NDLI: Active Detection With a Barrier Sensor Network Using a Scan Statistic

Content Provider	IEEE Xplore Digital Library
Author	Xiufeng Song Willett, P. Glaz, J. Shengli Zhou
Copyright Year	1976
Abstract	Abstract-The cooperation of an active acoustic source and a large number of distributed passive sensors offers an opportunity for active sonar detection. The system works as follows: first, each sensor compares its matched filter output with a given threshold to obtain a binary local decision-"0" or "1"; then, a fusion center (FC) collects them to make a system-level inference. How effectively to combine these local results-distributed detection fusion-is the concentration of this paper. Suppose that the sensor network is unaware of the target's reflection model. Then, the local detection probabilities cannot be obtained; therefore, the optimal fusion rule is unavailable. The obvious detection strategy is a counting rule test (CRT), which simply counts the total number of 1's and compares it to a threshold. This approach does not require knowledge of sensor locations, and equally considers all network subareas. However, the reflected signal from some targets, such as a submarine, can be highly aspect dependent, and in many instances only sensors in a particular zone can receive its echoes. This paper focuses on the scan statistic, which slides a window across the sensor field, and selects the subarea with the largest number of 1's to make a decision. The scan statistic integrates the aspect-dependence characteristic of the target into detection fusion. With a proper window size, it may suppress the subarea interference, and improve the system-level performance.
Sponsorship	IEEE Oceanic Engineering Society
Starting Page	66
Ending Page	74
Page Count	9
File Size	1822311
File Format	PDF
ISSN	03649059
Volume Number	37
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Acoustics Object detection Probability Propagation losses Geometry Surveillance Impedance matching submarine Counting rule test (CRT) detection detection fusion multistatic scan statistic sensor network sonar
Content Type	Text
Resource Type	Article
Subject	Ocean Engineering Mechanical Engineering Electrical and Electronic Engineering

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