Joint Detection and Localization of Multiple Moving Targets in a Distributed Radar System

This article investigates the joint detection and localization (JDL) problem of unknown number multiple moving targets in a distributed radar system. Upon formulating this problem as a composite multiple hypothesis testing problem, we derive a generalized information criterion (GIC)-based detector to simultaneously extract targets and estimate their unknown parameters, including their number, amplitudes, locations, and velocities. Although this solution theoretically achieves impressive performance by using raw echoes data to jointly detect and estimate multiple targets at the fusion center (FC), it also requires an unbearable computational load in practice. It is because multiple targets are expected to be simultaneously extracted by realizing a joint maximization task and making an enormous search. To reduce the computational burden, we propose a low-complexity solution to decompose the high-dimensional problem into several low-dimensional optimization problems. For local radars to undertake a portion of the calculations, the log-likelihood ratio (LLR) data are generated at each local station and then completely transmitted to the FC. Different from extracting multiple targets simultaneously using a GIC-based detector, we devise an extended successive-interference-cancellation (SIC) algorithm to detect targets one by one at the FC, and meanwhile, the parameters of targets can be simultaneously estimated at each iteration. Finally, the effectiveness of the proposed algorithm is demonstrated by the provided simulations.