NDLI: Robust estimation of sinusoidal signals with colored noise using decentralized processing

Content Provider	IEEE Xplore Digital Library
Author	Kashyap, R.L. Oh, S.G. Madan, R.N.
Copyright Year	1974
Abstract	A technique is developed for the estimation of the number of signals and their central frequencies using decentralized processing, when it is known a priori that the observations consist of a finite number of sinusoidal signals corrupted by an additive colored random noise process with unknown correlations. Such a noise sequence may be caused by jamming from a hostile agent. The authors' decentralized processing scheme is one in which each sensor estimates the frequencies and their covariance matrix and sends the results to the fusion center. At the fusion center, since the estimates from the sensors have a mixture density that is possibly not Gaussian, a robust technique is utilized to combine the estimates. Even when the numbers of frequencies transmitted by the various sensors are identical, determining corresponding frequencies from each sensor is not a straightforward task. Also, outliers caused by line splitting or by spurious frequencies are hard to detect. These problems can be resolved by two methods: the so-called refitting method and the ranking method. Algorithms for both are presented in detail.<>
Starting Page	91
Ending Page	104
Page Count	14
File Size	1272274
File Format	PDF
ISSN	00963518
Volume Number	38
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise robustness Signal processing Colored noise Sensor arrays Frequency estimation Covariance matrix Additive noise Sensor fusion Central Processing Unit Parameter estimation
Content Type	Text
Resource Type	Article
Subject	Signal Processing

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