Three-Dimensional Passive Localization Method for Underwater Target Using Regular Triangular Array

2019 ◽  
Author(s):  
Xin-yi SUN ◽  
Nan-song LI ◽  
Xiao LIU
Keyword(s):  
Three Dimensional ◽  
Triangular Array ◽  
Localization Method ◽  
Underwater Target ◽  
Passive Localization

Shifted Rayleigh filter: a novel estimation filtering algorithm for pervasive underwater passive target tracking for computation in 3D by bearing and elevation measurements

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lakshmi M. Kavitha ◽  
Rao S. Koteswara ◽  
K. Subrahmanyam
Keyword(s):  
Target Tracking ◽  
Long Range ◽  
Target Location ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Content Type ◽  
Solution Convergence ◽  
Passive Target Tracking ◽  
Underwater Target ◽  
Target Motion Analysis

Purpose Marine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking. Design/methodology/approach This research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF). Findings SHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach. Originality/value The proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.

EODL: Energy Optimized Distributed Localization Method in three-dimensional underwater acoustic sensors networks

2018 ◽  
Vol 141 ◽  
pp. 179-188 ◽  
Author(s):  
Zhuo Wang ◽  
Xiaoning Feng ◽  
Guangjie Han ◽  
Yancheng Sui ◽  
Hongde Qin
Keyword(s):  
Three Dimensional ◽  
Acoustic Sensors ◽  
Underwater Acoustic ◽  
Localization Method

Three Tiered Self-Localization of Two Position Estimation Using Three Dimensional Environment Map and Gyro-Odometry

2014 ◽  
Vol 26 (2) ◽  
pp. 196-203 ◽  
Author(s):  
Kazuya Okawa ◽  
Keyword(s):  
Three Dimensional ◽  
Position Estimation ◽  
Map Matching ◽  
Localization Method ◽  
Challenge Course ◽  
Environment Map ◽  
Improve Accuracy ◽  
Environment Maps ◽  
Using Data ◽  
Map Data

As in the Tsukuba Challenge, any robot that autonomously moves around outdoors must be capable of accurate self-localization. Among many existing methods for robot self-localization, the most widely used is for the robot to estimate its position by comparing it with prior map data actually acquired using its sensor while it moves around. Although we use such a self-localization method in this study, this paper proposes a new method to improve accuracy in robot self-localization. In environments with few detected objects, a lack of acquired data very likely will lead to a failure in map matching and to erroneous robot self-localization. Therefore, a method for robot self-localization that uses three-dimensional environment maps and gyro-odometry depending on the situation is proposed. Moreover, the effectiveness of the proposed method is confirmed by using data from the 2013 Tsukuba Challenge course.

scholarly journals Wireless Sensor Network Target Localization Algorithm Based on Two- and Three-Dimensional Delaunay Partitions

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Chenguang Shao
Keyword(s):  
Three Dimensional ◽  
Target Localization ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
2D And 3D ◽  
The Relationship

The target localization algorithm is critical in the field of wireless sensor networks (WSNs) and is widely used in many applications. In the conventional localization method, the location distribution of the anchor nodes is fixed and cannot be adjusted dynamically according to the deployment environment. The resulting localization accuracy is not high, and the localization algorithm is not applicable to three-dimensional (3D) conditions. Therefore, a Delaunay-triangulation-based WSN localization method, which can be adapted to two-dimensional (2D) and 3D conditions, was proposed. Based on the location of the target node, we searched for the triangle or tetrahedron surrounding the target node and designed the localization algorithm in stages to accurately calculate the coordinate value of the target. The relationship between the number of target nodes and the number of generated graphs was analysed through numerous experiments, and the proposed 2D localization algorithm was verified by extending it the 3D coordinate system. Experimental results revealed that the proposed algorithm can effectively improve the flexibility of the anchor node layout and target localization accuracy.

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