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Proceedings Paper

A system approach to real world multi-sensor data fusion
Author(s): Fred Daum
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Paper Abstract

Theoretically, fusion of measurements is optimal, and fusion of tracks is suboptimal. However, in the real world it frequently turns out that track fusion is superior to measurement fusion. The purpose of this paper is to explain the main reasons for this and to describe a measurement fusion algorithm that is robust in the real world. The two major reasons that measurement fusion fails to perform as well as expected in the real world are: (1) limited sensor resolution, and (2) residual sensor bias errors. Designing robust multi-sensor data fusion algorithms that work well in the real world requires understanding the physics of both sensor resolution and sensor bias errors.

Paper Details

Date Published: 17 May 2006
PDF: 9 pages
Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350S (17 May 2006); doi: 10.1117/12.665856
Show Author Affiliations
Fred Daum, Raytheon Co. (United States)

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

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