Distributed MIMO Radar Target Detection in Multipath Clutter Environments With Time Reversal

Abstract

The distributed multiple-input–multiple-output (MIMO) radar, as an emerging active sensing technology, uniquely leverages spatial diversity to significantly enhance radar detection performance. The time reversal (TR) technology can be incorporated into radar systems to further improve detection performance by effectively utilizing multipath signals. However, the coexistence of multipath signals and clutter presents a formidable challenge to radar detection, potentially diminishing its performance. To tackle this challenge, we propose a distributed MIMO radar detection algorithm that integrates the TR technology with a power allocation (PA) approach tailored for multipath clutter environments. Specifically, the algorithm initially leverages TR technology to efficiently process and exploit multipath signals, while concurrently optimizing the distribution of radar transmit power through strategic allocation, thereby bolstering detection performance in complex environments. On this foundation, a distributed MIMO radar signal model is established, and the TR-PA-MIMO detector is derived, embodying the proposed solution. Furthermore, a conventional distributed MIMO (CD-MIMO) detector is developed as a benchmark for comparative analysis. Several other detection algorithms are also evaluated under identical conditions to assess their relative performance. The Monte Carlo simulations and theoretical analysis demonstrate that the proposed detection algorithm outperforms all other algorithms for distributed MIMO radar systems operating in multipath clutter environments.