Joint Design of Horizontal and Vertical Polarization Waveforms for Polarimetric Radar Via SINR Maximization

For an extended target with different polarimetric response, one way of improving the detection performance is to exploit waveform diversity on the dimension of polarization. In this paper, we focus on joint design of transmit signal and receive filter for polarimetric radars with local waveform con...

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Bibliographic Details
Published inIEEE transactions on aerospace and electronic systems Vol. 59; no. 3; pp. 1 - 39
Main Authors Cheng, Xu, Wu, Linlong, Ciuonzo, Domenico, Wang, Wei
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:For an extended target with different polarimetric response, one way of improving the detection performance is to exploit waveform diversity on the dimension of polarization. In this paper, we focus on joint design of transmit signal and receive filter for polarimetric radars with local waveform constraints. Considering the signal-to-interference-plus-noise ratio (SINR) as the figure of merit to optimize, where the average Target-Impulse-Response Matrix (TIRM) within a certain Target-Aspect-Angle (TAA) interval is employed as the target response, the waveform is decomposed and then designed for both horizontal and vertical polarization segments, subject to energy and similarity constraints. An iterative algorithm is proposed based on the majorization-minimization (MM) method to solve the formulated problem. The developed algorithm guarantees the convergence to a B-stationary point, where in each iteration, optimal horizontal and vertical transmit waveforms are respectively solved by using the feasible point pursuit and successive convex approximation (FPP-SCA) technique. Experiment results show the effectiveness of the proposed algorithm, the robustness of the output SINR against the TAA change, and the advantages of polarization diversity and local design.
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ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2022.3223887