MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment

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...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-15
Main Authors: Yao, Yu, Li, Zeqing, Liu, Haitao, Miao, Pu, Wu, Lenan
Format: Article
Language:English
Subjects:
Algorithms
Asymptotic properties
Azimuth
Clutter
Design optimization
Energy requirements
Extended target
filter bank design
Filter banks
generalized fractional programming (GFP)
Impulse response
Interference
Iterative methods
MIMO communication
minorization-maximization (MM)
multiple-input multiple-output (MIMO) radar
Performance measurement
Radar
Robust design
Target detection
transceiver optimization
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Summary: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.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2022.3184366