Title :
An interacting multi-pattern probabilistic data association (IMP-PDA) algorithm for target tracking
Author :
Hong, Lang ; Cui, Ning-Zhou
Author_Institution :
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
fDate :
8/1/2001 12:00:00 AM
Abstract :
A theoretical development of a novel approach for target tracking based on multiple patterns extracted from measurement sequences is presented in this paper. The introduction of patterns leads to a new paradigm for developing high performance algorithms. An interacting multi-pattern probabilistic data association (IMP-PDA) algorithm is developed, taking the advantage of clever formulation of the interacting multiple model approach. The IMP-PDA algorithm employs distance, directional and maneuver information for data association, which enhances significantly the capability of discriminating correct measurements from false measurements
Keywords :
data handling; kinematics; pattern recognition; probability; target tracking; data association; interacting multiple-patterns; kinematics; multiple scan model; pattern extraction; probabilistic data association; target tracking; Approximation methods; Computational complexity; Data mining; Filters; Kinematics; Logic; State estimation; Target recognition; Target tracking; Uncertainty;
Journal_Title :
Automatic Control, IEEE Transactions on