Research Of Dam Danger Location Determination Algorithm Based On Bayesian Filtering And Rssi Ranging

Since the founding, different sizes of dams were built more than ninety thousand in ourcountry, dam would appear different security risks with an extension of using time, needconduct long-term, effective safety monitoring to achieve maintenance. Dam environmentdetermines the harsh environmental monitoring, with the development of sensor technology,wireless communication technology and embedded technology, using wireless sensor networktechnology for monitoring the dam has become a hot research, in which positioning thedangerous condition location of the dam timely and accurate is one of the core content of thestudy.Advantage of the flexibility, low power consumption and economy for wireless sensornetworks cause the disadvantage is equally clear, Nodes’ energy, computing power andstorage capacity constraints of the accuracy of positioning, the environment of dam safetymonitoring is relatively complex, need to fully take into account the interference of ambientnoise and human factors.This article through the scope and the advantages and disadvantages of eachmeasurement method to research and compare, chosen RSSI as the ranging method forpositioning, in order to ensure the accuracy of signal strength samples, proposed Bayesianstatistical filtering to improve the accuracy of positioning, to meet measurement accuracywithout additional hardware cost. On the basis of existing research results, conduct theresearch of dam danger location determination algorithm based on Bayesian filtering andRSSI ranging, main analyze the impact of the positioning accuracy of two main factors:ranging errors and calculation errors, and its main results are as follows:1.Ranging error terms: Analysis the factors that influence ranging accuracy of RSSI Inthe dangerous condition of the dam safety monitoring positioning and establish wirelesschannel loss model. Since the RSSI sampling own randomness and other characteristics, needto conduct gaussian filter for RSSI sampling to improve the accuracy of sampling and reducerange error;2. Calculation error terms: Analysis the impact on calculation error by triangle centroidalgorithm and the weighted three horny heart algorithm, propose the method of using Bayesian filtering principle to improve the accuracy, reduce the calculation error.