NDLI: Distributed adaptive OSWCA CFAR detector

Content Provider	IEEE Xplore Digital Library
Author	Ma Xiaoyan Xiang Jiabin Yang Jun
Copyright Year	2004
Description	Author affiliation: Dept. of lnf. Eng., Air Force Radar Acad., Hubei, China (Ma Xiaoyan; Xiang Jiabin; Yang Jun)
Abstract	In the sense of likelihood ratio test (LRT), a weighted adaptive OSWCA CFAR detector using distributed sensors is proposed in this paper. In the scheme, a local test statistic, which is the ratio of its test sample level and a designated order statistic (OS) of its reference samples, is calculated by each sensor, and then each sensor transmits its local test statistic to the fusion center. At the fusion center, the final decision is made based on weighted cell averaging algorithm (WCA). Since the weights are adjusted according to different signal-to-noise/clutter ratio (SNR), adaptively, the proposed detector can be available in the case of that the target echo and noise/clutter that have different level for each sensor. Unlike many current distributed CFAR detectors, which assuming that all noise/clutter samples satisfy independent identical distributed (IID) and have same SNR for each sensor. Meanwhile, for a Rayleigh fluctuating target in Gaussian noise of unknown level, we obtain its closed-form expressions for the false alarm probability and the detection probability. The numerical analysis results indicate that the proposed OSWCA scheme can be available.
Starting Page	2082
Ending Page	2085
File Size	711471
Page Count	4
File Format	PDF
ISBN	0780384067
DOI	10.1109/ICOSP.2004.1442186
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-08-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Testing Statistical analysis Statistical distributions Signal to noise ratio Sensor fusion Light rail systems Adaptive signal detection Noise level Gaussian noise
Content Type	Text
Resource Type	Article

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