Study On Displacement Monitoring Method Using GPS Based On Wireless Sensor Networks

GPS technology has lots of advantages such as fast speed,all-weather operation,high degree of automation and high positioning accuracy,which has been rapidly deployed in the field of structural health monitoring.However,the error analysis,data processing and other issues have limited the widespread application of this technology.On the other hand,the wireless sensor network has gradually become a new technology in the development of structural health monitoring disciplines,and begun to be applied in large complex monitoring system.The unique advantage of wireless sensor networks is that all intelligent sensor nodes collaborate in real time to accomplish complex tasks such as signal sensing and data processing analysis,thus providing a potential way to comprehensively utilize monitoring information and improve measurement precision.In order to enhance GPS measurement,this paper analyzes the differential GPS measurement mechanism and discusses its error influencing factors first.Then,a denoising method based on lifting wavelet transform is proposed to minimize the measurement error of GPS.At last,with the aid of signal localization technique of wireless sensor network(WSN)a new hybrid WSN/GPS displacement monitoring method is proposed,and the feasibility of the method is verified by real-world experiments.The main work and conclusions of this paper are as follows:This paper briefly summarizes the principle of existing carrier phase difference technique,and analyzes the influencing factors of GPS error in displacement monitoring,specifically for the cases of multipath and random noise.A series of displacement error are obtained by simulating different GPS monitoring environments.Results show that the multipath effect has significant effect on GPS measurement accuracy.Based on the analysis of deformation characteristics and error characteristics of GPS deformation monitoring system,a lifting wavelet is constructed due to its excellent time-frequency and multi-resolution characteristics.The filtering denoising of deformation observation sequence data is realized by programming.The denoising effect of the GPS measurement signal,and the effective data smoothing capability are verified by a numerical simulation study.In order to enhance the GPS measurement accuracy,this paper also analyzes the characteristics of the Received Signal Strength Indicator(RSSI)of wireless sensornetworks the GPS monitoring technology.Extend Kalman Filter(EKF)is selected as the information fusion method.Simulation results show that EKF algorithm can effectively achieve RSSI/GPS positioning data fusion,through which the positioning data accuracy has been improved.Furthermore,an EKF algorithm based on lifting wavelet transform is proposed to overcome the shortcomings of traditional EKF algorithm.Results show that the EKF fusion algorithm based on lifting wavelet can obtain more accurate positioning data.In order to verify the data fusion algorithm proposed in this paper,a verification experiment is designed and performed.Experimental results show that the comprehensive utilization of GPS technology and WSN signal localization is a feasible and effective displacement monitoring method,which is potential to be applied for displacement monitoring in the future.