Study on multitarget tracking algorithm in two direction-finding location systems

Recognition of ghosts is a very important unsolved problem in two direction-finding location systems. This paper studies the problem and proposes a new method to solve it. Firstly, the bearing measurements of two passive sensors are used to estimate the initial range intervals of targets that are divided into a number of subintervals. Then, the bearing measurements are associated to judge which measurements belong to the same target. An extended Kalman filter (KKF) is designed for each subinterval. And initial probability of target lying in each subinterval is also given. The combined state estimate is obtained as weighted sums of the state estimates of each subinterval. This probability is calculated recursively according to Bayes rule in the tracking. If the probability is below a detection threshold this model is abolished. Simulation results show that by using the algorithm discussed in this paper two passive sensors can locate and track multiple targets at the same time.