Extracting UWB One-Dimensional Scattering Center Based on Improved Matrix Pencil
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摘要: 针对微动参数的高精度快速估计问题，该文提出一种基于几何绕射(GTD)模型和改进矩阵束的超宽带(UWB)散射中心提取算法，可实现散射中心径向距离、类型参数及散射强度的同时估计。该方法将超宽带条件下的目标GTD散射模型转化为状态空间方程，利用奇异值分解将汉克尔矩阵中的噪声分量去除，对降秩的汉克尔矩阵做广义特征值分解，利用单个脉冲内最强的若干散射点构造回波估计，进而获得径向距离的估计；在准确估计距离参数的条件下，对模型参数解耦，使得类型参数与其他参数分离，通过最小二乘算法和搜索算法获得类型参数的估计；最后基于最小二乘法估计出散射中心的散射强度。仿真结果表明，改进的矩阵束方法在低信噪比(SNR)下具有好的鲁棒性，可快速且高精度地提取目标微动距离、类型参数和散射强度等信息。Abstract: In order to estimate the micro-motion parameters accurately and fleetly, an Ultra Wide Band (UWB) scattering center extraction algorithm based on Geometrical Theory of Diffraction (GTD) model and improved matrix pencil is proposed. The radial distance of the scattering center, the type parameters and the scattering intensity can be estimated simultaneously. The target GTD scattering model under UWB condition is transformed into a state space equation in this method, and the singular value decomposition is used to remove the noise component from the Hankel matrix. The generalized eigenvalue decomposition of the reduced Hankel matrix is performed, and the echo estimation is constructed by using the strongest scattering points in a single pulse, and then the radial distance estimation is obtained. Under the condition that the distance parameters are accurately estimated, the model parameters are decoupled so that the type parameters are separated from other parameters, and the type parameters are estimated by the least square algorithm and the search algorithm. Finally, the scattering intensity of the scattering center is estimated based on the least square method. The simulation results show that the improved matrix beam method has good robustness under low SNR, and can extract the target micro-motion distance, type parameters and scattering intensity with high precision.
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表 1 类型参数代表的几何特征
参数值 散射中心的几何特征 –4/2 边缘上曲率不连续点 –2/2 锥尖 –1/2 弯曲边缘衍射 0/2 双曲面，平直的边缘 +1/2 单曲面(柱面) +2/2 角反射器，平面 
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表 2 散射中心参数估计的仿真参数设置
参数名称 数值 频率间隔$\Delta f$ 10 MHz 频率点数 201 中心频率${f_{\text{c}}}$ 10 GHz 信号采样间隔$\Delta t$ 0.001 s 时间窗口 19 总体仿真时间 1 s
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表 3 加噪声情况下各算法的类型参数估计准确率及算法运行时间
算法名称 类型参数估计准确率(%) 算法运行时间(s) 状态空间平衡法 28.60 32.1984 矩阵束法 46.20 34.3592 改进的矩阵束法 46.14 17.1721
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