基于模态分解的地基雷达慢速弱目标检测方法

When using ground-based radar to detect ground moving targets in complex terrain scenes, it is difficult to distinguish slow weak targets from ground clutter in spectrum, and the Performance of traditional target detection methods is limited. To solve this problem, a slow weak target detection method for ground-based radar based on mode decomposition is proposed. Firstly, a lower threshold is set for cell average-constant false alarm rate (CA-CFAR) detection to preliminarily screen targets. Subsequently, complex empirical mode decomposition (CEMD) is applied to slow-time signals to separate moving targets from ground clutter. Finally, targets are detected according to the asymmetry difference in Doppler spectra of ground clutter and moving targets. This detection method is compared with the Performance of CA-CFAR and orthogonal projection-singular value decomposition-constant false alarm rate (OP-SVD-CFAR), and validated using Simulation data and measured data from two different target sets. Results demonstrate that the proposed method enhances the signal-to-clutter noise ratio of targets. Under the same detection probability, its false alarm rate is significantly lower than that of CA-CFAR. Moreover* under the same and higher detection probability, the proposed method also exhibits a lower false alarm rate compared to OP-SVD-CFAR, thereby affirming its efficacy.