Sparsity-aware target localization using TDOA/AOA measurements in distributed MIMO radars

Abstract

In this paper, a sparsity-aware hybrid target localization method in multiple-input-multiple-output (MIMO) radars from time difference of arrival (TDOA) and angle of arrival (AOA) measurements is proposed. This method provides a maximum likelihood estimate of target position by employing compressive sensing techniques. A blockwise approach is addressed in order to achieve better accuracy for a constant computational complexity. The mismatch problem due to grid discretization is also tackled by a dictionary learning technique. The Cramer–Rao lower bound for this model is derived as a benchmark. Numerical simulations are included to corroborate the theoretical developments.

Keywords

• Multiple-input-multiple-output (MIMO) radar
• Target localization
• Compressed sensing (CS)
• Time difference of arrival (TDOA)
• Angle of arrival (AOA)