Calibration and Direction of Arrival Performance of Sonar Arrays Composed of Multiple Sub-arrays

Ganti, Anil

doi:10.1109/oceans.2018.8604833

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…As an important branch of signal processing, array signal processing has developed rapidly in recent years. Up to now, array signal processing technology has been widely used in many military and civil fields such as radar [1,2], sonar [3], communication [4], navigation [5,6], intelligent transportation [7], geological exploration and even home safety monitoring [8,9]. Direction of arrival (DOA) estimation [10] has become one of the most important topics in array research.…”

Section: Introductionmentioning

confidence: 99%

A New Sparse Optimal Array Design Based on Extended Nested Model for High-Resolution DOA Estimation

Wang

Ren

et al. 2022

Electronics

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In this paper, we propose a new strategy with increased element spacings placed on two-side subarrays and increase the physical sparse sensors array aperture. In order to ensure the continuity of difference co-array, four conditions are proposed. Based on these conditions, a new array structure named TS2-ENA is derived. Compared with other nested-like arrays with a fixed number of elements, our proposed structure possesses a higher degree of freedom, closed-form expression and outstanding performance. Simulation results show the superiority of the new configuration with the spacial smoothing MUSIC algorithm conducted.

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Section: Introductionmentioning

confidence: 99%

A New Sparse Optimal Array Design Based on Extended Nested Model for High-Resolution DOA Estimation

Wang

Ren

et al. 2022

Electronics

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Signals-of-Opportunity-Based Hydrophone Array Shape and Orientation Estimation

Skog,

Nordenvaad,

Hendeby

2024

IEEE J. Oceanic Eng.

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A signal-of-opportunity-based method to automatically calibrate the orientations and shapes of a set of hydrophone arrays using the sound emitted from nearby ships is presented. The calibration problem is formulated as a simultaneous localization and mapping (SLAM) problem, where the locations, orientations, and shapes of the arrays are viewed as the unknown map states, and the position, velocity, etc. of the source as the unknown dynamic states. A sequential likelihood ratio test, together with a maximum a posteriori source location estimator, is used to automatically detect suitable sources and initialize the calibration procedure. The performance of the proposed method is evaluated using data from two 56-element hydrophone arrays. Results from two sea trials indicate that: (a) signal sources suitable for the calibration can be automatically detected; (b) the shapes and orientations of the arrays can be consistently estimated from the different data sets with shape variations of a few decimeters and orientation variations of less than two degrees; and (c) the uncertainty bounds calculated by the calibration method are in agreement with the true calibration uncertainties. Furthermore, the bearing time record from a sea trial with an autonomous mobile underwater signal source also shows the efficacy of the proposed calibration method. In the studied scenario the root mean square bearing tracking error was reduced from 4 to 1 degree when using the calibrated array shapes compared to assuming the arrays' to be straight lines. Also, the beamforming gain increased by approximately 1 decibel.

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Calibration and Direction of Arrival Performance of Sonar Arrays Composed of Multiple Sub-arrays

Cited by 2 publications

References 10 publications

A New Sparse Optimal Array Design Based on Extended Nested Model for High-Resolution DOA Estimation

A New Sparse Optimal Array Design Based on Extended Nested Model for High-Resolution DOA Estimation

Signals-of-Opportunity-Based Hydrophone Array Shape and Orientation Estimation

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