Moving Target Detection Using a Distributed MIMO Radar System With Synchronization Errors

This article addresses the detection and estimation problems of a distributed multiple-input and multiple-output (MIMO) radar system with synchronization errors. In such cases, the outputs of all waveform-specific matched filters contain errors in the resulting time delay estimates, which will cause biases in the corresponding estimation of the active range cells. To overcome the impact resulting from the presence of such errors, a joint robust detection and estimation framework is introduced. We first propose an extended generalized likelihood ratio test (GLRT) detector exhibiting the constant false alarm rate (CFAR) property to robustly detect multichannel misaligned data by extending the matching range cells among multiple channels, on which a Radon-Fourier transform (RFT) is employed to coherently accumulate the response of potentially moving targets. Then, a clustering algorithm is employed to obtain the unique time delays and Doppler shifts for each channel from the redundant results generated by the detector. Finally, we estimate the target locations and their velocities using the estimated multichannel time delays and Doppler shifts using a weighted least squares (WLSs) formulation, which is reformulated as a convex optimization problem in order to allow for an efficient solution. Both numerical and experimental results demonstrate the performance and the robustness of the proposed framework as compared with other recent approaches.