An adaptive segmentation and template matching based on SSA for interference suppression in millimeter wave radar

Abstract

The mutual interference between multiple-input multiple-output (MIMO) millimeter wave (mmWave) radars reduces the signal-to-noise ratio (SNR) of the target, which in turn affects the angle estimation of the target. The singular spectrum analysis (SSA) can be used to suppress the interference by signal reconstruction. However, when there is interference in the intermediate frequency (IF) signal, it is hard to select the principal components (PCs) to reconstruct the IF signal. Therefore, an adaptive segmentation and template matching based on SSA (ASTM-SSA) is proposed. In the adaptive segmentation, the IF signal is divided into interference and interference-free segments based on the location of the interference. In the template matching, the desired PCs of the interference-free segment are considered as the templates to match with PCs of the interference segment, and the matched PCs are used to reconstruct the IF signal. After all the interference are suppressed, the classical multiple signal classification (MUSIC) is performed to estimate the angle of the target. The simulation and field experiments are conducted to verify the effectiveness of the ASTM-SSA, and the results indicate that the ASTM-SSA can effectively suppress interference and accurately estimate the angle of the target.