Sparsity-aware multitarget localisation for distributed MIMO radar against phase synchronisation mismatch

摘要

The authors address the problem of coherent multitarget localisation for distributed multiple-input multiple-output (MIMO) radar, in the presence of phase synchronisation mismatch between each transmitter-receiver pair. The inherent sparsity of targets in the surveillance area can be exploited to represent radar data and then target locations are accurately estimated using sparse reconstruction. However, due to the difficulty of perfect phase synchronisation, the localisation technique is usually required to eliminate the phase errors. This study jointly considers the phase error correction problem in the context of multitarget localisation. In this novel method, the direct position determination of multitarget is obtained by estimating the spare reflection coefficients and phase errors alternately. Numerical simulation results demonstrate that the authors' iterative block sparse Bayesian learning via maximum likelihood estimation algorithm obtains enhanced estimation accuracy against the phase synchronisation mismatch.