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Proceedings Paper

Fusion of ultrasonic and infrared signatures for personnel detection by a mobile robot
Author(s): Matthew S. Carroll; Min Meng; William K. Cadwallender
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Paper Abstract

Passive Infrared sensors used for intrusion detection, especially those used on mobile robots, are vulnerable to false alarms caused by clutter objects such as radiators, steam pipes, windows, etc., as well as deliberately caused false alarms caused by decoy objects. To overcome these sources of false alarms, we are now combining thermal and ultrasonic signals, the results being a more robust system for detecting personnel. Our paper will discuss the fusion strategies used for combining sensor information. Our first strategy uses a statistical classifier using features such as the sonar cross-section, the received thermal energy, and ultrasonic range. Our second strategy uses s 3-layered neural classifier trained by backpropagation. The probability of correct classification and the false alarm rate for both strategies will be presented in the paper.

Paper Details

Date Published: 30 April 1992
PDF: 11 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57958
Show Author Affiliations
Matthew S. Carroll, Purdue Univ. (United States)
Min Meng, Purdue Univ. (United States)
William K. Cadwallender, MDARS Lab. (United States)

Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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