Adaptive fusion algorithm for multiple passive sensor tracking

Single sensor tracking algorithms have four disadvantages: (1) bad stability, (2) long settling time, (3) big bias and (4) susceptibility to initial conditions. The corresponding fusion using the information results of each sensor limits the improvements and consumes excessive computation and communication resources. This paper presents a new fusion structure of multiple stations. First, multiple two stations was used to improve the performance, and then it was used to fuse and make pseudo measurements adaptive. Finally, the fusion results were returned to the multiple two stations. The formulas for this new fusion structure were derived. These formulas make the algorithm converge very quickly and not susceptible to initial conditions. Simulation results show the effectiveness of the new algorithm.