A Passive Acoustic Positioning Algorithm Based on Virtual Long Baseline Matrix Window

2018 ◽  
Vol 72 (1) ◽  
pp. 193-206 ◽  
Author(s):  
Tao Zhang ◽  
Ziqiang Wang ◽  
Yao Li ◽  
Jinwu Tong
Keyword(s):  
Sound Source ◽  
Cross Correlation ◽  
Autonomous Underwater Vehicles ◽  
Underwater Sound ◽  
Positioning Systems ◽  
Long Baseline ◽  
Positioning Method ◽  
Passive Acoustic ◽  
Positioning Algorithm ◽  
Acoustic Positioning

A new acoustic positioning method for Autonomous Underwater Vehicles (AUV) that uses a single underwater hydrophone is proposed in this paper to solve problems of Long Baseline (LBL) array laying and communication synchronisation problems among all hydrophones in the traditional method. The proposed system comprises a Strapdown Inertial Navigation System (SINS), a single hydrophone installed at the bottom of the AUV and a single underwater sound source that emits signals periodically. A matrix of several virtual hydrophones is formed with the movement of the AUV. In every virtual LBL window, the time difference from the transmitted sound source to each virtual hydrophone is obtained by means of a Smooth Coherent Transformation (SCOT) weighting cross-correlation in the frequency domain. Then, the recent location of the AUV can be calculated. Simulation results indicate that the proposed method can effectively compensate for the position error of SINS. Thus, the positioning accuracy can be confined to 2 m, and the method achieves good applicability. Compared with traditional underwater acoustic positioning systems, the proposed method can provide great convenience in engineering implementation and can reduce costs.

Subjective Evaluation of Three Headphone-Based Virtual Sound Source Positioning Methods Including Differential Head-Related Transfer Function

2016 ◽  
Vol 41 (3) ◽  
pp. 437-447
Author(s):  
Dominik Storek ◽  
Frantisek Rund ◽  
Petr Marsalek
Keyword(s):  
Transfer Function ◽  
Sound Source ◽  
Subjective Evaluation ◽  
Sound Localisation ◽  
Signal Features ◽  
Listening Tests ◽  
Positioning Method ◽  
Head Related Transfer Function ◽  
Positioning Algorithm ◽  
Source Positioning

Abstract This paper analyses the performance of Differential Head-Related Transfer Function (DHRTF), an alternative transfer function for headphone-based virtual sound source positioning within a horizontal plane. This experimental one-channel function is used to reduce processing and avoid timbre affection while preserving signal features important for sound localisation. The use of positioning algorithm employing the DHRTF is compared to two other common positioning methods: amplitude panning and HRTF processing. Results of theoretical comparison and quality assessment of the methods by subjective listening tests are presented. The tests focus on distinctive aspects of the positioning methods: spatial impression, timbre affection, and loudness fluctuations. The results show that the DHRTF positioning method is applicable with very promising performance; it avoids perceptible channel coloration that occurs within the HRTF method, and it delivers spatial impression more successfully than the simple amplitude panning method.

scholarly journals Fog Computing-Based Differential Positioning Method for BDS

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Lina Wang ◽  
Linlin Li
Keyword(s):  
Fog Computing ◽  
Satellite Navigation ◽  
Original Data ◽  
Mobility Support ◽  
Positioning Systems ◽  
Satellite Navigation System ◽  
Differential Positioning ◽  
Positioning Method ◽  
Positioning Algorithm ◽  
Positioning Time

As one of the four global satellite navigation and positioning systems, BeiDou satellite navigation system (BDS) has received increasingly more attention. The differential positioning technology of BDS has greatly enhanced its accuracy and meets the needs of high-precision applications, but its positioning time still has much room for improvement. Fog computing allows the use of its services with low latency and mobility support to make up for the disadvantages of differential positioning algorithm. The paper proposes the fog computing-based differential positioning (FCDP) method which introduces fog computing technology to BDS. Compared with the original data center-based differential positioning (DCDP) method, the simulation results demonstrate that the FCDP method decreases the latency of positioning, while assuring the positioning accuracy.

Research on spatial positioning of online inspection robots for vertical storage tanks

2019 ◽  
Vol 47 (2) ◽  
pp. 187-195
Author(s):  
Zhiqiang Huang ◽  
Lei He ◽  
ZhaoXin Gao ◽  
Yingqi Jia ◽  
Yewei Kang ◽  
...  
Keyword(s):  
Storage Tank ◽  
Positioning Error ◽  
Content Type ◽  
Positioning Method ◽  
Spatial Positioning ◽  
Inspection Robots ◽  
Positioning Algorithm ◽  
Online Inspection ◽  
Technology Level ◽  
Acoustic Positioning

Purpose This paper aims to introduce a new acoustic positioning method to solve the problem of space positioning for online inspection robots within the storage tank. Design/methodology/approach The proposed positioning system comprises two acoustic signal emitters and two receivers. Emitters are brought by the robot into the storage tank. Receivers are mounted on the external edge of the storage tank floor. The spatial coordinate values and motion directions of the robot in the storage tank are calculated by using the proposed acoustic positioning algorithm. Findings The experiment results and positioning error analysis indicate that the method can obtain the data of robotic space coordinates and motion orientation, while the positioning error of the method can be less than 20 cm. The accuracy reaches the positioning technology level of other tank online inspection robots. Originality/value This method not only expands the positioning of the inspection robots from 2D plane to 3D space but also significantly reduces the number of positioning sensors carried by a robot and improves the safety of a robot in the tank.

Hawaii Experimental Acoustics Range for Shallow Water Applications

2011 ◽  
Vol 45 (3) ◽  
pp. 69-76 ◽  
Author(s):  
Tom Fedenczuk ◽  
Eva-Marie Nosal
Keyword(s):  
Shallow Water ◽  
Water Environment ◽  
Shallow Water Acoustics ◽  
Central Node ◽  
Long Baseline ◽  
Wide Range ◽  
Shallow Water Environment ◽  
Near Shore ◽  
Monitoring And Surveillance ◽  
Passive Acoustic

AbstractShallow water acoustics provide a means for monitoring and surveillance of near-shore environments. This paper describes the current and future capabilities of the low- to high-frequency Hawaii Experimental Acoustics Range (HEAR) that was designed to facilitate a wide range of different shallow water acoustics experiments and allow researchers from various institutions to test various array components and configurations. HEAR is a portable facility that consists of multiple hydrophones (12‐16) cabled independently to a common central node. The design allows for variable array configurations and deployments in three modes: experimental (off boats and piers), autonomous, and cabled. An application of HEAR is illustrated by the results from a deployment at Makai Research Pier, Oahu, Hawaii. In this deployment, HEAR was configured as a long-baseline range of two volumetric subarrays to study passive acoustic tracking capabilities in a shallow water environment.

Modeling AUV Localization Error in a Long Baseline Acoustic Positioning System

2018 ◽  
Vol 43 (4) ◽  
pp. 955-968 ◽  
Author(s):  
Dugald J. M. Thomson ◽  
Stan E. Dosso ◽  
David R. Barclay
Keyword(s):  
Positioning System ◽  
Localization Error ◽  
Long Baseline ◽  
Acoustic Positioning

scholarly journals RSS Based Wi-Fi Positioning Method Using Recursive Least Square (RLS) Algorithm

2018 ◽  
Vol 7 (2.24) ◽  
pp. 492
Author(s):  
Sreevardhan Cheerla ◽  
D Venkata Ratnam
Keyword(s):  
Least Square ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Positioning Systems ◽  
Indoor Location ◽  
Positioning Method ◽  
Accurate Position ◽  
Software And Hardware ◽  
Newton Raphson ◽  
Raphson Method

Due to rapid increase in demand for services which depends upon exact location of devices leads to the development of numerous Wi-Fi positioning systems. It is very difficult to find the accurate position of a device in indoor environment due to substantial development of structures. There are many algorithms to determine the indoor location but they require expensive software and hardware. Hence receiving signals strength (RSS) based algorithms are implemented to find the self-positioning. In this paper Newton-Raphson, Gauss-Newton and Steepest descent algorithms are implemented to find the accurate location of Wi-Fi receiver in Koneru Lakshmaiah (K L) University, Guntur, Andhra Pradesh, India. From the results it is evident that Newton -Raphson method is better in providing accurate position estimations. 

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