Journal article

Phase-Continuous Frequency Line Track-Before-Detect of a Tone With Slow Frequency Variation

Sofia Suvorova, Andrew Melatos, Rob J Evans, William Moran, Patrick Clearwater, Ling Sun

IEEE Transactions on Signal Processing | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2018

Abstract

We consider optimal Bayesian detection of a slowly varying tone of unknown amplitude in situations characterized by very low signal-To-noise ratio (SNR) and a large number of measurements, as found in certain gravitational wave and passive sonar problems. We use a hidden Markov model (HMM) framework but, unlike typical HMM-based frequency line tracking methods, we develop a true track-before-detect algorithm, which does not threshold the blocked Fourier data and only considers frequency trails that have phase continuity across all HMM steps. We model the frequency and phase evolution as a phase-wrapped Ornstein-Uhlenbeck process. The resulting optimal detector is computationally efficient. T..

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Grants

Awarded by Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav)


Awarded by USA National Science Foundation


Funding Acknowledgements

The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Wenwu Wang. This work was supported by the Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav) under Grant CE170100004 and in part by the Aspen Center for Physics, which is supported by the USA National Science Foundation under Grant PHY-1607611.