Author :
Ruan, Yanhua ; Willett, Peter
Author_Institution :
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
Abstract :
The PMHT (probabilistic multihypothesis tracker) uses "soft" a posteriori probability associations between measurements and targets. Its implementation is a straightforward iterative application of a Kalman smoother operating on "synthetic" (i.e., modified) measurements, and of recalculation of these synthetic measurements based on the current track estimate. In this correspondence, we first discuss the basic PMHT and some of the older PMHT variants that have been used to enhance convergence. We then introduce the new turbo PMHT, which is informed by the recent success of turbo decoding in the digital communication context. This new PMHT has performance substantially improved versus any of the previous versions.
Keywords :
Kalman filters; iterative methods; probability; smoothing methods; target tracking; turbo codes; Kalman smoother operation; iterative application; probabilistic multihypothesis tracker; soft a posteriori probability association; synthetic measurement; track estimate recalculation; turbo PMHT; turbo decoding; Context; Convergence; Current measurement; Decoding; Digital communication; Kalman filters; Maximum likelihood estimation; Target tracking; Testing; Time measurement;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2004.1386891