A Data Association Algorithm of Passive Sensor Based on Target Assumption

Aiming at the problem of the static data association of multi-targets with only angle information, an improved Lagrangian relaxation that can be rapidly converged on the condition that missed detection and false alarm are allowed is presented in this paper. On the assumption that some targets are real ones, the cost matrix is modified, which contributes to the fast convergence of Lagrangian relaxation. Simulation results show that this method improves the speed and accuracy of data association, especially in multiple targets and/or heavy noise condition.