Car Gps / Dr Integrated Positioning System Data Fusion

At the operational phase of demonstration of electric vehicles,it is necessary to develop electric vehicles monitoring terminals in order to facilitate the monitoring of electric vehicles, accumulate operating experience,and improve the performance of electric vehicles,which can help real-time monitoring of status parameters in the operation of electric vehicles,learn faults and conditions of vehicles,adjust the operating parameters of vehicles,and optimize the performance of electric vehicles.Car GPS navigation module is an integral part of monitoring terminal.Now widely used global positioning system are characterized with high speed positioning,high precision,the continuum of covering ground,and so on.But in the city full of high rises,it is because of shielding effect of multi-path problem that the positioning accuracy decreases and a lot of blind spots occur.Dead reckoning system(DR) makes use of traffic direction and distance information to calculate the instantaneous vehicle position without depending on external signals,which has autonomous positioning and navigation performance, though the inherent disadvantage of dead reckoning system is that the positioning errors are accumulated over time,and a separate system of dead reckoning cannot be used for poisoning for long.With the combination of these two systems,GPS and DR can complement each other to achieve better positioning effect.The core of its portfolio multi-sensor data fusion algorithms, united with Kalman filtering algorithm,can make use of the principle of information distribution, to implement optimal generalization multi-sensor information,make the whole system not only has high accuracy but also has a certain degree of fault-tolerant capability,thus the overall on the optimal performance.Focusing on the Kalman filter data fusion algorithm,this article derives the standard Kalman filter mathematical model(state equation and measurement equation) for the GPS system according to the standard linear system Kalman filter equations;it derives the expansion of the Kalman filter mathematical model(state equation and measurement equation) for the DR system according to the extended Kalman filter equations of nonlinear systems.United Kalman filter is designed for two types of GPS and DR data fusion system,and the use of the location of machine precision(PDOP) provided by GPS receivers fusion coefficient can be designed to adjust the adaptive data fusion program and derive the optimal position estimates after both the data integration system.Of the United Kalman filter designed for the computer simulation, simulation results show that:the application of the United Self-adaptive Kalman filter can significantly improve vehicle GPS / DR Integrated Positioning System positioning accuracy and fault tolerance,can also achieve real-time,accurate,all-weather,continuous positioning of the target.Finally,this article gives a design at the hardware implementation of surveillance terminal board and the software design.