Anchor-Free Localization Algorithm with Low-Complexity Method for Node Distance Estimation Enhancement Using ToA

Author(s):  
Vladimír Cipov ◽  
L’ubomír Doboš ◽  
Ján Papaj
2007 ◽  
Vol 04 (01) ◽  
pp. 77-89 ◽  
Author(s):  
WANMING CHEN ◽  
HUAWEI LIANG ◽  
TAO MEI ◽  
ZHUHONG YOU ◽  
SHIFU MIAO ◽  
...  

Global Positioning System (GPS) is often used as a main information source for robot localization and navigation. However, it cannot be used in room or in field complex environment because of the bad signal there. To solve this problem, the authors designed and implemented a specific wireless sensor network (WSN) to provide information about the environment and indicate path for robot navigation. A two-stage auto-adaptive route selecting mechanism of the WSN was proposed to facilitate data relaying in localization and the robot's navigation. A low complexity localization algorithm was used to localize both the nodes and the robot. An indirect communication method was designed to make the communication between the WSN and the robot possible. In addition, a robot navigation method was proposed based on the wireless sensor network. In this method, the robot did not need to obtain the environment information; the wireless sensor nodes collected and fused the distributed information and then indicate a path for the robot. Experiments showed that the wireless sensor network can result in obstacle avoidance navigation, and can implement the online navigation.


2014 ◽  
Vol 538 ◽  
pp. 502-507
Author(s):  
Jiang Shan Ai ◽  
Xiao Hong Chen

For accomplishing acoustic location in wireless sensor networks (WSNs), a range free acoustic localization algorithm based on perpendicular bisector partition is proposed, taking into account of reducing computation complexity and reduce the interference of the background noise. Adopting a range free perpendicular bisector partition, the proposed method can find the sub-region of the source, and the time complexity is much lower than that of existing methods. According to extensive analysis on noise, the concept of noise sensitive region is derived. Experimental results show that the proposed method has a high localization precision and low complexity.


Author(s):  
Shwe Myint ◽  
Warit Wichakool

This paper presents a single ended faulted phase-based traveling wave fault localization algorithm for loop distribution grids which is that the sensor can get many reflected signals from the fault point to face the complexity of localization. This localization algorithm uses a band pass filter to remove noise from the corrupted signal. The arriving times of the faulted phase-based filtered signals can be obtained by using phase-modal and discrete wavelet transformations. The estimated fault distance can be calculated using the traveling wave method. The proposed algorithm presents detail level analysis using three detail levels coefficients. The proposed algorithm is tested with MATLAB simulation single line to ground fault in a 10 kV grounded loop distribution system. The simulation result shows that the faulted phase time delay can give better accuracy than using conventional time delays. The proposed algorithm can give fault distance estimation accuracy up to 99.7% with 30 dB contaminated signal-to-noise ratio (SNR) for the nearest lines from the measured terminal.


2013 ◽  
Vol 791-793 ◽  
pp. 1368-1372
Author(s):  
Cheng Dong Wu ◽  
Zhao Li ◽  
Yun Zhou Zhang

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs) which are based on the transmission of ultrasonic signals and proposed for indoor positioning of mobile robots. In this paper we propose an improved auto-localization algorithm based on weighted least squares (WLS). The improved algorithm depends on the different error estimations which caused by the different relative positions of the beacons and the measurements nodes. Simulation results show that our WLS-based Linearized Auto-Localization Algorithm can provide improved accuracy in both distance estimation and position estimation.


2018 ◽  
Vol 14 (01) ◽  
pp. 29
Author(s):  
Wu Chunxiang

To overcome the low accuracy and high energy consumption of positioning algorithm in wireless sensor network, we proposed a optimization positioning based on algorithm neighborhood model. Based on the characteristics of the neighborhood model, the algorithm selects the best beacon node and calculates the proximity distance to transmit the distance information to the base station. The base station uses the MDS-MAP algorithm to determine the location of the unknown node. The simulation was conducted on NS-2 platform. The results show that the performance of the proposed algorithm was better than traditional optimization algorithms. Significant enhancement is obtained with the proposed algorithm in terms of node distance estimation error and position error.


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