and range-angle-dependent beam-focusing characteristics, which are different from those of conventional phased array (PA) systems. However, analysis of the received signal is challenging due to its time-varying nature. In this paper, an artificial intelligence (AI)-based multi-target localization system is proposed, which works with a simple multi-Tx (Transmitter) and single-Rx (Receiver) FDA system. The AI-based model can find the relationship between the locations of the targets and the received signal, since all the necessary information is contained in the time-varying reflected signal. With a simple multi-Tx, single-Rx model, the system can be implemented in the real world. It is verified that the proposed system can locate at least two targets simultaneously with reasonable performance.