CDKF 算法在四旋翼飞行器组合导航系统中应用

针对基于四旋翼无人飞行器的组合导航系统在小失准角情况下滤波器较短时间内发散的问题, 将中心差分卡尔曼滤波算法应用于低成本的组合导航系统中, 设计了飞行器组合导航系统的硬件电路。该系统采用MPU-6050 芯片作为飞行器姿态传感器, 选用u-Blox 公司的NEO-6M 模块获取GPS(Global Positioning System)信号, 并利用中心差分卡尔曼滤波算法实现多传感器的数据融合, 从而获取导航信息。在四旋翼无人飞行器平台上对该系统进行实验的结果表明, 该导航系统能有效抑制传感器噪声, 克服了陀螺仪的漂移现象, 避免了传统EKF((Extended Calman Filter) )算法近似程度不高, 易导致解算结果发散等问题的发生, 为飞行器提供了准确的导航信息。

CDKF Algorithm Applied to Quadrotor Integrated Navigation System

Considering the condition of filter divergence problem in a relatively short time caused by small misalignment angle, based on the quadrotor intergrated navigation system, the central difference of kalman filtering algorithm is applied to the low cost integrated navigation system. First this paper realizes the hardware circuit of quadrotor integrated navigation system, the MPU-6050 chip is used for the attitude sensor, choosing NEO-6M module from u-Blox company to get a GPS(College of Science) signal. Then the central difference of kalman filtering algorithm is used to realize the multi-sensor data fusion, and to get the navigation information.Finally the system can be applied to actual quadrotor platform for experiment. The results of the experiment show that the design of quadrotor integrated navigation system based on CDKF(Central Difference Kalman Filter) algorithm can effectively restrain the sensor noise, overcome the gyroscope drift phenomenon, avoid the shortcomings of traditional EKF(Extended Calman Filter) algorithm, and provide accurate navigation information for aircraft.