A PELT-KCN Algorithm for FMCW Radar Interference Suppression Based on Signal Reconstruction

摘要

In frequency-modulated continuous-wave (FMCW) radar interference suppression based on signal reconstruction, the pruned exact linear time (PELT) algorithm is used to detect the time positions of the interference. Due to the uncertain penalty factor of the PELT algorithm, the exactness of the position detection is reduced; thus, the suppression performance is degraded. We propose a PELT algorithm with a known change number (PELT-KCN), where a known change number is used to calculate the optimal penalty factor such that the high accuracy of the algorithm can be guaranteed. After interference recognition, the beat signal is separated into two parts: the undamaged signal and the damaged signal. The former is utilized to restore the latter through an autoregressive (AR) model. In simulations and field experiments, we applied our proposed PELT-KCN algorithm to the interference suppression method and verified its performance. Our method can accurately detect the time positions of interference and effectively improve the signal-to-noise ratio (SNR) of the detected targets.