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Proceedings Paper

Multi-environment NLF tracking assessment testbed (MENTAT): an update
Author(s): Ronald Mahler; Joseph Spinks; Michael Ekhaus; Lingji Chen
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Paper Abstract

In applications in which even the best EKFs and MHTs may perform poorly, the single-target and multi-target Bayes nonlinear filters become potentially important. In recent years, new implementation techniques such as sequential Monte Carlo (a.k.a. particle-system) have emerged that, when hosted on ever more inexpensive, smaller, and powerful computers, make these filters potentially computationally tractable for real-time applications. A methodology for preliminary test and evaluation (PT&E) of the relative strengths and weaknesses of these algorithms is becoming increasingly necessary. The purpose of PT&E is to (1) assess the broad strengths and weaknesses of various algorithms or algorithm types; (2) justify further algorithm development; and (3) provide guidance as to which algorithms are potentially useful for which applications. At last year's conference we described our plans for the development of a PT&E tool, MENTAT. In this paper we report on current progress. Our implementation is MATLAB-based, and harnesses the GUI-building capabilities of the well-known MATLAB package, SIMULINK.

Paper Details

Date Published: 17 May 2006
PDF: 12 pages
Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350Q (17 May 2006); doi: 10.1117/12.667090
Show Author Affiliations
Ronald Mahler, Lockheed Martin MS2 Tactical Systems (United States)
Joseph Spinks, Lockheed Martin MS2 Tactial Systems (United States)
Michael Ekhaus, Gibralter Analytics (United States)
Lingji Chen, Scientific Systems Co., Inc. (United States)


Published in SPIE Proceedings Vol. 6235:
Signal Processing, Sensor Fusion, and Target Recognition XV
Ivan Kadar, Editor(s)

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