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基于迭代線性約束最小方差的穩(wěn)健自適應(yīng)脈沖壓縮方法

李秀友 董云龍 黃勇 關(guān)鍵

李秀友, 董云龍, 黃勇, 關(guān)鍵. 基于迭代線性約束最小方差的穩(wěn)健自適應(yīng)脈沖壓縮方法[J]. 電子與信息學(xué)報(bào), 2015, 37(10): 2300-2306. doi: 10.11999/JEIT141631
引用本文: 李秀友, 董云龍, 黃勇, 關(guān)鍵. 基于迭代線性約束最小方差的穩(wěn)健自適應(yīng)脈沖壓縮方法[J]. 電子與信息學(xué)報(bào), 2015, 37(10): 2300-2306. doi: 10.11999/JEIT141631
Li Xiu-you, Dong Yun-long, Huang Yong, Guan Jian. Robust Adaptive Pulse Compression Algorithm Based on Reiterative Linearly Constrained Minimum Variance[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2300-2306. doi: 10.11999/JEIT141631
Citation: Li Xiu-you, Dong Yun-long, Huang Yong, Guan Jian. Robust Adaptive Pulse Compression Algorithm Based on Reiterative Linearly Constrained Minimum Variance[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2300-2306. doi: 10.11999/JEIT141631

基于迭代線性約束最小方差的穩(wěn)健自適應(yīng)脈沖壓縮方法

doi: 10.11999/JEIT141631
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61002045, 61179017, 61102167)和山東省自然科學(xué)基金(2015ZRA06052)

Robust Adaptive Pulse Compression Algorithm Based on Reiterative Linearly Constrained Minimum Variance

Funds: 

The National Natural Science Foundation of China (61002045, 61179017, 61102167)

  • 摘要: 針對(duì)常規(guī)自適應(yīng)脈沖壓縮方法在目標(biāo)散射點(diǎn)與采樣中心失配時(shí)旁瓣抑制性能下降的問(wèn)題,該文提出一種基于迭代線性約束最小方差(RLCMV)的自適應(yīng)脈沖壓縮方法。該方法首先將自適應(yīng)波束形成器算法引入到自適應(yīng)脈沖壓縮濾波器設(shè)計(jì)中。其次對(duì)目標(biāo)及干擾單元進(jìn)行線性約束,并用對(duì)角加載技術(shù)避免矩陣出現(xiàn)病態(tài)。最后構(gòu)造了迭代運(yùn)算方法,依次抑制不同大小目標(biāo)的距離旁瓣。仿真結(jié)果表明,該算法可以有效抑制散射點(diǎn)隨機(jī)分布目標(biāo)的距離旁瓣,對(duì)散射點(diǎn)與采樣中心失配情況具有較好的穩(wěn)健性,在多目標(biāo)及距離擴(kuò)展目標(biāo)場(chǎng)景中達(dá)到較好的旁瓣抑制性能,并在一定程度上提高了多普勒容性。
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出版歷程
  • 收稿日期:  2014-12-20
  • 修回日期:  2015-06-01
  • 刊出日期:  2015-10-19

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