Frequency Increment Optimization With FDA-MIMO Radar for Target Localization

This letter presents an optimization approach for frequency increments tailored to Frequency Diverse Array (FDA)-Multiple-Input Multiple-Output (MIMO) radar for target localization. We start to formulate the problem as minimizing the Cramér-Rao Bounds (CRBs) for both range and angle estimation, subject to practical constraints on the frequency increments. To facilitate optimization, the objective function is mathematically transformed, which results in a maximization problem, leveraging its inherent non-negativity of both the numerator and denominator. To address the resultant non-convex and NP-hard optimization problem, a Minorization-Maximization (MM)-Maximum Block Improvement (MBI) algorithm is devised by partitioning the frequency increment vector into distinct blocks, allowing for alternating maximization. In particular, each frequency increment is refined with the MM algorithm, while holding the others fixed, and only the block yielding the maximum objective increment is updated within each iteration. Simulation results are provided to demonstrate the excellent target localization of our proposed approach.