Passive location algorithm of two sensors based on multihypothesis extended Kalman filter

Multitarget tracking with bearings only measurements of two passive sensors is a very important problem, which has not been solved. To counter this problem a method is proposed in this paper, This method firstly used the bearing measurements of two passive sensors to estimate the initial range interval of targets, which are divided into several subintervals. At each subinterval an extended Kalman filter and a multihypothesis method are used to estimate the state of targets. At the same time the bearing measurements are associated. Combined state estimate is obtained as weighted sums of the state estimate of each subinterval. Simulation results show that through using the algorithm discussed in this paper two passive sensors can locate and track multiple targets at the same time.