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On adaptive cell-averaging CFAR radar signal detection

Posted on:1988-06-25Degree:Ph.DType:Dissertation
University:Syracuse UniversityCandidate:Barkat, MouradFull Text:PDF
GTID:1478390017456842Subject:Engineering
Abstract/Summary:
In radar signal detection, the problem is to automatically detect a target in a nonstationary noise and clutter background while maintaining a constant probability of false-alarm. Classical detection using a matched filter receiver and a fixed threshold is not applicable due to the nonstationary nature of the background noise. Therefore, adaptive threshold techniques are needed to maintain a constant false-alarm rate (CFAR). One approach to adaptive detection in nonstationary noise and clutter background is to compare the processed target signal to an adaptive threshold. In the cell-averaging CFAR processing, an estimate of the background noise from the leading and the lagging reference windows is used to set the adaptive threshold. A threshold multiplier (or scaling factor) is used to scale the threshold to achieve the desired probability of false-alarm.; In the first part of this dissertation, we have proposed two modified cell-averaging detectors for multiple target situations. The first one is a weighted cell-averaging CFAR detector, WCA-CFAR, where weighted leading and lagging reference windows are used to obtain the adaptive threshold. The second is a cell-censored cell-averaging CFAR processor where a predetermined fixed threshold is used to eliminate those cells that may contain interference.; In the second part of the dissertation, the theory of distributed CFAR detection with data fusion is developed. First, a system consisting of n CA-CFAR detectors with data fusion is considered. The overall system is optimized so that the overall probability of detection is maximum while the overall probability of false-alarm is fixed at the desired value. Next, CFAR detection with multiple background estimators and a data fusion center is studied. Finally, adaptive CFAR detection with multiple detectors for different network topologies is considered. Two topologies, namely, a parallel and a tandem topology are investigated. The overall systems are optimized so that the probability of detection is maximum while CFAR is achieved.
Keywords/Search Tags:CFAR, Detection, Adaptive, Signal, Background, Probability, Noise, Overall
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