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Decentralized CFAR signal detection
Signal Processing, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Emad K. Al-Hussaini +2 more
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CFAR Outlier Detection With Forward Methods
IEEE Transactions on Signal Processing, 2007Separation or classification of signal-present samples from noise-only samples is studied. The false-alarm probability implies how many noise-only samples are wrongly classified as outliers, and typically it should be smaller than some upper limit. The noise distribution parameters are not known a priori and have to be estimated. Multiple outliers have
Saarnisaari Harri +3 more
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Adaptive CFAR detection of multidimensional signals
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002Adaptive detection of multidimensional signals in the presence of interference with unknown covariance matrix is an expanding topic in a variety of scenarios ranging from radar/sonar to digital communication systems. We attack the problem of detecting a multidimensional radar signal, modeled as an unknown N/spl times/H matrix, embedded in Gaussian ...
E. Conte +3 more
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CFAR detection for two correlated targets
Signal Processing, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mourad Barkat, Samira Dib
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Weighted likelihood CFAR detection for Weibull background
Digital Signal Processing, 2021Abstract In modern radar detection systems, constant false alarm rate (CFAR) control is a key technique for automatic target detection in clutter level unknown environments. The maximum likelihood criterion is often used to design the CFAR detector for which it has the best detection performance with the expected probability of false alarm.
Baiqiang Zhang +3 more
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OS characterization for local CFAR detection
IEEE Transactions on Systems, Man, and Cybernetics, 1991An order-statistic (OS) characterization for modeling clutter statistics at local detectors is presented. Important features of the OS characterization include its structure, which allows for parallel computations, and its degrees of freedom, which enable it to track various changes in the clutter statistics.
Kevin D. Donohue, Nihat M. Bilgutay
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An improved CFAR algorithm for target detection
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2017The constant false alarm rate (CFAR) technique plays a key role in radar automatic detection process. The cell averaging (CA) CFAR procedure suffers from the masking effect in almost all the multitarget situations. The smallest of cell averaging (SOCA) CFAR has a better performance only when the interfering targets are present in the front or the rear ...
Chunmei Xu +5 more
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A time frequency approach to CFAR detection
2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2011Simultaneous analysis of signals in time and frequency domains is a standard approach in many signal processing applications including some detection. Parameters of clutter, noise and interference, and in some cases Doppler specifications, are the basis for most of current CFAR target detection techniques.
Siamak Layeghy +3 more
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On the modelling of uncertainty in radar CFAR detection
Signal, Image and Video Processing, 2009In this paper, we propose a model for a constant false alarm detection that uses fuzzy logic to describe the uncertainty on the decision about the presence or the absence of a target. The received signal is processed in a sequential manner so that the test is performed after each observation.
Chehla Alioua, Faouzi Soltani
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