Path Planning for Mobile-Anchor Based Wireless Sensor Networks Localization: Obstacle-Presence Schemes

In many Wireless Sensor Network (WSN) applications, the location of the nodes in the network is required. A logical method to find Unknown Nodes (UNNs) in the network is to use one or several mobile anchors (MAs) equipped with GPS units moving between UNNs and periodically broadcast their current location. The main challenge at this stage is to design an optimum path to estimate the locations of UNNs as accurately as possible, reach all nodes in the network, and complete the localization process as quickly as possible. This article proposes a new path planning approach for MA-based localization called Nested Hexagon Curves (NHexCurves). The proposed model’s performance is compared with the performance of five existing static path planning models using Weighted Centroid Localization (WCL) and Accuracy Priority Trilateration (APT) localization techniques in the obstacle-presence scenario. With the obstacle-handling trajectories used for the models, the negative impact of the obstacle on the localization is reduced. The proposed model provides full coverage and high localization accuracy in the obstacle-presence scenario. The simulation results show the advantages of the proposed path planning model with the H-curve model over existing schemes.

Research on Underground Personnel Positioning Method Based on PSO-GSA Optimization

In the case of coal mine accidents, in order to ensure timely rescue of the suffering people in a complex environment of underground localization, focusing on Received Signal Strength Indicator (RSSI) in underground personnel positioning accuracy is low and the problem of dynamic tracing parameters changes. Therefore, using an improved gravitational search algorithm (GSA) for the weighted centroid localization that based on RSSI. Utilizing the log distance path loss model gets the distance between the beacon nodes and unknown nodes, and then through the weighted centroid localization algorithm perform the unknown node positioning. Finally, the improved GSA-PSO optimizes the preliminary location results and parameters. Proposed solutions to establish simulation model is verified in MATLAB, and use the on-chip system CC2430 chips experiment platform is established. Experimental results show the proposed method can improve both the positioning accuracy effectively and the adaptive ability of changeful environment.

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

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.