The Research of Multiple Signal Hybrid Filter Based on Detection Probability Model

In wireless location technology, the environment restriction cause the coverage area of single signal is limited and incontinuous. So it is hard to get better position precision and larger coverage area. In the same time, the traditional non-linear filter has too high computation burden, influenced the real-time performance of location very bad. Due to the mutual limits among precision, coverage and real-time, how to find a way that get a good position precision with no much computation burden is a key problem. The paper considers utilizing detection probability model to fuse multiple measurement signals in target zone fully and effectively. Then a line and nonlinear hybrid filter under Bayesian rule is established and can estimate target location information. It is extremely interesting to improve the robust of location and tracking. Simulation results show the various signal fusion algorithm based on hybrid filter can not only guarantee the positioning accuracy very well, but also save more computation time. At all the performance of positioning and track is improved very well.