Design And Implementation Of Indoor Navigation System Based On Adaptive Kalman Filter

With the development of science and technology,people's demand for location service is increasing rapidly in daily life.However,Global Position System could not perform normally in indoor environment,such as supermarket,underground garage and so on.To make up for the defects of GPS in indoor positioning,people usually choose indoor inertial navigation system as an alternative to GPS.But indoor environment has its unique complexity and variability;wearable device users also have distinct individual differences.Under these circumstances,the positioning accuracy of the indoor inertial navigation system will decline when sensors receive imprecise values coursed by environmental interference.Therefore,it is very important for indoor inertial navigation system to judge whether the sensor is interfered by the environmental interference and reduce the bias of the track location caused by the sensors' measurement error.The indoor inertial navigation system based on adaptive Kalman filter has been researched in this thesis.However,due to the lack of information on the external environment,the fixed process noise and observation noise are usually used in the extended Kalman filter.In this case,the accuracy loss caused by the sensor data error is easy to occur.In this thesis,through the analysis of the process data in the extended Kalman filter,the error analysis and modeling are carried out from two aspects of the walking length and the walking direction.The neural network algorithm is used in the training of extended Kalman filter noise model,so as to achieve the optimal model parameters for different individuals.The influence of individual difference and external environment disturbance on the accuracy of the model is reduced,in order to improve the positioning accuracy and anti-interference of the indoor inertial navigation system.The system structure of the embedded terminal-the host computer-server is adopted in this thesis,this structure has its own advantage is that the extensibility of the whole system is improved when the power consumption and design complexity of the embedded end are reduced.In the actual test,the error of the positioning error of the indoor inertial navigation system is less than 2 meters per 100 meters.Under the disturbance of external environment,the interference degree of trace is reduced by 30%-50%.The whole system responses quickly and meets the design expectations.In this thesis,an indoor inertial navigation system based on adaptive extended Kalman filter is realized.The system meets the design requirements in both function and performance.The system can track the dynamic trajectory of pedestrian walking indoors.The research results have certain engineering practical value for the application of the system of indoor inertial navigation and positioning technology.