Title :
A new relaxation algorithm and passive sensor data association
Author :
Pattipati, Krishna R. ; Deb, Somnath ; Bar-Shalom, Yaakov ; Washburn, Robert B., Jr.
Author_Institution :
Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA
fDate :
2/1/1992 12:00:00 AM
Abstract :
The static problem of associating measurements at a given time from three angle-only sensors in the presence of clutter, missed detections, and an unknown number of targets is addressed. The measurement-target association problem is formulated as one of maximizing the joint likelihood function of the measurement partition. Mathematically, this formulation leads to a generalization of the 3-D assignment (matching) problem, which is known to be NP hard. The solution to the optimization problem developed is a Lagrangian relaxation technique that successively solves a series of generalized two-dimensional (2-D) assignment problems. The algorithm is illustrated by several application examples
Keywords :
clutter; optimisation; radar theory; relaxation theory; set theory; signal detection; tracking; 3-D assignment; Lagrangian relaxation technique; NP hard; clutter; measurement partition; measurement-target association; missed detections; optimization; passive sensor data association; set theory; signal detection; tracking; Cost function; Current measurement; Lagrangian functions; Noise measurement; Partitioning algorithms; Polynomials; Radar tracking; State estimation; Target tracking; Time measurement;
Journal_Title :
Automatic Control, IEEE Transactions on
