Analisis Perkiraan TDOA menggunakan Algoritma LMS Adaptif pada Pelacakan Paus Lodan

https://doi.org/10.22146/ijeis.7149

Andriyan Permana(1*), Agfianto Eko Putra(2), Catur Atmaji(3)

(1) 
(2) Jurusan Ilmu Komputer dan Elektronika, FMIPA UGM
(3) Jurusan Ilmu Komputer dan Elektronika, FMIPA UGM
(*) Corresponding Author

Abstract


Research on TDOA estimation in sperm whale tracking has been done [1] that uses the Teager - Kaiser operator in improving accuracy the TDOA estimation using adaptive LMS algorithm on sperm whale tracking. However, further researches on the right convergence factor (μ) (fast and accurate) in TDOA estimation using adaptive LMS algorithms for sperm whale tracking have not been performed. Will be analyzed the TDOA estimation using adaptive LMS algorithm in sperm whale tracking with the variation of μ. As a reference to determine the right value of μ, the results of sperm whale tracking[2] is used.

TDOA estimation using Adaptive LMS algorithm was first published by Benesty [3]. The approach taken is based on estimation of the impulse responses from source to receivers. In the adaptive LMS algorithm function updates the coefficient with μ as adaptation step. TDOA values obtained from the difference between the two impulse responses.

From the results, values changing of μ affect the speed of TDOA estimation using the LMS adaptive algorithm. However, the wrong value of μ is lead to inaccurate sperm whale tracking results. The best value of μ for TDOA estimation using the LMS adaptive algorithm for sperm whale tracking is 0.01.


Keywords


TDOA estimation, adaptive LMS, convergence factor, sperm whale tracking

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References

[1] Kandia, V., Dutoit, T., Stylianou, Y., 2008, Improve the accuracy of TDOA measurement using the Teager-Kaiser Energy operator, New Trends for Environmental Monitoring Using Passive Systems, 1-6.
[2] Kandia, V., Dutoit, T., Stylianou, Y., 2009, How can marine biologists track sperm whales in the oceans?, Dutoit, T., Marques, F., Applied Signal Processing A MATLAB - Based Proof of Concept, Springer Science+Business Media, New York.

[3] Benesty, J., 2000, Adaptive eigenvalue decomposition algorithm for passive acoustic source localization, Journal of the Acoustical Society of America, 107(1), 384–391.
[4] Kaiser, J.F., 1990, On a simple algorithm to calculate the “Energy” of a signal, Proceedings of the IEEE ICASSP, Albuquerque.
[5] Kandia, V. dan Stylianou, Y., 2005, Detection of creak clicks of sperm whales in low SNR conditions, CD Proceedings of the IEEE Oceans, Brest.



DOI: https://doi.org/10.22146/ijeis.7149

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