Array diagnosis using signal subspace clustering in MIMO radar

Abstract

In multiple-input multiple-output (MIMO) radar system, timely array diagnosis method is needed for transmit and receive arrays. To avoid using extra probes or measurements, a novel signal subspace clustering-based array diagnosis method is proposed. By exploiting the relationship between the signal subspace extracted from the covariance matrix and the steering matrix in MIMO radar, the feature of the anomalous data points in signal subspace caused by faulty elements is examined. Consequently, the anomalies are grouped into one cluster by density peaks clustering algorithm, and the faulty antennas in transmit and receive arrays can be identified based on the clustering results. Numerical simulation results demonstrate the superiority of the proposed approach in array diagnosis problem for MIMO radar.