Research on the Optimization of Wireless Sensor Network Localization Based on Real-Time Estimation
Range-based localization of wireless sensor networks is to obtain sensory data for the calculation of the distance to the target. The positioning accuracy is directly affected by environmental factors. The major localization error of the traditional metho
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Research on the Optimization of Wireless Sensor Network Localization Based on Real-Time Estimation Xiancun Zhou, Mingxi Li and Fugui He
Abstract Range-based localization of wireless sensor networks is to obtain sensory data for the calculation of the distance to the target. The positioning accuracy is directly affected by environmental factors. The major localization error of the traditional methods will be made by the use of fixed parameters for the measurement of distance. In this chapter, we proposed a RSSI-based cooperative localization algorithm by adjusting the signal propagation model dynamically. The localization method was optimized and the triangular range localization method was taken as an example to verify the optimization result. From the simulation and experiment, we verify that the proposed algorithm can provide higher localization accuracy. Keywords Sensor network
Range-based localization RSSI
3.1 Introduction Target localization is one of the key application areas of sensor networks. For the application with strict requirements on target localization accuracy, range-based localization methods are practically adopted. The range-based localization methods commonly used include: RSSI (Received Signal Strength Indicator) [1], TOA (Time
X. Zhou (&) F. He School of Information Engineering, West Anhui University, lu’an, Anhui, China e-mail: [email protected] M. Li School of Computer Science, University of Science and Technology of China, Hefei, China e-mail: [email protected]
W. Lu et al. (eds.), Proceedings of the 2012 International Conference on Information Technology and Software Engineering, Lecture Notes in Electrical Engineering 210, DOI: 10.1007/978-3-642-34528-9_3, Ó Springer-Verlag Berlin Heidelberg 2013
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Of Arrival) [2], TDOA (Time Difference Of Arrival) [3], AOA (Angle Of Arrival) [4] and so on. Compared with other range-based localization methods, the localization methods based RSSI can simultaneously broadcast their own coordinates at beacon nodes and complete by the RSSI measurement. With the known transmit strength in RSSI, the receiving node calculates the signal losses in the communication process according to the received signal strength, and then transforms the propagation loss into distance with the theoretical or empirical signal propagation model. Currently, RSSI-based wireless sensor network localization algorithm provides various approaches to improve the accuracy of localization. In the literature [5], an algorithm proposed based on extended Kalman filter (EKF) to reduce error of target localization, but the method brings a lot of communication and computing cost. A RSSIbased self-localization algorithm is presented in the literature [6]. The algorithm performs well in localization accuracy when anchors are at the fringe of the networks. However, it increases work complexity of the anchor nodes layout and the burden of communication. Online correction method [7] can improve the environmental adaptability of the sensor network and es
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