TY - JOUR
T1 - Particle filtering for arrival time tracking in space and source localization
AU - Michalopoulou, Zoi Heleni
AU - Jain, Rashi
N1 - Funding Information:
This work was supported by the Office of Naval Research through grants N000140510262, N000140710521, and N000141010073.
PY - 2012/11
Y1 - 2012/11
N2 - Locating and tracking a source in an ocean environment and estimating environmental parameters of a sound propagation medium are critical tasks in ocean acoustics. Many approaches for both are based on full field calculations which are computationally intensive and sensitive to assumptions on the structure of the environment. Alternative methods that use only select features of the acoustic field for localization and environmental parameter estimation have been proposed. The focus of this paper is the development of a method that extracts arrival times and amplitudes of distinct paths from measured acoustic time-series using sequential Bayesian filtering, namely, particle filtering. These quantities, along with complete posterior probability density functions, also extracted by filtering, are employed in source localization and bathymetry estimation. Aspects of the filtering methodology are presented and studied in terms of their impact on the uncertainty in the arrival time estimates. Using the posterior probability densities of arrival times, source localization and water depth estimation are performed for the Haro Strait Primer experiment; the results are compared to those of conventional methods. The comparison demonstrates a significant advantage in the proposed approach.
AB - Locating and tracking a source in an ocean environment and estimating environmental parameters of a sound propagation medium are critical tasks in ocean acoustics. Many approaches for both are based on full field calculations which are computationally intensive and sensitive to assumptions on the structure of the environment. Alternative methods that use only select features of the acoustic field for localization and environmental parameter estimation have been proposed. The focus of this paper is the development of a method that extracts arrival times and amplitudes of distinct paths from measured acoustic time-series using sequential Bayesian filtering, namely, particle filtering. These quantities, along with complete posterior probability density functions, also extracted by filtering, are employed in source localization and bathymetry estimation. Aspects of the filtering methodology are presented and studied in terms of their impact on the uncertainty in the arrival time estimates. Using the posterior probability densities of arrival times, source localization and water depth estimation are performed for the Haro Strait Primer experiment; the results are compared to those of conventional methods. The comparison demonstrates a significant advantage in the proposed approach.
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U2 - 10.1121/1.4756954
DO - 10.1121/1.4756954
M3 - Article
C2 - 23145590
AN - SCOPUS:84869129714
SN - 0001-4966
VL - 132
SP - 3041
EP - 3052
JO - Journal of the Acoustical Society of America
JF - Journal of the Acoustical Society of America
IS - 5
ER -