基于图信号处理的频控阵雷达目标定位方法

针对现代雷达应用对目标高精度测角和测距的需求，该文将图信号处理(GSP)应用于频控阵(FDA)雷达目标定位中，提出一种基于图信号处理的频控阵雷达目标定位新方法。首先，基于频控阵雷达几何模型及回波数据间的信号关联性构建回波数据的图信号模型，进而利用图傅里叶变换对上述图信号作图谱分解，构建2维谱峰搜索优化函数，最终有效获得目标的方位角-距离联合估计。仿真实验结果表明，该算法能够正确估计出目标的方位角和距离信息；在相同仿真条件下，算法的估计精度优于同类算法且提升了对弱目标的定位性能。

A Novel Target Localization Method for Frequency Diverse Array Based on Graph Signal Processing

In most target localization applications, achieving high spatial resolution on angle and range is requested. Addressing this demand, a novel Graph Signal Processing (GSP) based target localization method for monostatic Frequency Diverse Array (FDA) is proposed in this paper. Firstly, a directed graph model applicable to the FDA is established based on the array geometry and the signal correlations among array elements, in which echoes received in the array are mapped to a graph signal. By leveraging the concept of the graph Fourier transform, the obtained graph signal is decomposed into a set of spectrums, and then the joint angle and range estimation can be solved successfully using a well-designed two-dimensional spectral peak search. The simulation results illustrate the validity and effectiveness of the proposed method, and it is shown that the proposed method outperforms the existing methods in estimation accuracy and is capable to achieve performance improvement for the weak target in a low Signal-to-Noise Ratio (SNR) environment.