The Non-linear Tracking of IMM- PHD Filter for Rader-Infrared Sensor Data Fusion
Anqing Zhang, Wanshun Zhang, QI Haiming · Journal of Physics Conference Series · 2020
Abstract In order to improve the accuracy of multi-target tracking, a feasible dada fusion system is proposed for radar and infrared sensor used together, to overcome the defects both small detection range and no distance measurement for infrared sensor, and to avoid the problem of large error in measurement information of single sensor. Rader and infrared dada fusion can achieve complementary information. An optimal weighted fusion method for measurement of radar and infrared sensors is derived, and an interactive multi-model PHD nonlinear filtering algorithm is used to improve the accuracy of target tracking. The computer simulation results show that the integrated system and multi-sensor measurement fusion method can improve the accuracy of target state estimation. It is of great practical significance to solve the problem of target tracking estimation of heterogeneous multi-sensor.