Investigation on Node Localization and Network Coverage in Wireless Sensor Networks
|School||Nanjing University of Technology and Engineering|
|Course||Communication and Information System|
|Keywords||wireless sensor networks (WSN) node localization network coverage ultra wideband (UWB) DV-Hop accumulative error Ineffective sensor node (InESN) node deployment node selection|
Wireless sensor network (WSN) is a newly-developed distributed system for information sensing and processing. The network integrates various techniques from the areas of MEMS, smart sensors, embedded computing, wirless communications and distributed information processing, and has great application potentials in military, medical treatment, business and environment monitoring and so on.WSN consists of a large amount of sensor nodes which have sensing, computing and communication capabilities. Among various application researches, the sensor node localization and the network coverage are two support techniques. The node localization is the premiss for practical applications and its accuracy is one of important performance criteria. The network coverage defines the service area supported by WSNs and affects the network costs and application performance. In the WSN design, the network coverage problem sould be firstly involved in.This dissertation conducts researches in the node localization and network coverage techniques. In the node localization, range-based localization, range-free localization and incremental localization techniques are deeply studied. In the network coverage, static network coverage and mobile network coverage are separately investigated.The main works in the dissertation are summarized as follows:1. Study on the range-based localization and range-free localization techniques(1) An UWB-based time-of-arrival (TOA) distance-measuring method is presented for the the range-based localization. The UWB signal has large bandwidth and high distance-measuring accuracy. However, in the application of the node localization, it is difficult to detect direct-path UWB signal. The dissertation proposes to calculate the TOA of the direct-path signal by weighting the TOAs of the first-path singal and the strongest-path signal. The weighting coefficients are obtained through fuzzy logic techniques. Simulation experiments with real data show the UWB-based technique can greatly enhance the localization accuracy.(2) Typical DV-Hop algorithm is improved for the range-free localization techniques. The DV-Hop algorithm performs well in isotropic density sensor network, however, it has larger location errors in randomly distributed networks. According to the localization principle of the DV-Hop algorithm, this dissertation proposes three improvements including the estimation of average single hop distance, the calculation of distance between unknown nodes and reference nodes and the estimation of node positions. These improvements can be used independently or jointly to replace the corresponding steps in the DV-Hop algorithm. The theoretic and simulation results show that the proposed improvements can greatly enhance the localization accuracy of the unknown nodes. In addition, the proposed schemes do not change the localization process of the DV-Hop algorithm, and hence they need no further communication resource and additional hardware requirement.2. Study on the incremental localization techniques(1) After thorough analyses on the incremental localization techniques, it is poined out that there are the accumulative errors and inefficient sensor node (InESN) problems in the techniques.(2) The effects of the errors on localization accuracy are firstly revealed. Then an improved incremental localization algorithm is proposed to reduce the accumulative errors. The basic idea behind the proposed algorithm is to reduce the error propagation by using the constraints on the distances between the unknown nodes and the most accurate nodes in previously known nodes. The simulation results confirm that this method can significantly reduce the accumulative errors of the incremental localization algorithm, and thus enhance the localization accuracy.(3) The InESN is defined and its existing characteristics are analysed. The InESNs are classified into three categories. With a moving target in the WSN and the link information between the InESN and known nodes, a constrained least-squares formulation is developed for estimating the InESNs. Numerical evaluations are carried out to examine the performance of the proposed method and show that it is indeed effective for locating the InESNs. By incorporating the InESNs in the tracking applications, the performance of the target tracking can be greatly enhanced.3. Study on the network coverage techniques(1) For the static network coverage, the network 1-coverage has acquired wide attention. The dissertation achives the network k (≥3) -coverage with new strategies onnode deployment and on the adjustment of node sensing radii. The strategies are suitable for deterministic coverage and random coverage, separatelly. For the network dynamic coverage, an energy-efficient selection of local nodes is presented, which greatly reduces the information exchanges with the neighbor nodes and center node and saves the network energy. (2) For the mobile network coverage, an optimal node distribution is proposed, which can enhance the performance on the target localization.