Study on Data Association Methods for Distributed Passive Sensors with Long Baseline

This paper is concerned with the data association problem of distributed long baseline 2-D passivesensors (or jammed 3-D active sensors). Two data association methods, minimum miss distance method and hingeangle method, are discussed when the earth curvature isconsidered. According to the pioneering work, when theearth curvature effect was not considered, the results obtained by using the hinge angle based statistic were essentially the same as those obtained by using the miss distancebased statistic in two sensor case. In long baseline case, theearth curvature must be considered. In this paper, the detailed expressions of the above two methods are derived forlong baseline cases. In order to analyze the performance ofthe two methods, the correct association probability of thetrue targets and the incorrect association probability of theghost targets are defined. The Monte Carlo simulations intwo and three sensor cases are made, respectively. Simulation results show that the minimum miss distance methodis superior to the hinge angle method both in the case ofthree sensors and in the case of two sensors with targetsbeing located near the baseline, and that the performanceof the minimum miss distance method is equivalent to thatof the hinge angle method when the targets are located farfrom the baseline.