scholarly journals Iterative Positioning Algorithm for Indoor Node Based on Distance Correction in WSNs

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4871 ◽  
Author(s):  
Jing Chen ◽  
Shixin Wang ◽  
Mingsan Ouyang ◽  
Yuting Xuan ◽  
Kuan-Ching Li
Keyword(s):  
Distance Distribution ◽  
Distribution Model ◽  
Localization Algorithm ◽  
Target Node ◽  
Positioning Accuracy ◽  
Position Information ◽  
Deviation Coefficient ◽  
Positioning Algorithm ◽  
Distance Deviation ◽  
Distance Correction

Node position information is critical in wireless sensor networks (WSN). However, existing positioning algorithms commonly have the issue of low positioning accuracy due to noise interferences in communication. Hence, proposed in this paper is an iterative positioning algorithm based on distance correction to improve the positioning accuracy of target nodes in WSNs, with contributions including (1) a log-distance distribution model of received signal strength indication (RSSI) ranging which is built and from which is derived a noise impact factor based on the model, (2) the initial position coordinates of the target node obtained using a triangle centroid localization algorithm, via which the distance deviation coefficient under the influence of noise is calculated, and (3) the ratio of the distance measured by the log-distance distribution model to the median distance deviation coefficient which is taken as the new distance between the target node and the anchor node. Based on the new distance, the triangular centroid positioning algorithm is applied to calculate the coordinates of the target node, after which the iterative positioning model is constructed and the distance deviation coefficient updated repeatedly to update the positioning result until the criteria of iterations are reached. Experiment results show that the proposed iterative positioning algorithm is promising and effectively improves positioning accuracy.

scholarly journals Iterative Positioning Algorithm of the Target Node Based on Distance Correction in WSN

2019 ◽  
Author(s):  
Jing Chen ◽  
Shixin Wang ◽  
Mingsan Ouyang ◽  
Yudi Chen ◽  
Yuting Xuan
Keyword(s):  
Initial Position ◽  
Distribution Model ◽  
Localization Algorithm ◽  
Target Node ◽  
Positioning Accuracy ◽  
Position Information ◽  
Deviation Coefficient ◽  
Positioning Algorithm ◽  
Distance Deviation ◽  
Distance Correction

The node position information is critical in the wireless sensor network (WSN). However, the existing positioning algorithms commonly have low positioning accuracy because of noise interferences in communication. To solve this problem, this paper presents an iterative positioning model based on distance correction to improve the positioning accuracy of the target node in WSN. First, the log-distance distribution model of received signal strength indication (RSSI) ranging is built and the noise impact factor is derived based on the model. Second, the initial position coordinates of the target node are obtained based on the triangle centroid localization algorithm, thereby calculating the distance deviation coefficient under the influence of noise. Then, the ratio of the distance measured by the log-normal distribution model to the median distance deviation coefficient is taken as the new distance between the anchor node and the target node. Based on the new distance, the triangular centroid positioning algorithm is used again to calculate the target node coordinates. Finally, the iterative positioning model is constructed, and the distance deviation coefficient is updated repeatedly to update the positioning result until the set number of iterations is reached. Experiment results show that the proposed iterative positioning model can improve positioning accuracy effectively.

A Localization Algorithm Research to Eliminate the Indoor NLOS Error

2014 ◽  
Vol 989-994 ◽  
pp. 2232-2236 ◽  
Author(s):  
Jia Zhi Dong ◽  
Yu Wen Wang ◽  
Feng Wei ◽  
Jiang Yu
Keyword(s):  
Indoor Environment ◽  
Arrival Time ◽  
Channel Model ◽  
Indoor Positioning ◽  
Superior Performance ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Software Simulation ◽  
Positioning Algorithm

Currently, there is an urgent need for indoor positioning technology. Considering the complexity of indoor environment, this paper proposes a new positioning algorithm (N-CHAN) via the analysis of the error of arrival time positioning (TOA) and the channels of S-V model. It overcomes an obvious shortcoming that the accuracy of traditional CHAN algorithm effected by no-line-of-sight (NLOS). Finally, though MATLAB software simulation, we prove that N-CHAN’s superior performance in NLOS in the S-V channel model, which has a positioning accuracy of centimeter-level and can effectively eliminate the influence of NLOS error on positioning accuracy. Moreover, the N-CHAN can effectively improve the positioning accuracy of the system, especially in the conditions of larger NLOS error.

scholarly journals NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2991 ◽  
Author(s):  
Jingyu Hua ◽  
Yejia Yin ◽  
Weidang Lu ◽  
Yu Zhang ◽  
Feng Li
Keyword(s):  
Hypothesis Test ◽  
Intermediate Position ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Positioning Algorithm ◽  
Non Line Of Sight

The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.

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 An Indoor Robust Localization Algorithm Based on Data Association Technique

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6598
Author(s):  
Long Cheng ◽  
Yong Wang ◽  
Mingkun Xue ◽  
Yangyang Bi
Keyword(s):  
Hypothesis Testing ◽  
Indoor Localization ◽  
Likelihood Estimation ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Position Information ◽  
Position Estimate

As a key technology of the Internet of Things, wireless sensor network (WSN) has been used widely in indoor localization systems. However, when the sensor is transmitting signals, it is affected by the non-line-of-sight (NLOS) transmission, and the accuracy of the positioning result is decreased. Therefore, solving the problem of NLOS positioning has become a major focus for indoor positioning. This paper focuses on solving the problem of NLOS transmission that reduces positioning accuracy in indoor positioning. We divided the anchor nodes into several groups and obtained the position information of the target node for each group through the maximum likelihood estimation (MLE). By identifying the NLOS method, a part of the position estimates polluted by NLOS transmission was discarded. For the position estimates that passed the hypothesis testing, a corresponding poly-probability matrix was established, and the probability of each position estimate from line-of-sight (LOS) and NLOS was calculated. The position of the target was obtained by combining the probability with the position estimate. In addition, we also considered the case where there was no continuous position estimation through hypothesis testing and through the NLOS tracking method to avoid positioning errors. Simulation and experimental results show that the algorithm proposed has higher positioning accuracy and higher robustness than other algorithms.

scholarly journals RMLNet—A Reliable Wireless Network for a Multiarea TDOA-Based Localization System

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4374
Author(s):  
Yuan Xue ◽  
Wei Su ◽  
Dong Yang ◽  
Hongchao Wang ◽  
Weiting Zhang
Keyword(s):  
Multipath Propagation ◽  
High Rate ◽  
Target Area ◽  
Indoor Environments ◽  
Localization Algorithm ◽  
Mobile Nodes ◽  
Target Node ◽  
Position Information ◽  
Precise Position ◽  
Localization System

Ultrawideband (UWB) wireless communication is a promising spread-spectrum technology for accurate localization among devices characterized by a low transmission power, a high rate and immunity to multipath propagation. The accurately of the clock synchronization algorithm and the time-difference-of-arrival (TDOA) localization algorithm provide precise position information of mobile nodes with centimeter-level accuracy for the UWB localization system. However, the reliability of target node localization for multi-area localization remains a subject of research. Especially for dynamic and harsh indoor environments, an effective scheme among competing target nodes for localization due to the scarcity of radio resources remains a challenge. In this paper, we present RMLNet, an approach focus on the medium access control (MAC) layer, which guarantees general localization application reliability on multi-area localization. Specifically, the design requires specific and optimized solutions for managing and coordinating multiple anchor nodes. In addition, an approach for target area determination is proposed, which can approximately determine the region of the target node by the received signal strength indication (RSSI), to support RMLNet. Furthermore, we implement the system to estimate the localization of the target node and evaluate its performance in practice. Experiments and simulations show that RMLNet can achieve localization application reliability multi-area localization with a better localization performance of competing target nodes.

An Improved RSSI Positioning Algorithm Based on Reference Distances

2014 ◽  
Vol 971-973 ◽  
pp. 1547-1552 ◽  
Author(s):  
Yun Feng Leng ◽  
Hai Ping Zhu ◽  
Talal Alsharari ◽  
Fei He
Keyword(s):  
Indoor Localization ◽  
Signal Strength ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Anchor Nodes ◽  
Reference Distance ◽  
Fluctuation Amplitude ◽  
Positioning Algorithm ◽  
Mean Filtering

Due to the fluctuation of RSSI (Received Signal Strength Indicator) value, the positioning accuracy of indoor localization algorithm that based on RSSI value is not high and unstable, RSSI filtering and reference distance used in this paper. Fluctuation amplitude of RSSI is reduced by mean filtering, and a known distance between anchor nodes introduced when calculating the unknown distance between blind node and anchor node. According to the result of experiment, the positioning accuracy of new localization algorithm can reach 1.45 meter, and it can meet the demand of indoor positioning.

scholarly journals Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2400
Author(s):  
Ziyong Zhang ◽  
Xiaoling Xu ◽  
Jinqiang Cui ◽  
Wei Meng
Keyword(s):  
Quadratic Programming ◽  
Wide Band ◽  
Area Coverage ◽  
Localization Algorithm ◽  
Placement Problem ◽  
Position Information ◽  
Relative Localization ◽  
Coverage Control ◽  
Localization Algorithms ◽  
Multi Uav

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

Based on RSSI Ranging Technology for DV-Hop Localization Algorithm of Wireless Sensor Network

2012 ◽  
Vol 442 ◽  
pp. 360-365 ◽  
Author(s):  
Yang Jun Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Approximate Calculation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Original Algorithm ◽  
Approximate Distance ◽  
Anchor Nodes ◽  
Simulation Results

For the DV-Hop algorithm of wireless sensor networks,there is an error arising problem that anchor nodes and location node hop distance is only an approximate calculation. A method based on the original Algorithm introducing RSSI ranging technique is proposed.Using RSSI ranging technology,we accord that if the anchor nodes is only a hop away from the location node,then decide whether using the DV-Hop algorithm to approach to the approximate distance between them. Simulation results show that the algorithm can effectively improve the error problems of calculating the hop distance between the anchor nodes and the location nodes, meanwhile improve the positioning accuracy of the node.

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