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超宽带穿墙雷达高效的TV-MAP稀疏成像方法
引用本文:景素雅,晋良念,刘庆华.超宽带穿墙雷达高效的TV-MAP稀疏成像方法[J].雷达科学与技术,2020,18(5):466-472.
作者姓名:景素雅  晋良念  刘庆华
作者单位:桂林电子科技大学信息与通信学院,广西桂林 541004;广西无线宽带通信与信号处理重点实验室,广西桂林 541004
基金项目:国家自然科学基金(No.61861011,61461012); 广西自然科学基金(No.2017GXNSFAA198050); 广西无线宽带通信与信号处理重点实验室2016主任基金项目(No.GXKL06160106)
摘    要:现有的穿墙雷达稀疏成像方法中构建的字典矩阵占据存储空间大,而且计算复杂度高,成像时间长。为此,本文针对全变分(TV)约束的最大后验(MAP, TV-MAP)稀疏成像方法,利用超宽带窄脉冲波形的特点和冲激函数具有的抽样特性,将优化最小化(MM)框架下的交替迭代更新公式中包含字典矩阵的相关运算用线性卷积和哈希表代替,避免了字典矩阵的构造、存储与计算;同时,通过对发射序列进行变换,使所提方法可以适用于任何超宽带发射波形,而不限于对称的发射波。仿真和实验结果表明,该方法不仅减少了所需内存,降低了时间复杂度,而且有效地抑制了杂波。

关 键 词:全变分法  最大后验  线性卷积  哈希表

Efficient TV-MAP Sparse Imaging Method for Ultra-Wideband Through-the-Wall Radar
JING Suy,JIN Liangnian,LIU Qinghua.Efficient TV-MAP Sparse Imaging Method for Ultra-Wideband Through-the-Wall Radar[J].Radar Science and Technology,2020,18(5):466-472.
Authors:JING Suy  JIN Liangnian  LIU Qinghua
Affiliation:1. School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China;2. Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, Guilin 541004, China
Abstract:The dictionary matrix constructed in the existing through-the-wall radar sparse imaging methods needs a large storage space. Moreover, these methods have high computational complexity and long imaging time. By means of the characteristics of ultra-wideband narrow pulse waveform and the sampling characteristics of impulse function, this paper uses linear convolution and Hash table to replace the related operations including the dictionary matrix in the alternative and iterative updating formula of the maximum a posteriori (MAP) sparse imaging method with total variation (TV) constraint under the framework of majorize-minimize (MM). In this way, the construction, storage and calculation of dictionary matrix are avoided. At the same time, by transforming the transmission sequence, this method can be applied to any ultra-wideband transmission waveform, not limited to symmetrical one. The simulation and experimental results show that the proposed method not only reduces the required memory and time complexity, but also effectively suppresses the clutter.
Keywords:total variation method  maximum a posteriori  linear convolution  Hash table
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