Decoupling probabilistic data association algorithm for multiplatform multisensor tracking

Abstract

In a multiplatform multisensor system, it is crucial to develop a practical algorithm under computation and communication constraints. A practical data association algorithm is presented. A decoupling proba- bilistic data association (DPDA) algorithm is proposed. The new algo- rithm decouples the joint probabilistic data association (JPDA) algorithm into separate PDA algorithms in a simple way because the complete decoupling PDA algorithm is too complex and loses its meaning for real- time use when there are more than three correlated targets. The algo- rithm is then extended to multiplatform multisensor tracking, where it is combined with a distributed algorithm. To evaluate a data association algorithm, the correct average probability (CAP) is used. The CAP is defined as the average probability of a true target measurement. Monte Carlo simulations demonstrate the effectiveness of the algorithm. © 1998 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(98)00602-3) Subject terms: sensor fusion; data association; target tracking; probabilistic data association; decoupling probabilistic data association algorithm; multiplatform multisensor system.