3DPHDV-Hop: A new 3D positioning algorithm using partial HopSize in WSN

2013 ◽  
Author(s):  
Rui-Jin Wang ◽  
Zhi-Guang Qin ◽  
Ja-Hao Wang ◽  
Yang Zhao ◽  
Wei-Wei Ni
Keyword(s):  
3D Positioning ◽  
Positioning Algorithm

A Decentralized Positioning Method for Wireless Sensor Networks

2014 ◽  
Vol 668-669 ◽  
pp. 1194-1197 ◽  
Author(s):  
Yan Feng ◽  
Bo Yi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Three Dimensional ◽  
Research Direction ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Position Information ◽  
Initial Location ◽  
3D Positioning ◽  
Positioning Algorithm

The three-dimensional positioning algorithm has become a hot research direction in wireless sensor networks localization algorithms, however the existing 3D positioning algorithms have general shortcomings, such as high complexity, low positioning accuracy, great energy consumption. Aiming at the existing problems of 3D localization algorithm, we propose an decentralized 3D positioning algorithm based on RSSI ranging and free ranging mechanism. The algorithm firstly use measured RSSI to establish beacon node neighborhood. Then the method adopts regional division to obtain initial location information for unknown nodes. Finally, the method use the iterative optimization process to achieve a position information updates. Simulation results demonstrate that proposed algorithm is feasible and has better localization accuracy.

scholarly journals Object Positioning Algorithm Based on Multidimensional Scaling and Optimization for Synthetic Gesture Data Generation

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5923
Author(s):  
Borja Saez-Mingorance ◽  
Antonio Escobar-Molero ◽  
Javier Mendez-Gomez ◽  
Encarnacion Castillo-Morales ◽  
Diego P. Morales-Santos
Keyword(s):  
Synthetic Data ◽  
Qualitative Evaluation ◽  
Mobile Object ◽  
Data Generation ◽  
Limited Memory ◽  
Synthetic Data Generation ◽  
Data Generator ◽  
3D Positioning ◽  
Step Algorithm ◽  
Positioning Algorithm

This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Memory-Broyden-Fletcher-Goldfarb-Shannon. A qualitative evaluation of these algorithms is performed for 3D positioning. As the final stage, smoothing filtering techniques are applied to estimate the trajectory, from the previously obtained positions. This approach can also be used as a synthetic gesture data generator framework. This framework is independent from the hardware and can be used to simulate the estimation of trajectories from noisy distances gathered with a large range of sensors by modifying the noise properties of the initial distances. The framework is validated, using a system of ultrasound transceivers. The results show this framework to be an efficient and simple positioning and filtering approach, accurately reconstructing the real path followed by the mobile object while maintaining low latency. Furthermore, these capabilities can be exploited by using the proposed algorithms for synthetic data generation, as demonstrated in this work, where synthetic ultrasound gesture data are generated.

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