Pedestrian Target Tracking Method in Low SNR Ratio Scenarios

Millimeter-wave radar is widely used in intelligent transportation and autonomous driving. However, due to the lack of coordination among radar systems, it is susceptible to interference from signals emitted by other radar systems, leading to issues such as increased background noise. To address this problem, this paper proposes a pedestrian target tracking method for low signal-to-noise ratio (SNR) scenarios. By leveraging the particle filtering method and simulating a large number of particles to approximate probability distributions, this method effectively resolves target tracking issues caused by increased background noise. Experimental results demonstrate that the proposed algorithm exhibits excellent tracking performance in low SNR radar scenarios.