Time-Varying Multi-Target Tracking Method Based on Particle Filter in Radio Tomographic Network

Traditional method based on radio tomographic image (RTI) suffers from latency, resulting in the existence of a lag between the estimated target number and the true one. Moreover, the tracking accuracy of the traditional method should be improved. In this paper, a particle filtering (PF) theory was introduced for time-varying multi-target tracking (MTT) in radio tomographic network, utilizing the particles with variable dimensions to estimate the target number and track the targets to solve the latency problem and improves the tracking accuracy. Some experiments were conducted in a monitored region with the area of 9.5 m×9.5 m to verify the effectiveness of the PF-based method. The experimental results show that the optimal sub-pattern assignment (OSPA) error of traditional method is 0.485 m. In contrast, the OSPA error of proposed method is 0.362 m, which is improved by 25%.