Study On Localization And Indoor Mapping Algorithm Of Wireless Sensor Network With Noises

Since the 1990 s,with the development of technologies such as sensor,microelectrnics and wireless communication technologies,wireless sensor network(WSN)has drawn great attention all over the world due to its immense application value.The wireless sensor network is composed of a large number of low-cost micro sensor nodes,which are deployed in the target area for specific monitoring target.WSN is widely used in military,transportation,environmental monitoring and other fields.Among them,the location of sensors and the information of indoor environment are crucial to the practical application of WSN.Therefore,localization technology and indoor mapping technology have become significant research direction,and how to deal with the impact of noises in the real environment on algorithms has become a major research hotspot.Based on the analysis of the application requirements of localization technology and indoor mapping technology,this paper mainly studies the localization and indoor mapping problems under noise.An improved method is proposed after analyzing the deficiency of the existing localization algorithm under noise.Considering that most of the existing WSN localization and indoor mapping algorithms are centralized algorithms with weak anti-noise ability,this thesis designs a novel approach for transforming the indoor mapping problem and a distributed solution under noise,including:1.Through analyzing the problem of ECHO-MN algorithm,a new calculation method of barycentric coordinate with measurement noise is proposed.Furthermore,an unbiased distance estimator is constructed to eliminate measurement noise.Based on the above discussion,this thesis develops a distributed localization algorithm under measurement noise called ROBLOCMN.Finally,the algorithm is verified from different aspects.The results show that the ROBLOC-MN algorithm is more robust than the ECHO-MN algorithm.Besides,the convergence speed of the algorithm is positively correlated with the sum of the attenuation coefficients tending to infinity.2.The localization and indoor mapping problem is transformed into pure localization problem by means of constructing virtual nodes,which are constructed by multi-path reflection signals of the nodes through the wall.Then,combined with the relevant conclusions in the literature,the positional conditions of the localization and indoor mapping problem are analyzed.Finally,based on existing localization algorithm,a distributed localization and indoor mapping algorithm called ROBLOCAM algorithm is proposed,and the effectiveness of the algorithm is verified by simulation.3.On the basis of combining the ROBLOC-MN localization algorithm with the indoor mapping method,this paper introduces the influence of quantization noise in digital communication into the problem.Thus,the localization and indoor mapping problem under measurement noise and communication noise is considered.Then the measurement noise processing method in the ROBLOC-MN algorithm is used to eliminate the influence of measurement noise.Furthermore,a dithered quantization method is provided for processing the quantization noise.Based on the previous analysis and discussion,a localization and indoor mapping algorithm with both types of noise named ROBLOCAM-CMN is proposed.Finally,the convergence of algorithm with both quantization error and distance error is validated by simulation.The simulation result reflects the robustness of the algorithm.