Position Estimation by Improved Genetic Algorithm for Hyperbolic Location

Lichun Li, Feng Wei College of Information Engineering Information Engineering University P.O.BOX 1001-828 Zhenzhou 450002, China Email: [email protected] Abstract—An effective technique in locating a source based on intersections of hyperbolic curves defined by the time differences of arrival of a signal received at a number of sensors is proposed. By making use of the knowledge of the cell’s ID, the approach uses coverage shrinkable improved genetic algorithm to search the position coordinates. It is an approximation of the maximum-likelihood estimator and is shown to attain the Cramer-Rao lower bound. Comparisons of performance with the fixed coverage genetic algorithm and the Chan’s method are made. The proposed method has higher accuracy than the fixed coverage algorithm and follows closely to the Cramer-Rao bound even at high noise level.