Bias phenomenon and compensation for PDA/JPDA algorithms

Probabilistic Data Association (PDA) and Joint PDA (JPDA) algorithms are approaches for target tracking which have received considerable attention. It has been observed for some years that they both yield biased tracks in a multitarget environment. However, most work assumes no false alarms and the rejection phenomenon of the JPDA algorithm has not been reported. In this paper, the general procedure of multitarget tracking and the PDA/JPDA algorithms are first described. Their bias phenomenon is simulated and investigated. It is observed that

(1) the JPDA algorithm has less bias than the PDA algorithm in a clean environment. Both of them yield coalescence

(2) the JPDA algorithm has coalescence and rejection bias phenomenon while the PDA algorithm has only coalescence phenomenon in a clutter environment.

Bias compensated algorithms are then presented using the polynomial regression method. Simulations are carried out to select the order of polynomial regression. Monte Carlo simulations also demonstrate the effectiveness of the compensated PDA/JPDA algorithms.