Improved Weighted Centroid Localization with Quadratic Means for Indoor Mobile Robot Tracking

2015 ◽  
Vol 781 ◽  
pp. 441-444
Author(s):  
Jirapat Sangthong ◽  
Kantaphon Torat ◽  
Sathaporn Promwong
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Indoor Mobile Robot ◽  
Robot Tracking ◽  
Weighted Centroid Localization ◽  
The One ◽  
Range Free

Nowadays, mobile robot tracking is the one of application in wireless sensor networks (WSNs). A one of promising localization algorithm in range-free algorithm is the weighted centroid localization (WCL) algorithm. This work proposed the improved WCL algorithm with quadratic means based on received signal strength (RSS). The ZigBee operated at 2.4 GHz frequency is used to measure in the indoor environment. The final results will be discuss about the comparison of the typically WCL algorithm and the improved WCL algorithm. From the results, the 1-meter-precision of improved WCL is 91.67% and WCL is 83.33%. Moreover, the improved WCL obtained the 16.67% no error of estimated position.

A Localization Algorithm for Wireless Sensor Network Based on the Weighted Correction in Geometric Measurement

2015 ◽  
Vol 740 ◽  
pp. 823-829
Author(s):  
Meng Long Cao ◽  
Chong Xin Yang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Localization Algorithms ◽  
Weighted Centroid Localization ◽  
Geometric Measurement

Firstly, the characteristics of regular Zigbee localization algorithms-the received signal strength indicator algorithm (RSSI) and the weighted centroid localization algorithm are introduced. Then, the factors of the errors existing in the aforementioned algorithms are analyzed. Based on these above, the improved RSSI algorithm-correction geometric measurement based on weighted is proposed. Finally, utilizing this algorithm to design and implement the localization nodes, which have the CC2431 wireless microcontroller on them. The simulation and experimental results show that the accuracy of this localization algorithm improved about 2%, comparing with the regular algorithms.

An Improved Weighted Centroid Localization Algorithm Based on RSSI

2014 ◽  
Vol 989-994 ◽  
pp. 1574-1577 ◽  
Author(s):  
Chang Liang Liu ◽  
Zhe Li
Keyword(s):  
Safety Management ◽  
Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Precise Positioning ◽  
Centroid Algorithm ◽  
Traditional Algorithm ◽  
Weighted Centroid Localization ◽  
Positioning Algorithm

In wireless sensor networks, the precise positioning of unknown nodes is the precondition and security for all kinds of applications. In this paper, by analyzing the present research status of personnel positioning algorithm and on the basis of the study of traditional centroid algorithm, an improved based on RSSI (Received Signal Strength Indicator) of the weighted centroid localization algorithm is proposed. The algorithm takes the signal intensity meanwhile the distance between the unknown nodes and beacon nodes as a reference to correct RSSI value. Through the simulation of the localization algorithm it proves that the improved localization algorithm has higher precision than the traditional algorithm. Once the accidents can be timely and efficient rescue for the underground staff, better meet the actual demand of safety management.

scholarly journals A Research Cluster based Scheme for Node Positioning in Indoor Environment

2019 ◽  
Vol 8 (6S) ◽  
pp. 79-83
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Cluster Head ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Localization Error ◽  
Network Efficiency

Location estimation in Wireless Sensor Network (WSN) is mandatory to achieve high network efficiency. Identifying the positions of sensors is an uphill task as monitoring nodes are involved in estimation and localization. Clustered Positioning for Indoor Environment (CPIE) is proposed for estimating the position of the sensors using a Cluster Head (CH) based mechanism. The CH estimates the number of neighbor nodes in each floor of the indoor environment. It sends the requests to the cluster members and the positions are estimated based on the Received Signal Strength Indicators (RSSIs) from the members of the cluster. The performance of the proposed scheme is analyzed for both stable and mobile conditions by varying the number of floors. Experimental results show that the propounded scheme offers better network efficiency and reduces delay and localization error

scholarly journals An RSSI-based Wireless Sensor Network Localization Algorithm with Error Checking and Correction

2017 ◽  
Vol 13 (12) ◽  
pp. 52 ◽  
Author(s):  
Bo Guan ◽  
Xin Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Anchor Node ◽  
Network Localization ◽  
Error Checking

<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper studies the wireless sensor network localization algorithm based on the received signal strength indicator (RSSI) in detail. Considering the large errors in ranging and localization of nodes made by the algorithm, this paper corrects and compensates the errors of the algorithm to improve the coordinate accuracy of the node. The improved node localization algorithm performs error checking and correction on the anchor node and the node to be measured, respectively so as to make the received signal strength value of the node to be measured closer to the real value. It corrects the weighting factor by using the measured distance between communication nodes to make the coordinate of the node to be measured more accurate. Then, it calculates the mean deviation of localization based on the anchor node close to the node to be measured and compensates the coordinate error. Through the simulation experiment, it is found that the new localization algorithm with error checking and correction proposed in this paper improves the localization accuracy by 5%-6% compared with the weighted centroid algorithm based on RSSI.</span></p>

scholarly journals Efficient range-free localization using elliptical distance correction in heterogeneous wireless sensor networks

2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875627 ◽  
Author(s):  
Wenlan Wu ◽  
Xianbin Wen ◽  
Haixia Xu ◽  
Liming Yuan ◽  
Qingxia Meng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Likelihood Estimation ◽  
Cumulative Distribution ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Heterogeneous Wireless Sensor Networks ◽  
Heterogeneous Wireless Sensor Network ◽  
Range Free ◽  
Distance Correction

In this article, a novel range-free localization algorithm is proposed based on the modified expected hop progress for heterogeneous wireless sensor networks where all nodes’ communication ranges are different. First, we construct the new cumulative distribution function expression of expected hop progress to reduce the computational complexity. Then, the elliptical distance correction method is used to improve the accuracy of the estimation distance and simultaneously decrease overhead. Finally, using the modified distance, the coordinate of the unknown node can be obtained by maximum likelihood estimation. Compared with other algorithms for heterogeneous wireless sensor network, the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes.

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