Differential Sampling for Fast Frequency Acquisition Via Adaptive Extended Least Squares Algorithm
AffiliationCalifornia Institute of Technology
California State University
MetadataShow full item record
RightsCopyright © International Foundation for Telemetering
Collection InformationProceedings 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.
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.
SponsorsInternational Foundation for Telemetering