A new method for track initiation in a distributed passive sensor network

A new algorithm is proposed for track initiation in a distributed passive sensor network. The algorithm is formulated using a newly defined fuzzy synthetic closeness function in which the correlations between the set of measurements and targets are reflected. First of all, the algorithm detects targets through searching the globe extreme points of the fuzzy synthetic closeness function using the steepest descent method, then assigns measurements to various targets using threshold test, and finally estimates the initial states of targets using their correlative measurements by Levenberg-Marquart algorithm. The approach does not need any additional information such as the probability of detection, false alarm rate and the clutter density. Simulation results show its effectiveness.