Research On RSSI-based Wireless Sensor Networks Localization Algorithm

Wireless sensor networks are a kind of new information processing platform equipped with sensing, computing and communication ability. They are widely applied to many fields such as national defense, environmental monitoring, traffic control and medical treatment. Sensor node localization is the base and prerequisite for most applications. In Recent years, many academies and industries have been making an in-depth research on sensor node localization technologies. This thesis has studied the the main technologies of node localization in wireless sensor networks, mainly including physical measurement, geometrical restriction acquisition, node coordinate solution, and the analysis on model parameters and experimental result errors. This thesis makes the following innovations:1. A novel distance estimating method using RSSI (Received Signal Strength Indicator) is proposed. The relationships of the distances between communicatable node paires are deduced by empirical radio propagation model without the path loss exponent. The communication range is used to estimate the distances between communicable paired nodes.2. Based on distance estimaton method, two RSSI-based centralized localization algorithms, RSSI-NLP (Received Signal Strength Indicator-Nonlinear Programming) and RSSI-LP (Received Signal Strength Indicator-Linear Programming) are proposed. The estimated distances are modeled as a set of geometrical constraints. A global solution of a nonlinear or linear optimization problem for these constraints yields estimations for the unknown node positions. Experimental results show that these algorithms have preferable localization accuracy when the anchors are placed on the fringe of the networks. Some analyses are made to validate the influences of anchor distribution, the number of anchors, and connectivity in localization error.3. A broadcast-answer mechanism for topology discovery in unknown wireless sensor netwoks is proposed. Its communication traffic is only O(n~2). And arbitrary edge of the wireless sensor networks can be discovered within O(n) time complexity.4. A clustering algorithm based on topology sensing is proposed. This algorithm can be used in distributed localization in wireless sensor networks. The sensing region of a planar network is divided into several sub-areas by the anchor nodes according to their geographical positions, which are all known. Anchor nodes implement the perception to their surrounding network topology through discovering topologies and communicating among themselves. According to the principle of proximity, each unknown node is assigned into a cluster. And the anchor nodes are at the fringe of each cluster. The main node of each cluster saves all the topology informations and RSSIs in the cluster. This algorithm can implement n-hop nodes clustering. 5. Based on the clustering algorithm, a distributed RSSI-LP localization method is proposed. The main node of each cluster runs the RSSI-LP algorithm with the saved topology informations and RSSIs in the cluster. Simulation results show that the distributed RSSI-LP performs well when the anchor nodes placed on the grid or randomly. The distributed method reduces the traffic and computational complexity, and is suitable for large-scale networks.6. The errors produced in wireless sensor networks localization algorithm are analyzed in detail. The errors in every method are divided into three types: distance estimation errors, position computational errors, and the localization algorithm errors. The geographic distribution, correlation, and probability distribution of the localization errors are analysed in several experiments.Based on MatlabR2007a, this thesis has simulated all the models and methods above, and analysed the results detailly.