Loading…

Direct estimation of multiple time-varying frequencies of non-stationary signals

•Instantaneous frequency estimation of multiple components simultaneously.•State estimation with noisy observation improved by the use of an underlying model.•Closed-form Jacobian matrix instead of numerical derivative improved accuracy.•Constrained extended Kalman filter used for wrapped phase retr...

Full description

Saved in:
Bibliographic Details
Published in:Signal processing 2020-04, Vol.169, p.107384, Article 107384
Main Authors: Samanta, Anik Kumar, Routray, Aurobinda, Khare, Swanand R., Naha, Arunava
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Instantaneous frequency estimation of multiple components simultaneously.•State estimation with noisy observation improved by the use of an underlying model.•Closed-form Jacobian matrix instead of numerical derivative improved accuracy.•Constrained extended Kalman filter used for wrapped phase retrieval.•Gravitational waves, motor supply frequency, bat-echo signal used as practical examples. In this paper, we propose a generalized framework for real-time tracking of multiple time-varying sinusoidal frequencies of a non-stationary signal. The non-stationary signal is modeled as a time-varying autoregressive (TVAR) process. A non-linear state-space model is formed to truly represent the TVAR process, considering the frequencies as state variables. We have defined the observation and its Jacobian by the modified roots of a polynomial formed by the state variables. Numerical derivatives have been substituted by the analytic form of the Jacobian matrix for improved numerical accuracy. A constrained Kalman filter is then applied for real-time tracking of the frequencies. We have compared the statistical performance of the proposed method with four other established methods using Monte-Carlo simulations. The proposed method is found to have superior error performance under different conditions of chirp-rate, resolution, noise variance, and abrupt changes in frequency. Additionally, we have taken the bat echolocation signal, gravitational waves of a binary black hole merger, and supply frequency of a three-phase squirrel cage induction motor as practical examples to demonstrate the applicability and efficacy of the proposed method in real-world scenarios.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2019.107384