Attitude tilting angle estimation method suitable for precise operation of agricultural machine

Abstract

The invention discloses an attitude tilting angle estimation method suitable for precise operation of an agricultural machine. The attitude tilting angle estimation method comprises a self-adaptive Kalman filtering attitude fusion algorithm for estimating inherent zero offset of an MEMS (Micro-electromechanical System) gyroscope and an accelerometer and combining with a gyroscope second-order AR (Auto Regression) error model. The attitude tilting angle estimation method comprises the following steps: estimating measurement errors phierr1, phierr2, thetaerr1 and thetaerrr2 of an X-axis gyroscope and a Y-axis gyroscope by adopting an AR model to serve as state input quantities for Kalman filtering, and adaptively estimating a measurement error covariance matrix R; establishing a system external development Kalman filtering state equation and a measuring equation containing six state vectors and two observation vectors; adaptively adjusting a process error covariance matrix Q by means of a space geometric model of a triaxial accelerometer. According to the attitude tilting angle estimation method disclosed by the invention, the inherent zero offset of the gyroscope and the accelerometer is considered, and the condition of introducing system errors during attitude estimation can be avoided; by means of the second-order AR error model, the influence of random errors of a random gyroscope on attitude estimation can be avoided; by using an adaptive Kalman filtering system equation, attitude estimation precision in different states can be ensured.

Description

technical field [0001] The invention belongs to the technical field of inertial navigation, and in particular relates to an attitude inclination estimation method suitable for precise operation of agricultural machinery. Background technique [0002] Inertial navigation technology is a completely autonomous navigation technology developed in the middle of the 20th century. The angular velocity and acceleration information of the carrier relative to the inertial space is measured by the inertial measurement component, and the instantaneous velocity and position information of the carrier is automatically calculated by using Newton's law of motion. . It can continuously provide all navigation and guidance parameters (position, linear velocity, angular velocity, attitude angle) of the carrier, and is widely used in the fields of aerospace, aviation, and navigation, especially in the military field. The accurate estimation of attitude inclination is the key parameter to realiz...

AI Technical Summary

Problems solved by technology

The four-element method requires Taylor expansion when calculating, and usually ignores its higher-order terms to convert nonlinearity into linearity for attitude estimation, and there are errors

[0007] However, the characteristics of the sensor itself are not considered in the actual application, such as the inherent zero bias of the gyroscope and the accelerometer, the random disturbance of the gyroscope, etc.

At the same time, there is still a lack of research on the process error covariance matrix Q and measurement error covariance matrix R under different working conditions, and the adaptability is limited, especially for agricultural machinery with complex operating conditions and environments

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