Paper
26 November 2001 Demonstration of multiple-hypothesis tracking (MHT) practical real-time implementation feasibility
Author Affiliations +
Abstract
Since its initial definition, about 25 years ago, the potential data association performance enhancements associated with Multiple Hypothesis Tracking (MHT) have been widely accepted. However, the actual practical implementation of MHT has been impeded by the perception that its complexity precludes real-time application. The purpose of this paper is to show that modern computational capabilities and newly developed MHT algorithm efficiencies make real-time MHT implementation feasible even for scenarios with large numbers of closely spaced targets. The paper begins by outlining the elements of our MHT algorithm and by defining a typical stressing scenario, with about 100 closely spaced targets, which is used for evaluation of real-time MHT implementation capability. It then presents the processing times required for each of the MHT algorithm elements on a 866Mhz Pentium III computer. Finally, it also presents the memory requirements. Conclusions are that real-time implementation is currently feasible for typical stressing scenarios using the 866Mhz Pentium III computer or other similar modern machines. The extension to larger scenarios with future computer systems is outlined.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel S. Blackman, Robert J. Dempster, and R. W. Reed "Demonstration of multiple-hypothesis tracking (MHT) practical real-time implementation feasibility", Proc. SPIE 4473, Signal and Data Processing of Small Targets 2001, (26 November 2001); https://doi.org/10.1117/12.492756
Lens.org Logo
CITATIONS
Cited by 11 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Computing systems

Radar

Algorithm development

Data processing

Detection and tracking algorithms

Logic

Filtering (signal processing)

Back to Top