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 probabilistic data association (DPDA) algorithm is proposed. The new algorithm 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 realtime use when there are more than three correlated targets. The algorithm 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.