Attitude Estimation Method Combining UAV Dynamics Model and MEMS Sensors

A mechanical model and attitude estimation technology, applied in the field of UAV navigation, to improve the estimation accuracy, avoid software simulation calculation or a large number of wind tunnel tests

Active Publication Date: 2022-04-12
BEIHANG UNIV
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Problems solved by technology

[0005] In order to solve the problem of on-line parameter identification of the UAV dynamics model and the UAV attitude estimation problem of dynamic model / MEMS sensor fusion, the present invention provides a method of using the UAV dynamics model to assist the MEMS sensor to perform attitude estimation, so as to effectively improve the UAV attitude estimation. Attitude Estimation Accuracy of Human-Machine During Large Maneuvering Movement

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  • Attitude Estimation Method Combining UAV Dynamics Model and MEMS Sensors
  • Attitude Estimation Method Combining UAV Dynamics Model and MEMS Sensors
  • Attitude Estimation Method Combining UAV Dynamics Model and MEMS Sensors

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[0060] The present invention will be further described below in conjunction with the accompanying drawings and examples. It should be understood that the following examples are intended to facilitate the understanding of the present invention, and have no limiting effect on it.

[0061] Such as figure 1 Shown, the attitude estimation method of the present invention in conjunction with unmanned aerial vehicle dynamics model and MEMS sensor, comprises the steps:

[0062] Step 1: When the GPS signal is valid, use the GPS / MEMS integrated navigation results to estimate the motor pull coefficient and the three-axis constant disturbance torque of the UAV dynamic model, and according to the estimated motor pull coefficient and the three-axis constant disturbance torque Corrected drone dynamics model.

[0063] The following formula (1) gives the state quantities for estimating the motor pull coefficient and the three-axis constant disturbance torque and the nonlinear equation of sta...

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Abstract

The invention belongs to the field of unmanned aerial vehicle navigation, and in particular proposes an attitude estimation method combining an unmanned aerial vehicle dynamic model and a MEMS sensor, so as to effectively improve the attitude estimation accuracy of the unmanned aerial vehicle during large maneuvering movements. When GPS signal is valid, the present invention utilizes GPS / MEMS integrated navigation information to carry out on-line estimation to UAV dynamics model parameter, has provided the UAV dynamics model after correction; The gyroscope data in the MEMS sensor is filtered and the motion acceleration of the UAV is estimated, and combined with the MEMS sensor for Kalman filtering to obtain the attitude estimation of the UAV system. The invention can compensate the influence of the motion acceleration caused by the large maneuvering of the UAV on the gravity measured by the accelerometer, and is suitable for application occasions that require higher precision in attitude estimation of the UAV when the GPS fails.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle navigation, and particularly relates to a method for using an unmanned aerial vehicle dynamics model to assist a MEMS sensor to perform attitude calculation, which can compensate the influence of the motion acceleration caused by the large maneuvering of the unmanned aerial vehicle on the gravity measured by the accelerometer, and is applicable to It is used in applications that require high accuracy of UAV attitude estimation when GPS fails. Background technique [0002] UAV navigation technology is one of the key technologies for UAV system to realize autonomous flight. The realization of functions such as UAV path planning, real-time obstacle avoidance, precise landing and flight control requires the navigation module to provide continuous and comprehensive navigation information. Commonly used navigation technologies for drones mainly include inertial navigation, GPS navigation, visual n...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C23/00G01C21/18G01C21/16G01S19/49
CPCG01C23/005G01C21/18G01C21/165G01S19/49
Inventor 王学运张京娟徐一钒张谦
Owner BEIHANG UNIV
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