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GPS AND KALMAN FILTER INTEGRATION FOR APPLICATION IN AUTONOMOUS VEHICLES

机译:GPS和卡尔曼滤波集成在自主车辆中的应用

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In this paper a methodology for integration of a Kalman Filter and a Global Positioning System (GPS) is presented to estimate the position of an autonomous vehicle. To further improve the estimation of the position given by the integration of the GPS and the Kalman Filter, a fuzzy system (Kalman Fuzzy Tuner) is designed which notably reduce the RMSE of the position coordinates, i.e., latitude, altitude and longitude. Using experimental characterization of the position and error of the GPS and the equations of the Kalman filter, simulations are carried out to test the feasibility of the proposed integration. Simulation results showed better performance of KF-GPS with the Kalman Fuzzy Tuner.
机译:在本文中,提出了一种用于集成卡尔曼滤波器和全球定位系统(GPS)的方法,以估计自动驾驶汽车的位置。为了进一步改善由GPS和卡尔曼滤波器的集成给出的位置估计,设计了一种模糊系统(Kalman Fuzzy Tuner),该系统显着降低了位置坐标(即纬度,海拔和经度)的RMSE。利用GPS的位置和误差的实验特性以及Kalman滤波器的方程,进行了仿真,以验证所提出的集成的可行性。仿真结果表明,使用卡尔曼模糊调谐器可以更好地实现KF-GPS的性能。

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