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基于知識輔助的MIMO雷達(dá)波形設(shè)計方法

關(guān)鍵,  李秀友,  黃勇,  薛永華

關(guān)鍵, 李秀友, 黃勇, 薛永華. 基于知識輔助的MIMO雷達(dá)波形設(shè)計方法[J]. 電子與信息學(xué)報, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
引用本文: 關(guān)鍵, 李秀友, 黃勇, 薛永華. 基于知識輔助的MIMO雷達(dá)波形設(shè)計方法[J]. 電子與信息學(xué)報, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
GUAN Jian, LI Xiuyou, HUANG Yong, XUE Yonghua. Knowledge-aided MIMO Radar Waveform Design Method[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
Citation: GUAN Jian, LI Xiuyou, HUANG Yong, XUE Yonghua. Knowledge-aided MIMO Radar Waveform Design Method[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008

基于知識輔助的MIMO雷達(dá)波形設(shè)計方法

doi: 10.11999/JEIT160008 cstr: 32379.14.JEIT160008
基金項目: 

國家自然科學(xué)基金(61471382, 61401495, 61201445, 61179017, 61501487)，山東省自然科學(xué)基金(2015ZRA06052)，泰山學(xué)者建設(shè)工程專項經(jīng)費

Knowledge-aided MIMO Radar Waveform Design Method

Funds: 

The National Natural Science Foundation of China (61471382, 61401495, 61201445, 61179017, 61501487), Natural Science Foundation of Shandong Province (2015ZRA 06052), Special Funds of Taishan Scholars Construction Engineering

  • 摘要: 該文針對雷達(dá)系統(tǒng)受到天線主瓣和副瓣雜波以及強(qiáng)干擾影響時性能下降問題，提出基于距離擴(kuò)展目標(biāo)和雜波先驗信息的MIMO雷達(dá)波形設(shè)計方法。首先建立了目標(biāo)函數(shù)，綜合考慮了波束主瓣增益、旁瓣雜波抑制能力以及目標(biāo)輸出SCNR的改善性能；然后在優(yōu)化問題求解中對約束條件進(jìn)行松弛，使得波形矩陣空域和時域2維解耦合，從而實現(xiàn)空域波束形成和時域波形設(shè)計獨立優(yōu)化求解；其次利用L-BFGS算法設(shè)計恒模的發(fā)射波形矩陣，形成低副瓣的波束方向圖和較深的強(qiáng)雜波抑制凹口，并基于目標(biāo)輸出SCNR最大化準(zhǔn)則，利用迭代算法分步求解優(yōu)化的主瓣發(fā)射波形和接收濾波器；最后通過電磁仿真的距離擴(kuò)展目標(biāo)數(shù)據(jù)驗證所提算法的有效性。
    Abstract: In order to solve the problem of performance degradation when radar system is influenced by clutter from mainlobe and sidelobe, MIMO radar waveform design algorithm based on knowledge of range-spread target and clutter is investigated. Firstly, an optimization cost function is established, which includes mainlobe gain, sidelobe clutter suppression capability and Signal to Clutter plus Noise Ratio (SCNR) improvement. Secondly, to tackle the optimization problem, a relaxation is made to decouple spatial and temporal domain of the waveform matrix, beamforming and waveform design can be solved independently. Thirdly, L-BFGS algorithm is used to design the unimodular waveform matrix, beampattern with lower sidelobe and deep null is got. Based on maximization of SCNR, transmitted waveform and receiving filter are designed by iterative algorithm. Finally, the effectiveness of the proposed algorithm is verified by electromagnetic simulation of range-spread target.
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出版歷程
  • 收稿日期:  2016-01-04
  • 修回日期:  2016-05-30
  • 刊出日期:  2016-12-19

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