基于切比雪夫多项式的双基地前视SAR成像算法
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(1. 海军航空大学岸防兵学院,山东烟台264001;2. 海军工程大学兵器工程学院,武汉430033)

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E-mail: chenqiyt@163.com.

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TN959.3

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国家重点实验室开放课题基金项目(CEMEE2016K0201B).


Imaging algorithm for bistatic forward-looking SAR based on Chebyshev polynomials
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(1. College of Coast Defence Arm,Naval Aviation University,Yantai 264001,China;2. College of Weapons Engineering,Naval University of Engineering,Wuhan 430033,China)

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    摘要:

    双基地前视合成孔径雷达(SAR)的特殊构型使其距离历程具有双根号和大斜视的特点,给回波信号的成像处理带来困难,也对成像算法的精度提出更高要求,为此提出一种基于切比雪夫多项式的双基地前视SAR RD成像算法.首先,建立双基地前视SAR的几何模型与回波信号模型,指出收发分离构型对二维频谱公式推导过程中驻定相位点求解的影响;然后,引入切比雪夫多项式展开代替传统成像算法中的泰勒级数展开,在此基础上进行双基地前视SAR斜距等效模型和二维频谱模型的推导;最后,通过分析确定双基地前视SAR RD成像算法的相位匹配函数,给出成像算法的完整流程.仿真结果表明,所提出算法可极大减小双基地前视SAR的斜距等效误差与频谱展开误差,有效提高成像算法的聚焦深度和成像质量.

    Abstract:

    The special configuration of the bistatic forward-looking synthetic aperture radar(SAR) brings double square root and high squint angle to its range history, which makes it difficult to focus the echo signal, and puts forward higher requirements to the accuracy of the imaging algorithm. Therefore, a bistatic forward-looking SAR RD imaging method based on Chebyshev polynomials is proposed. Firstly, the geometry model and echo model are built, and the influence caused by separated configuration on determining stationary phase point during two-dimensional spectrum model deriving is indicated. Then, by the introduction of Chebyshev polynomials expansion replacing Taylor series expansion in the traditional imaging algorithm, the equivalent range model and the two-dimensional spectrum model of bistatic forward-looking SAR are derived. Finally, the phase matching functions of the bistatic forward-looking SAR RD imaging algorithm are determined by analysis, and the complete program of the imaging algorithm is given. The simulation results show that the proposed algorithm can significantly decrease the equivalent range error and spectrum expansion error of the bistatic forward-looking SAR, and improve the focus depth and imaging quality effectively

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陈麒,李相平,祝明波,等.基于切比雪夫多项式的双基地前视SAR成像算法[J].控制与决策,2019,34(6):1241-1246

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  • 在线发布日期: 2019-05-09
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