Improved Grid-Scan Localization Algorithm for Wireless Sensor Networks

Localization is a fundamental and crucial service for various applications in wireless sensor networks (WSNs). In this paper an improved grid-scan localization algorithm has been proposed. In the proposed algorithm, information about 1-hop, 2-hop, and farther neighboring anchors has been collected that estimates the region using 1-hop anchors. Then, this estimated region is divided into a grid array, finding valid grids using 1-hop and 2-hop anchors information. In addition to that the farther anchor information further reduces the valid grids. The proposed algorithm achieves better location estimation accuracy than the existing grid-scan algorithm. 1. Introduction A wireless sensor network (WSN) consists of a number of randomly arranged sensor nodes. Each sensor node is capable of sensing and communicating with another sensor node in the designed communication range. In WSNs some sensor nodes have prior knowledge about their location which can be obtained from hardware connected to such nodes. These nodes are known as anchor nodes. The hardware may also be a GPS system. The sensor nodes which do not have knowledge about their location are called normal nodes. Some of the applications of such WSNs are vehicle tracking, target tracking, wildlife habitat monitoring, and disaster management. These applications without the knowledge of the location are absurd. One of the methods to obtain the location of a normal node is to connect the hardware to it. The WSNs consist of several hundreds of sensor nodes. Hence, the overall cost of WSNs increases. In some places GPS system cannot be operated such as mines and indoor environment as there is a problem in communication. To overcome the above problems several localization algorithms were proposed. Localization algorithms are classified into two categories: range-based algorithms and range-free algorithms. The range-based algorithms estimate the coordinates of nodes from pairwise distances using special hardware. This hardware is used to measure angle of arrival (AOA) [1], time of arrival (TOA) [2], time of difference arrival (TDOA) [3], received signal strength indicator (RSSI) [4], and so forth. The calculation of distance or angle can be affected by multipath propagation and noise. Moreover, these algorithms need additional devices to measure the angle or distance between sensor nodes. In range-free algorithms, the localization between normal nodes is obtained through connectivity with the neighboring sensors which do not require any additional hardware. This significantly reduces the overall cost and energy