MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT(2022)

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摘要
Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter bank in MIMO structure to improve extended target detection capability in signal-dependent interference environment. Considering the average and the worst case signal-to-interference-plus-noise ratio (SINR) at the output as the performance metrics to maximize, we propose two iterative optimization procedures, under similarity and energy requirements on the radar code. The convergence property and asymptotic optimality of two algorithms are analyzed. Finally, simulation results have displayed that two proposed optimization strategies achieve higher objective values than the existing approaches, and share reasonable computational burden.
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关键词
Azimuth, Clutter, Extended target, filter bank design, generalized fractional programming (GFP), minorization-maximization (MM), multiple-input multiple-output (MIMO) radar, transceiver optimization
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