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Proceedings Paper

Sensor fusion for intrusion detection and assessment
Author(s): Cynthia L. Nelson; Deborah S. Fitzgerald
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Paper Abstract

Successful intrusion detection and assessment within a secured area typically requires the presentation of a large amount of information to a central alarm station operator. Typically, alarm information from several separate sensors is forwarded to the operator to be manually interpreted. However, the information is not always consistent with the actual situation and may not be sufficiently complete to make an accurate analysis. Alarm processing and fusion techniques can be applied to the sensor data to result in complete and manageable information that is presented to the operator for easier interpretation. This paper discusses the sensor fusion approach taken to combine the information from the three sensors included in the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low false/nuisance alarm operation, and immediate visual assessment. It combines three sensor technologies, visible, infrared, and millimeter wave radar, collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of one revolution per second to detect and track motion and provide assessment in a continuous 360 degree(s) field-of-regard. Sensor fusion techniques are used to correlate and integrate the track data from the three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator.

Paper Details

Date Published: 14 February 1997
PDF: 12 pages
Proc. SPIE 2935, Surveillance and Assessment Technologies for Law Enforcement, (14 February 1997); doi: 10.1117/12.266804
Show Author Affiliations
Cynthia L. Nelson, Sandia National Labs. (United States)
Deborah S. Fitzgerald, Sandia National Labs. (United States)

Published in SPIE Proceedings Vol. 2935:
Surveillance and Assessment Technologies for Law Enforcement
A. Trent DePersia; Suzan Yeager; Steve M. Ortiz, Editor(s)

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