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.