Maximum Likelihood Joint Tracking and Association in Strong Clutter. (14th January 2013)

• Record Type: Journal Article
• Authors: Perlovsky, Leonid I.; Deming, Ross W.
• Is Part Of: International journal of advanced robotic systems. Volume 10:Number 1(2013)
• Publication Date: 2013-01-14
• Subjects: Maximum Likelihood -- Joint Association Tracking and Detection -- Combinatorial Complexity -- Tracking -- Association -- Clutter -- Weak Targets -- Strong Clutter; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/52859
• Languages: English
• ISSNs: 1729-8806

Abstract

We have developed a maximum likelihood formulation for a joint detection, tracking and association problem. An efficient non-combinatorial algorithm for this problem is developed in case of strong clutter for radar data. By using an iterative procedure of the dynamic logic process "from vague-to-crisp" explained in the paper, the new tracker overcomes the combinatorial complexity of tracking in highly-cluttered scenarios and results in an orders-of-magnitude improvement in signal-to-clutter ratio.