JOURNAL ARTICLE

Improving the localization estimates using Kalman filters

Abstract

Localization of underwater targets is an important requirement in surveillance operations. A method for improving the accuracy of the estimated location of an unknown target using Kalman filters is presented in this paper. The localisation is carried out using a sensor network comprising of three fixed surface buoy systems, each consisting of steerable hydrophone arrays and support electronics, positioned at the vertices of a triangle. The system picks up the noise emanations from the targets of interest and the hydrophone arrays of each node gets aligned to the direction of maximum signal arrival (DOA). Using the DOAs measured at each buoy system, the distances of the target from the three nodes are computed using the triangulation technique.

Keywords:
Hydrophone Kalman filter Computer science Multilateration Triangulation Underwater Noise (video) Node (physics) SIGNAL (programming language) Buoy Direction finding Acoustics Computer vision Real-time computing Artificial intelligence Engineering Telecommunications Geology Geography Physics Marine engineering

Metrics

3
Cited By
0.26
FWCI (Field Weighted Citation Impact)
4
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Underwater Acoustics Research
Physical Sciences →  Earth and Planetary Sciences →  Oceanography
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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