Unmanned aerial vehicle attitude calculation method and system based on least square method and EKF

Abstract

The invention discloses an unmanned aerial vehicle attitude calculation method and system based on a least square method and an EKF. The method comprises the following steps: S100, collecting the state parameter values, including an angular velocity value and a linear acceleration value, of the flight state of an unmanned aerial vehicle based on an IMU data sensor; S200, performing fitting and interpolation calculation on the angular velocity value and the linear acceleration value based on a least square method, and establishing a state-space equation about the angular velocity and the acceleration; and S300, importing the IMU data subjected to least square method calculation processing into an extended Kalman filtering algorithm module, and carrying out attitude calculation on the attitude of the unmanned aerial vehicle. Based on the angular velocity value and the acceleration value processed by the least square method, the state-space equation and a measurement equation about the angular velocity and the acceleration are established, an attitude estimation module is established through an extended Kalman filtering algorithm theory based on the equations and a corresponding Jacobian matrix, and attitude calculation is performed on the attitude of the unmanned aerial vehicle, so the influence of noise and abrupt change values in the data on the accuracy and stability of attitude calculation is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicles, in particular to a method and system for unmanned aerial vehicle attitude calculation based on the least square method and EKF. Background technique [0002] A drone is an aircraft that does not contain manned functions and is controlled by radio or controlled by its own program. The wide application in the fields of plant protection, military and geological exploration is inseparable from a flight control algorithm with good stability and high precision. The flight control algorithm mainly includes three major algorithm modules: strapdown inertial navigation system, Kalman filter algorithm and flight control PID. The quality of the algorithm is the key to whether it can achieve stable flight. Among them, the Kalman filter algorithm is based on the IMU module, GPS and wind flow meter to complete the state parameter estimation of the UAV. In the state estimation, the attitude sol...

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Problems solved by technology

[0005] A method and system for unmanned aerial vehicle attitude calculation based on the least squares method and EKF proposed by the present invention can solve the related problems of noise and non-smoothness in the data in the attitude calculation, thereby improving the stability of the flight state of the unmanned aerial vehicle and stable performance, promote the development and popularization of drones

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