Tracking in a high-clutter environment: simulation results characterizing a bi-level MHT algorithm

David S.K. Chan; Daniel D. Harrison; David A. Langan

doi:10.1117/12.157805

22 October 1993 Tracking in a high-clutter environment: simulation results characterizing a bi-level MHT algorithm

David S.K. Chan, Daniel D. Harrison, David A. Langan

Proceedings Volume 1954, Signal and Data Processing of Small Targets 1993; (1993) https://doi.org/10.1117/12.157805
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

As detection processing becomes increasingly advanced, for example, in infrared search and track (IRST) systems, the detection threshold becomes the bottleneck to overall system performance. Significantly reducing this threshold requires the capability to track targets in a high clutter environment. In theory, the multiple hypothesis tracking (MHT) algorithm is a solution to this problem. However, in practice, MHT in its basic form becomes computationally prohibitive for all but low to moderate false alarm densities. In this paper, we evaluate a computationally feasible alternate form, which we call a bi-level MHT algorithm. The basic form of this algorithm has been previously proposed, but results on its performance have been lacking. In addition to describing an implementation of a bi-level MHT algorithm, this paper present Monte Carlo simulation results characterizing the performance of the algorithm, and demonstrates the tradeoff between track acquisition range and false track rate for a simple IRST fly-by scenario.

Citation Download Citation

David S.K. Chan, Daniel D. Harrison, and David A. Langan "Tracking in a high-clutter environment: simulation results characterizing a bi-level MHT algorithm", Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); https://doi.org/10.1117/12.157805

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available