Sequential track monitoring with multiple 2-D Passive sensors

Track monitoring is a fast method of determining incorrect return-to-track and track-to-track assignments. An analytical method to evaluate the effectiveness of track monitoring was presented by reference [1]. In order to reduce the probability of initiating or accepting the ghost track, two sequential track monitoring algorithms, which use the inclination angles to form test statistics, are proposed in this paper. Two decision rules are given and the corresponding thresholds are derived. The paper also gives the estimation methods of the noncentral parameter of noncentral chi-square distribution when the true value of it is unknown. the algorithms can adaptively estimate the decision thresholds and can make sequential track monitoring decision on line. Simulation is also made and the results show that the proposed algorithms are effective and feasible.