Ship-board pedestrian positioning method by integrating Dead Reckoning and Wireless Sensor Networks

2015 ◽  
Author(s):  
Kezhong Liu ◽  
Yihang Xie ◽  
Mozi Chen ◽  
Jie Ma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dead Reckoning ◽  
Wireless Sensor ◽  
Positioning Method

An Improved Sensor Positioning for Wireless Sensor Networks

2014 ◽  
Vol 716-717 ◽  
pp. 1322-1325
Author(s):  
Jin Tao Lin ◽  
Guang Yu Fan ◽  
Wen Hong Liu ◽  
Ying Da Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Sensor Positioning

Sensor positioning is a fundamental block in various location-dependent applications of wireless sensor networks. In order to improve the positioning accuracy without increasing the complex and cost of sensor nodes, an improve sensor positioning method is proposed for wireless sensor networks. In the method, after receiving the broadcasting message of the neighboring anchor nodes, the sensor nodes calculate a modifying factor of the change of the signal strength. And they modify the distances between themselves and neighboring anchor nodes with the modifying factor. Simulation results show that the proposed method can obtain a high positioning accuracy.

scholarly journals Development and Application of a New Positioning Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 14 (10) ◽  
pp. 80
Author(s):  
Guohong Gao ◽  
Feng Wei ◽  
Jianping Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Measurement Error ◽  
Wireless Sensor ◽  
Time Of Arrival ◽  
Unknown Parameters ◽  
Positioning Method ◽  
Research Findings ◽  
Positioning Algorithm ◽  
Technical Basis

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">This paper aims to create a desirable positioning method for nodes in wireless sensor networks (WSNs). For this purpose, a source node positioning algorithm was developed based on time-of-arrival (TOA), in view of the nonlinear correlation between the measured values and unknown parameters in the observation equation of TOA source position. Several experiments were carried out to evaluate the performance of the proposed algorithm in terms of time measurement error, computing complexity, location error and Cramér–Rao lower bound (CRLB). The results show that the CRLB acquired by this algorithm can be used for WSN node positioning, provided that the independent zero mean Gauss measurement error is sufficiently small. The research findings lay a solid technical basis for optimal management, load balance, efficient routing, and automatic topology control of WSNs.</span>

Analysis of Flying Vehicle Cooperative Positioning by Sea-Surface Wireless Sensor Networks

2012 ◽  
Vol 505 ◽  
pp. 338-344
Author(s):  
Wei Ming Xu ◽  
Xiao Dong Yin ◽  
Geng Feng Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Time Synchronization ◽  
Sea Surface ◽  
Wireless Sensor ◽  
Relative Positioning ◽  
Cooperative Positioning ◽  
Positioning Method ◽  
Absolute Bias ◽  
Positioning Algorithm

Sea-surface wireless sensor networks (S2WSN) is a combination of many nodes forming a certain geometric shape, such as ships and sea-surface radio buoys. To satisfy the requirement of precise tracking for flying vehicle (FV) in times of exterior location datum outages, a cooperative positioning algorithm (CPA) for the FV is proposed. Time synchronization among the nodes is crucial to guarantee CPA. Taking a single-hop S2WSN as an example, the problem of low synchronization precision is resolved by two-way timing with unequal reply time (TWT-UTD). Monte Carlo simulation results show that, through optimizing the position dilution of precision among the sea-surface nodes and the FV, the absolute bias of the FV tracking by the proposed CPA is superior to that of the conventional single ship-based relative positioning method. Meanwhile, the synchronization precision is increased by more than 20% via TWT-UTD method.

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