Differential Sampling for Fast Frequency Acquisition Via Adaptive Extended Least Squares Algorithm

Persistent Link:
http://hdl.handle.net/10150/615321
Title:
Differential Sampling for Fast Frequency Acquisition Via Adaptive Extended Least Squares Algorithm
Author:
Kumar, Rajendra
Affiliation:
California Institute of Technology; California State University
Issue Date:
1987-10
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
This paper presents a differential signal model along with appropriate sampling techniques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in measurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can be made small.
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleDifferential Sampling for Fast Frequency Acquisition Via Adaptive Extended Least Squares Algorithmen_US
dc.contributor.authorKumar, Rajendraen
dc.contributor.departmentCalifornia Institute of Technologyen
dc.contributor.departmentCalifornia State Universityen
dc.date.issued1987-10-
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractThis paper presents a differential signal model along with appropriate sampling techniques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in measurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can be made small.en
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123-
dc.identifier.issn0074-9079-
dc.identifier.urihttp://hdl.handle.net/10150/615321-
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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