Accurate distributed range-based positioning algorithm for wireless sensor networks
IEEE Transactions on Signal Processing
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Advances in the micro-electro-mechanical system and wireless communication technology have enabled researchers to develop large-scale wireless sensor networks with a large number of inexpensive and small sensors. Many applications are developed based on wireless sensor networks, such as habitat monitoring, navigation, and objects detection and tracking. By its nature, location awareness is indispensable for the implementation of these applications. In this dissertation, we study two issues related to sensor and object localization in wireless sensor networks. We first examine the sensor localization algorithms, which are used to determine sensors' positions in ad-hoc sensor networks. Most existing sensor localization methods suffer from various location estimation errors that result from ranging errors, complex network topologies and anisotropic terrain, etc. We explore the characteristics of dimensionality reduction techniques and propose three sensor localization algorithms based on the multidimensional scaling techniques. They include a centralized sensor localization algorithm, a distributed sensor localization algorithm, and a robust sensor location algorithm based on multidimensional scaling. The results of our experiment demonstrate that these algorithms are effective in positioning sensors. Positioning all sensors in a sensor network usually consumes a large amount of time and energy. In many applications based on sensor networks, there is no need to estimate the location of all sensors in a sensor network. Sometimes, only sensors within a given direction or region need to be located. We propose the concept of differentiated sensor localization. Three differentiated sensor localization methods are also proposed, which can selectively locate only one or a specific set of sensors. Given the sensor location information known, many surveillance tasks may then be carried out with sensor networks. One of the major applications of sensor networks is locating objects and tracking their movement. We investigate the problem of using large-scale sensor network to locate large continuous objects and track their boundary movement. The large continuous objects, such as wild fire and bio-chemical materials, are different from the traditional single or multiple discrete targets in that they are continuously distributed across a region and usually occupy a large area. Detecting and tracking the large continuous objects poses many challenging research issues which have not been adequately addressed in previous research. Capturing their spread and boundary information is usually an efficient approach for monitoring them. A distributed algorithm is proposed in this research to locate the boundary of continuous objects. A dynamic structure is proposed to track the movement of boundaries and to facilitate the fusion and dissemination of boundary information in a sensor network. Simulation results show the efficiency of the proposed algorithms.