Time delay estimation in reverberant and low SNR environment by EMD based maximum likelihood method

•Time delay estimated by EMD ML in low SNR and reverberant underwater environment.•In EMD ML method, estimation of impulse response function is been avoided.•Among TDE methods EMD ML is suitable in low signal strength, low frequency source. In recent times, time delay estimation (TDE) has received s...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2019-04, Vol.137, p.655-663
Hauptverfasser: Marxim Rahula Bharathi, B., Mohanty, A.R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Time delay estimated by EMD ML in low SNR and reverberant underwater environment.•In EMD ML method, estimation of impulse response function is been avoided.•Among TDE methods EMD ML is suitable in low signal strength, low frequency source. In recent times, time delay estimation (TDE) has received significant practical importance in sonar, radar, GPS, and various other fields. In a passive sonar system, estimation of time delay for low frequency and low signal to noise (SNR) acoustic source is a difficult task. If the source and receivers are kept inside the reverberation environment, time delay estimation becomes more difficult because of sound source echo’s. This research work proposes a new TDE approach named empirical mode decomposition maximum likelihood time delay estimation (EMD ML TDE) method, for the low-frequency and low SNR underwater machinery acoustic signal in a reverberant environment. EMD ML TDE method is based on maximum likelihood (ML) method, and it is using empirical mode decomposition (EMD) denoising technique to estimate acoustic sound signal and noise from the noisy reverberant signal. The experimental results are provided that this new approach is better to estimate time delay in reverberant environments.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2019.01.096