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Proceedings Paper

Pulse train PDA analysis and deinterleaving filter
Author(s): Benjamin J. Slocumb; Edward W. Kamen
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Paper Abstract

This paper develops the pulse train probabilistic data association filter (PT-PDAF) for use in pulse train analysis and deinterleaving applications. The approach is based on a state-space formulation of the pulse train evolution model. The PDA approach overcomes real-world problems of false and missing pulses which cause the basic Kalman filter to break down. Simulations are developed to show that the PT-PDAF approach is superior to a nearest neighbor filter. An augmented PDA approach which incorporates available pulse parameter measurements such an angle of arrival into the PDA algorithms is shown to further improve the filter performance.

Paper Details

Date Published: 28 July 1997
PDF: 12 pages
Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); doi: 10.1117/12.280808
Show Author Affiliations
Benjamin J. Slocumb, Georgia Tech Research Institute (United States)
Edward W. Kamen, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3068:
Signal Processing, Sensor Fusion, and Target Recognition VI
Ivan Kadar, Editor(s)

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