Wireless Location Algorithm

Wireless positioning, performed either in network or in mobile station, is to determine the geographic location of mobile station through the estimated measurements with the help of location algorithms and the communications resource. Since the E-911 location regulation submitted by the FCC in 1996, the wireless positioning technology has been promoted further as its inexhaustible commercial potential.Nowadays, more and more scholars devote themselves to wireless positioning filed, and large numbers of research results and patents have appeared in resent years.Two main modules are required in an entire location process: 1) estimation of the location parameters and 2) operation of the location algorithms. Firstly, the related parameters, such as the time or angle information, are distilled from the received signals with the help of the parameter estimation algorithms. And then, the parameters are inputted to the location module to yield the location estimation. The primary difficulties lie in the resistance against the estimating errors caused by the severe wireless channel, and the solution to the nonlinear equations which exhibit the geometric relation between the mobile station and the participant base stations.Some systematic research work on the pirotal technology of wireless position has been done after referring to many classic or new naterials. Some positioning methods are improved for the key-difficulty. In this paper, some wireless positioning algorithms are proposed, and some comparisons have done between the classic Talor series algorithem and the hybrid/only motheds based on the Kalman filter. The simulation result shows that the methods based on he Kalman filter perform better than Talor series, and hybrid method has higher precision than only method.To efficiently mitigate the NLOS error, two location algorithms are proposed through the modification on the standard Kalman iterative process. Mobile Tracking Using Hybrid Measurements in NLOS Environments introduce data fusion and hybrid positioning to iterative process, as an one-step method to mitigate NLOS error; Tracking Based on Kalman Filtering for Measurements Restructuring and Mobile Location as a two-step method, use the KF to estimate both the measurements and NLOS error, and restructure the real measurements. Through the simulation and comparison with other methods, the two algorithms suit for the NLOS environment and have higher precision. Further more, the development of positioning method in wireless sensor network is presented briefly, which introduced method to a new direction as a good example.