Improved Tracking of Airborne Targets Hidden in the Blind Doppler using Particle Filter

In airborne tracking, the blind Doppler makes the target undetectable, resulting in great tracking difficulties. In this paper, we sum up two types of the blind Doppler cases under constant velocity constraint: targets´ intentional tangential flying to radar and unintentional flying also leading to the blind Doppler. We propose an improved particle filter by introducing two different levels of noise to the movement model and one of them is a random acceleration noise. This acceleration selection added to the sampling step makes the constant velocity model efficient in dealing with maneuvering motions (i.e. escape turns). We compare the proposed particle filter with the extended Kalman filter and previous particle filter solution. Simulation results show that the proposed method outperforms previous ones in tracking accuracy and continuity.