Target Tracking with Two Passive Infrared Sensors Augmented with Irradiance Ratio

Abstract

In target tracking using the passive infrared sensors, the principle of triangulation distance measurement is normally used as the basic method. However, when the target directions are nearly collinear relative to the baseline, this method merely based on EKF and angle measurements produces poor results. To solve this problem, we propose a target tracking solution based on dual infrared sensors in the cluttered environment. This method is a joint estimation algorithm of target motion state and atmospheric parameter such as the extinction coefficient. The method combines the probability data association algorithm with the augmented extended Kalman filter algorithm, into which we introduce the rate of infrared energy absorbed by the sensors at the ends of the baseline as additional measurement vector. Simulation results show that the proposed method performs better than the standard extended Kalman filter method, even in the case that the targets position is near the baseline in the cluttered environment.