Image and Signal Processing Methods

Adaptive waveform optimization design for target detection in cognitive radar

[+] Author Affiliations
Xiaowen Zhang

Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Information and Communication Engineering, Minhang District, Shanghai, China

Kaizhi Wang, Xingzhao Liu

Shanghai Jiao Tong University, Minhang District, Shanghai, China

J. Appl. Remote Sens. 11(1), 015024 (Mar 20, 2017). doi:10.1117/1.JRS.11.015024
History: Received November 16, 2016; Accepted February 28, 2017
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Abstract.  The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

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Citation

Xiaowen Zhang ; Kaizhi Wang and Xingzhao Liu
"Adaptive waveform optimization design for target detection in cognitive radar", J. Appl. Remote Sens. 11(1), 015024 (Mar 20, 2017). ; http://dx.doi.org/10.1117/1.JRS.11.015024


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