Acoustic localization with multi-layer isogradient sound speed profile using TDOA and FDOA

Zhan, Dongzhou; Wang, Sitian; Cai, Shougui; Zheng, Huarong; Xu, Wen

doi:10.1631/fitee.2100398

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…In particular, the two–level architecture facilitates the addition of new function modules. For example, currently, it is assumed that the sound velocity is constant; a ray–tracing submodule [ 39 ] can be added to the mapping simulation module to handle a depth–dependent sound velocity profile.…”

Section: Discussionmentioning

confidence: 99%

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

Meng

Shen

et al. 2023

Sensors

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Side scan sonar (SSS) is a multi–purpose ocean sensing technology, but due to the complex engineering and variable underwater environment, its research process often faces many uncertain obstacles. A sonar simulator can provide reasonable research conditions for guiding development and fault diagnosis, by simulating the underwater acoustic propagation and sonar principle to restore the actual experimental scenarios. However, the current open–source sonar simulators gradually lag behind mainstream sonar technology; therefore, they cannot be of sufficient assistance, especially due to their low computational efficiency and unsuitable high–speed mapping simulation. This paper presents a sonar simulator based on a two–level network architecture, which has a flexible task scheduling system and extensible data interaction organization. The echo signal fitting algorithm proposes a polyline path model to accurately capture the propagation delay of the backscattered signal under high–speed motion deviation. The large–scale virtual seabed is the operational nemesis of the conventional sonar simulators; therefore, a modeling simplification algorithm based on a new energy function is developed to optimize the simulator efficiency. This paper arranges several seabed models to test the above simulation algorithms, and finally compares the actual experiment results to prove the application value of this sonar simulator.

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Section: Discussionmentioning

confidence: 99%

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

Meng

Shen

et al. 2023

Sensors

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“…The sound speed profile (SSP) is an important oceanic parameter that is used in a variety of marine acoustic applications, such as underwater target identification, underwater communication, and marine environmental monitoring (Teymorian et al, 2009;Xu et al, 2013;Luo et al, 2022;Su et al, 2022;Zhan et al, 2023). The speed of sound varies significantly even in adjacent areas of the sea due to the complexity and variability of the marine environment.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing the sound speed profile of South China Sea using remote sensing data and long short-term memory neural networks

Zhao,

Xu,

et al. 2024

Front. Mar. Sci.

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IntroductionSound waves are refracted along the direction of their propagation owing to spatial and temporal fluctuations in the speed of sound in seawater. Errors are compounded when sound speed profiles (SSPs) with low precision are used to detect and locate distant underwater targets because an accurate SSP is critical for the identification of underwater objects based on acoustic data. Only sparse historical spatiotemporal data on the SSP of the South China Sea are available owing to political issues, its complex atmospheric system, and the unique topography of its seabed, because of which frequent oceanic movements at the mesoscale affect the accuracy of inversion of its SSP.MethodIn this study, we propose a method for the inversion of the SSP of the South China Sea based on a long short-term memory model. We use continuous-time data on the SSP of the South China Sea as well as satellite observations of the height and temperature of the sea surface to make use of the long-term and short-term memory-related capacities of the proposed model.ResultIt can achieve highly accurate results while using a small number of samples by virtue of the unique structure of its memory. Compared with the single empirical orthogonal function regression method, the inversion accuracy of this model is improved by 24.5%, and it performed exceptionally well in regions with frequent mesoscale movements.DiscussionThis enables it to effectively address the challenges posed by the sparse sample distribution and the frequent mesoscale movements of the South China Sea.

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“…The observations are limited by heights in [12], which offers an altitude constrained source localisation utilising Time Difference of Arrival, FDOA, and differential Doppler rate. The methods of joint TDOA and FDOA localization, passive DOA multiple sensor networks for mobile targets, and multiple sources are presented in [13], [14] and [15] respectively. However, they do not take into account receivers mounted on multiplatform devices, which can be stationary or mobile, and the method is computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

Emitter Geolocation from Near-Space Platform Using 3D TDOA

2023

5th ISSE National Conference (INAC-05) on Systems Approach for Self-Reliance in Advanced Technologies

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The space between the maximum altitude at which a modern plane can fly and the minimum altitude at which a satellite can operate is known to as near space. A free balloon, an airship, and an unmanned aerial (UAV) vehicle are some of the aircraft in the near space. The near-space platform has the ability to identify far-off emitters in a large area due to its unique feature of having a large coverage area, full-time, and large-scaled. Near-space has drawn a lot of attention recently since it is below the ionosphere and doesn't experience ionospheric scintillations, which can significantly degrade RF communications and navigation performance. The focus of this paper is to compute geolocation in various scenarios. Geolocation is computed in two dimension (2D) using hybrid AOA/TDOA/FDOA measurements from ground/ship-based sensors at varying emitter distances and geolocation accuracy is calculated using Root Mean Square Error (RMSE) and Circular Error of Probability (CEP50). Further, geolocation is computed in three dimension (3D) using TDOA measurements from ground/ship-based sensors at varying emitter altitudes and geolocation accuracy is computed in terms of total joint covariance matrix (Standard Deviation) from all receivers. The results of above geolocation accuracy are compared with geolocation from near-space based sensors placed at varying altitudes while the emitter is placed on ground/ship-based platform using 3D TDOA measurements. TDOA measurements are obtained by cross-correlating the signal received at all the sensors. The performance for all the scenarios are demonstrated through modeling and simulations. Experimental results in varied scenarios and specifically near-space platforms will help in designing of systems as per the required accuracy and in future visualizing the accuracies from space-based platforms.

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Acoustic localization with multi-layer isogradient sound speed profile using TDOA and FDOA

Cited by 8 publications

References 27 publications

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

Reconstructing the sound speed profile of South China Sea using remote sensing data and long short-term memory neural networks

Emitter Geolocation from Near-Space Platform Using 3D TDOA

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