scholarly journals Linear-regression-based Weighted Centroid Localization Algorithm in Wireless Sensor Network

2011 ◽  
Vol 15 ◽  
pp. 3068-3072 ◽  
Author(s):  
Hu Yu ◽  
Yao Weizhao
Keyword(s):  
Wireless Sensor Network ◽  
Linear Regression ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Weighted Centroid Localization

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.

Enhanced the Weighted Centroid Localization Algorithm Based on Received Strength Signal in Indoor Wireless Sensor Network

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Medhav Kumar Goonjur ◽  
◽  
Irfan Dwiguna Sumitra ◽  
Sri Supatmi ◽  
◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Maximum Error ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Scheme ◽  
Indoor Wireless ◽  
Anchor Nodes ◽  
Weighted Centroid Localization

A challenging problem that arises in the Wireless Sensor Network (WSN) is localization. It is essential for applications that need information about target positions, are inside an indoor environment. The Localization scheme presented in this experiment consists of four anchor nodes that change their position coordinates and one target node that is used to control the distance. The Localization algorithm designed in this paper makes use of the combination of two algorithms; the Received Strength Signal Indication (RSSI) and Weight Centroid Localization Algorithm (WCLA), called the RSSI-WCLA algorithm. The laboratory results show that the fusion between the RSSI-WCLA algorithm is outstanding than RSSI and WCLA algorithms itself in terms of localization accuracy. However, our proposed algorithm shows that the maximum error distance is less than 0.096m.

The Research on Magnetic Target Detection Technology Based on Wireless Sensor Network

2014 ◽  
Vol 644-650 ◽  
pp. 1213-1217
Author(s):  
Bo Zhou Hu ◽  
Meng Chun Pan ◽  
Peng Jiang ◽  
Wu Gang Tian ◽  
Jia Fei Hu ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Magnetic Anomaly ◽  
Experimental System ◽  
Magnetic Sensors ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Detection Technology ◽  
Weighted Centroid Localization ◽  
Magnetic Resistance

In the conditions of magnetic dipole model, this paper proposed forward a centroid localization algorithm on magnetic anomaly target based on wireless sensor network node which distribution are random and the improved the weighted centroid localization algorithm based on magnetic induction intensity. According to the fluctuation of magnetic field intensity which detected by magnetic sensors, that can detect the existence of magnetic anomaly target and its location. Established an experimental system of the wireless sensor network for magnetic anomaly detection whose core designs including the HMC1043 three-axis magnetic resistance sensor and the CC2530 Zigbee RF chip. The experimental results show that the algorithm can accurately positioning the magnetic anomaly target within the network.

scholarly journals V2X-Based Mobile Localization in 3D Wireless Sensor Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Iram Javed ◽  
Xianlun Tang ◽  
Kamran Shaukat ◽  
Muhammed Umer Sarwar ◽  
Talha Mahboob Alam ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Three Dimensional ◽  
Link Quality ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Position Information ◽  
Mobile Anchor ◽  
Anchor Nodes

In a wireless sensor network (WSN), node localization is a key requirement for many applications. The concept of mobile anchor-based localization is not a new concept; however, the localization of mobile anchor nodes gains much attention with the advancement in the Internet of Things (IoT) and electronic industry. In this paper, we present a range-free localization algorithm for sensors in a three-dimensional (3D) wireless sensor networks based on flying anchors. The nature of the algorithm is also suitable for vehicle localization as we are using the setup much similar to vehicle-to-infrastructure- (V2I-) based positioning algorithm. A multilayer C-shaped trajectory is chosen for the random walk of mobile anchor nodes equipped with a Global Positioning System (GPS) and broadcasts its location information over the sensing space. The mobile anchor nodes keep transmitting the beacon along with their position information to unknown nodes and select three further anchor nodes to form a triangle. The distance is then computed by the link quality induction against each anchor node that uses the centroid-based formula to compute the localization error. The simulation shows that the average localization error of our proposed system is 1.4 m with a standard deviation of 1.21 m. The geometrical computation of localization eliminated the use of extra hardware that avoids any direct communication between the sensors and is applicable for all types of network topologies.

Sign in / Sign up

Export Citation Format

Share Document