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Evaluation of GPS Data for Navigational Solution and Error Reduction Using Kalman Filter

机译:利用卡尔曼滤波器评估GPS数据的导航解决方案和减少误差

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Now a day navigation system has been receiving a high demand for numerous applications. Among these systems global positioning system (GPS) is more popular which is frequently using for the aircraft for navigation and autonomous navigation purposes. However GPS suffers because of continuity and reliability problems in many applications. In this proposed model a novel architecture of kalman filter has been selected to integrate with GPS to overcome above problem. A software defined radio (SDR) is used for the GPS data extraction which is nothing but an analog to digital converter. The integrated GPS with kalman filter system can be able reduce velocity, position and attitude errors compared to the many conventional algorithms. To verify this technique a real time model is created using Simulink/Matlab. The simulated outcomes confirm the advantages of assimilated system in both urban and open areas and suitable for real time implementations.
机译:现在,一天导航系统已经收到了对众多应用程序的高需求。在这些系统中,全球定位系统(GPS)更为流行,它通常用于飞机的导航和自主导航目的。然而,由于许多应用中的连续性和可靠性问题,GPS遭受了损失。在该提出的模型中,已经选择了卡尔曼滤波器的新颖架构来与GPS集成以克服上述问题。 GPS数据提取使用软件无线电(SDR),它只是一个模数转换器。与许多传统算法相比,带有卡尔曼滤波系统的集成GPS可以减少速度,位置和姿态误差。为了验证该技术,使用Simulink / Matlab创建了实时模型。模拟结果证实了同化系统在城市和开放区域中的优势,并且适合实时实施。

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