3D Localization and Error Minimization in Underwater Sensor Networks

Abstract

Wireless sensor networks (WSNs) consist of nodes distributed in the region of interest (ROI) that forward collected data to the sink. The node’s location plays a vital role in data forwarding to enhance network efficiency by reducing the packet drop rate and energy consumption. WSN scenarios, such as tracking, smart cities, and agriculture applications, require location details to accomplish the objective. Assuming a 3D application space, a combination of received signal strength (RSS) and time of arrival (TOA) can be helpful for reliable range estimation of nodes. Notably, the anchor node can minimize localization error for non-line-of-sight (NLOS) signals. We proposed an error minimization protocol for localization of the sensor node, assuming that the anchor node’s location is known prior and can limit the receiving signal in LOS, single, or twice reflection. We start to exploit the sensor node’s geometrical relationship and the anchor node for LOS and NLOS signals and address misclassification. We started initially from the erroneous node position, bound its volume in 3D space, and reduced volume with each iteration following the constraint. Our simulation result outperforms the traditional methods on many occasions, such as boundary volume and computational complexity.