<title>IMAM algorithm for tracking maneuvering targets in clutter</title>

Abstract

Target tracking in clutter is difficult because there can be several contact-to-track associations for a given track update. The nearest neighbor approach is traditionally used but probabilistic methods, such as probabilistic data association (PDA), have since proved more capable. Tracks are also lost during maneuvers and the interacting multiple model (IMM) algorithm has been demonstrated to be effective at tracking maneuvering targets by responding to different target modes. By combining the IMM and PDA, the resulting algorithm responds to target maneuvers and is effective in clutter. The interacting multiple bias model (IMBM) algorithm is also an effective technique when tracking maneuvering targets but considers the target acceleration a system bias. The bias is estimated in an IMM algorithm framework and then used to compensate a constant velocity filter estimate. The integrated PDA filter will be incorporated into the IMBM algorithm and applied to tracking maneuvering targets in clutter. A performance comparison of IMM and IMBM techniques for tracking maneuvering targets in clutter will also be presented.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.