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基于相鄰互相關(guān)函數(shù)-參數(shù)化中心頻率-調(diào)頻率分布-Keystone變換的無源雷達機動目標(biāo)相參積累方法

趙勇勝,  胡德秀,  劉智鑫,  趙擁軍,  趙闖

趙勇勝, 胡德秀, 劉智鑫, 趙擁軍, 趙闖. 基于相鄰互相關(guān)函數(shù)-參數(shù)化中心頻率-調(diào)頻率分布-Keystone變換的無源雷達機動目標(biāo)相參積累方法[J]. 電子與信息學(xué)報, 2019, 41(10): 2358-2365. doi: 10.11999/JEIT180858
引用本文: 趙勇勝, 胡德秀, 劉智鑫, 趙擁軍, 趙闖. 基于相鄰互相關(guān)函數(shù)-參數(shù)化中心頻率-調(diào)頻率分布-Keystone變換的無源雷達機動目標(biāo)相參積累方法[J]. 電子與信息學(xué)報, 2019, 41(10): 2358-2365. doi: 10.11999/JEIT180858
Yongsheng ZHAO, Dexiu HU, Zhixin LIU, Yongjun ZHAO, Chuang ZHAO. Coherent Integration Algorithm Based on Adjacent Cross Correlation Function-Parameterized Centroid Frequency-Chirp Rate Distribution -Keystone Transform for Maneuvering Target in Passive Radar[J]. Journal of Electronics & Information Technology, 2019, 41(10): 2358-2365. doi: 10.11999/JEIT180858
Citation: Yongsheng ZHAO, Dexiu HU, Zhixin LIU, Yongjun ZHAO, Chuang ZHAO. Coherent Integration Algorithm Based on Adjacent Cross Correlation Function-Parameterized Centroid Frequency-Chirp Rate Distribution -Keystone Transform for Maneuvering Target in Passive Radar[J]. Journal of Electronics & Information Technology, 2019, 41(10): 2358-2365. doi: 10.11999/JEIT180858

基于相鄰互相關(guān)函數(shù)-參數(shù)化中心頻率-調(diào)頻率分布-Keystone變換的無源雷達機動目標(biāo)相參積累方法

doi: 10.11999/JEIT180858 cstr: 32379.14.JEIT180858

  • 解放軍戰(zhàn)略支援部隊信息工程大學(xué)數(shù)據(jù)與目標(biāo)工程學(xué)院 鄭州 ??450001

基金項目: 國家自然科學(xué)基金(61703433)
詳細信息
    作者簡介:

    趙勇勝：男，1990年生，博士生，研究方向為無源雷達信號處理

    胡德秀：男，1983年生，講師，研究方向為無源定位、信號分析與處理

    劉智鑫：男，1991年生，博士生，研究方向為輻射源定位、電子偵察等

    趙擁軍：男，1964年生，教授、博士生導(dǎo)師，研究方向為雷達信號處理

    趙闖：男，1978年生，副教授，研究方向為雷達信號處理

    通訊作者:

    胡德秀　paper_hdx@126.com

  • 中圖分類號: TN971

Coherent Integration Algorithm Based on Adjacent Cross Correlation Function-Parameterized Centroid Frequency-Chirp Rate Distribution -Keystone Transform for Maneuvering Target in Passive Radar

  • School of Data and Target Engineering, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China

Funds: The National Natural Science Foundation of China (61703433)
  • 摘要: 延長積累時間可以有效提高無源雷達的目標(biāo)探測能力，但是對于高速機動目標(biāo)，其速度、加速度、第二加速度等因素導(dǎo)致現(xiàn)有的檢測算法在積累過程中發(fā)生距離徙動(RM)和多普勒頻率徙動(DFM)，使得目標(biāo)檢測性能惡化。該文針對無源雷達中變加速運動目標(biāo)的長時間相參積累問題，提出一種基于相鄰互相關(guān)函數(shù)(ACCF)-參數(shù)化中心頻率-調(diào)頻率分布(PCFCRD)-Keystone變換(KT)的相參積累算法(ACCF-PCFCRD-KT)。首先給出無源雷達中變加速運動目標(biāo)的回波模型，分析了目標(biāo)速度、加速度和第二加速度對相參積累的影響。針對目標(biāo)第二加速度引起的多普勒頻率彎曲，采用ACCF降低了距離和多普勒頻率徙動的階數(shù)，而后利用PCFCRD估計出目標(biāo)加速度和第二加速度參數(shù)，在補償了目標(biāo)加速度和第二加速度引起的2次和3次徙動后，利用KT校正目標(biāo)速度引起的線性徙動，并實現(xiàn)目標(biāo)回波的積累。仿真結(jié)果表明，該算法可有效補償無源雷達中目標(biāo)運動導(dǎo)致的RM和DFM，對變加速機動目標(biāo)的積累效果顯著優(yōu)于現(xiàn)有算法。
    Abstract: Increasing the integration time can effectively improve the detection performance of passive radar. However, for maneuvering targets, the complex motions, such as high velocity, acceleration and jerk, cause existing detection methods to suffer the Range Migration (RM) and Doppler Frequency Migration (DFM) during the integration time, which deteriorates the detection performance. This paper addresses the long time coherent integration for a maneuvering target with high-order motion (e.g., jerk motion) in passive radar systems. A method based on Adjacent Cross Correlation Function (ACCF), Parameterized Centroid Frequency-Chirp Rate Distribution (PCFCRD) and Keystone Transform (KT)(ACCF-PCFCRD-KT), is proposed. Firstly, the signal model for the maneuvering targets is given, and the influence of the target velocity, acceleration and jerk on the coherent integration is analyzed. For the Doppler curvature induced by the jerk motion, the ACCF is firstly applied to reducing the order of RM and DFM. Then the PCFCRD operation is employed to estimate the acceleration and jerk parameters. After compensating the RM and DFM caused by the acceleration and jerk, the RM arising from the velocity is corrected via the KT operation and the target echo energy is coherently integrated. Simulation results demonstrate that the proposed method can effectively compensate the RM and DFM caused by the target motion parameters in passive radar, and for a maneuvering target with jerk motion, the proposed method achieves better integration performance over the existing methods.
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  • 圖  1  雙基地?zé)o源雷達目標(biāo)運動示意圖

    圖  2  本文算法對回波積累效果

    圖  3  不同算法回波積累效果比較

    圖  4  不同算法的檢測性能曲線(${P_{\rm f}} = {10^{ - 4}}$)

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出版歷程
  • 收稿日期:  2018-09-03
  • 修回日期:  2019-08-01
  • 網(wǎng)絡(luò)出版日期:  2019-08-21
  • 刊出日期:  2019-10-01

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