In this study, unlike other approaches, the major breakthrough is that we can achieve accurate localization of sensor nodes solely using omnidirectional antenna even if only one reference node exists. Besides, we can be benefit from the advantages of using omnidirectional antennas, e.g., low-cost (simplicity) and easy deployment (efficiency).In this work, a robust correlation is incorporated in analyzing the relative positions between two sensor nodes using the received signal strength indication (RSSI) pattern. A cooperative localization scheme is also developed to improve the accuracy of the estimation as multiple reference nodes are available. The performance of the proposed framework has been evaluated by computer simulations and real world experiments under various experimental conditions.
The rest of this paper is organized as follows: Section 2 describes the definition of localization problems in WSNs, including network configuration, a pair of customized antenna modules, an azimuth dependent radio power model, and RSSI patterns. Section 3 presents the modified robust correlation to provide a better metric for matching RSSI patterns. Section 4 provides the collaborative localization scheme for precise localization. Experimental results yielded by computer simulation and field test are reported in Section 5. Finally, the discussion and conclusion are given in the last section.2.?Problem Formulation2.1.
Network ConfigurationSuppose a WSN is composed of sensor nodes and reference nodes that are deployed in a given sensing field.
The objective of this study is to provide accurate location information of Entinostat the sensor nodes in WSNs. The coordinates of the reference nodes are assumed known a priori. The location of the sensor node is estimated based on the measurements of nearby reference nodes. In this study, we focus on WSNs formed by a number of reference nodes that Dacomitinib can estimate the locations of a given set of sensor nodes. Thus, we represent the network by the Euclidean graph G = (V, E), as depicted in Figure 1, with the following properties: V is a set of nodes in the network, and V = S, R; S is a set of sensor nodes equipped with RSSI sensors, and S = s1, s2, ��, snum_S; R is a set of reference nodes equipped with servomotor-controlled external antennas, and R = r1, r2, ��, rnum_R.
num_S is the number of sensor nodes; and num_R is the number of reference nodes. Sensor nodes S of the network do not know their location information. Physical positions of R are obtained by manual placement or external means. These nodes are the basis of the localization system.
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