A projection-based joint probabilistic data association algorithm

A novel projection-based joint probabilistic data association (PJPDA) algorithm is presented. The JPDA problem is formulated as a constrained optimization problem and solved using projection onto convex sets (POCS) methods. The PJPDA algorithm is extremely simple to implement, has no strenuous memory requirements and completely avoids the generation of feasible event matrices. The algorithm complexity is discussed and simulation results presented