Parametric Joint Target Detection and Localization Using Message Passing for Distributed Passive MIMO Radar

This paper addresses the challenge of joint target detection and localization with a distributed dual-channel passive multiple-input multiple-output (MIMO) radar, which comprises multiple non-cooperative illuminators of opportunity and receivers. In conventional approaches, the target position is typically obtained by conducting exhaustive grid search for the peak of the test statistics. To reduce the errors due to grid mismatch, the number of grid cells needs to be large, leading to high computational complexity and hampering real-time processing capabilities. Moreover, these approaches are ineffective under strong direct-path interference. In this paper, an efficient factor graph approach for joint target detection and localization is proposed, which detects and localizes the target through parameter estimation, significantly reducing the computational complexity while maintaining high robustness. In particular, we introduce a binary target existence variable to represent the presence or absence of a target and reformulate the problem as the computation of the marginal posterior probabilities of unknown parameters. Then an efficient message passing algorithm is developed to solve the reformulated problem. Extensive simulation results demonstrate that the proposed approach outperforms state-of-the-art approaches in various scenarios, while with much lower computational complexity.