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Adaptive Robust Waveform Selection for Unknown Target Detection in Clutter
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作者 Lu-Lu Wang Hong-Qiang Wang +1 位作者 Yu-Liang Qin Yong-Qiang Cheng 《Journal of Electronic Science and Technology》 CAS 2014年第2期229-234,共6页
A basic assumption of most recently proposed waveform design algorithms is that the target impulse response is a known deterministic function or a stochastic process with a known power spectral density (PSD). Howeve... A basic assumption of most recently proposed waveform design algorithms is that the target impulse response is a known deterministic function or a stochastic process with a known power spectral density (PSD). However, it is well-known that a target impulse response is neither easily nor accurately obtained; besides it changes sharply with attitude angles. Both of the aforementioned cases complicate the waveform design process. In this paper, an adaptive robust waveform selection method for unknown target detection in clutter is proposed. The target impulse response is considered to be unknown but belongs to a known uncertainty set. An adaptive waveform library is devised by using a signal-to-clutter-plus-noise ratio (SCNR)- based optimal waveform design method. By applying the minimax robust waveform selection method, the optimal robust waveform is selected to ensure the lowest performance bound of the unknown target detection in clutter. Results show that the adaptive waveform library outperforms the predefined linear frequency modulation (LFM) waveform library on the SCNR bound. 展开更多
关键词 Adaptive waveform library CLUTTER minimax robust selection target detection
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