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Proceedings Paper

Comparative analysis of multiple-lag out-of-sequence measurement filtering algorithms
Author(s): Mahendra Mallick; Keshu Zhang; X. Rong Li
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Paper Abstract

Out-of-sequence measurements (OOSMs) frequently arise in a multi-platform central tracking system due to delays in communication networks and varying pre-processing times at the sensor platforms. During the last few years, multiple-lag OOSM filtering algorithms have received a great deal of attention. However, a comparative analysis of these algorithms for multiple OOSMs is lacking. This paper analyzes a number of multiple-lag OOSM filtering algorithms in terms of optimality, accuracy, statistical consistency, and computational speed. These factors are important for realistic multi-target multi-sensor tracking systems. We examine the performance of these algorithms using a number of examples with Monte Carlo simulations. We present numerical results using simulated data, which includes two-dimensional position and velocity measurements.

Paper Details

Date Published: 5 January 2004
PDF: 13 pages
Proc. SPIE 5204, Signal and Data Processing of Small Targets 2003, (5 January 2004); doi: 10.1117/12.506789
Show Author Affiliations
Mahendra Mallick, Lockheed Martin Orincon (United States)
Keshu Zhang, Univ. of New Orleans (United States)
X. Rong Li, Univ. of New Orleans (United States)


Published in SPIE Proceedings Vol. 5204:
Signal and Data Processing of Small Targets 2003
Oliver E. Drummond, Editor(s)

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