Target recognition with high-fidelity target signatures and adaptive waveforms in MIMO radar

In previous work, we have demonstrated the advantage of a closed-loop radar system that provides a feedback loop from radar receiver to transmitter in a widely separated multi-input multi-output (MIMO) radar scenario. The results for widely separated MIMO radar showed performance benefit when exploiting spatial diversity with adaptive waveforms. However, the bistatic target signatures used in prior work were simply assumed to be impulse functions with complex-Gaussian reflectivity, which models a wide bistatic angle having poor range resolution. In this work, we use high-fidelity bistatic target signatures obtained by commercial electromagnetic FDTD software (XFdtd), and apply to the widely separated MIMO radar scenario. We optimize the waveform based on both the bistatic and monostatic target signatures and compare the performance to non-optimized (wideband) and partially optimized (optimized for monostatic target signatures only) waveforms. We also compare to results that ignore either the bistatic path (exploit monostatic only) or the monostatic path (exploit bistatic only). Constant-modulus constraints are enforced on the adaptive waveforms, and template-based classification is adopted for final decision.