Dynamic weighing algorithm for unmanned aerial vehicles based on filtering fusion

Tingting Deng; Xiang Zhu; Yechao Bai

doi:10.1117/12.3023197

28 March 2024 Dynamic weighing algorithm for unmanned aerial vehicles based on filtering fusion

Tingting Deng, Xiang Zhu, Yechao Bai

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130910J (2024) https://doi.org/10.1117/12.3023197
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

In agriculture, obtaining the remaining fertilizer weight is crucial for achieving accurate fertilizer application when using drones for spreading fertilizer. To address the problem of inaccurate weighing of remaining fertilizer caused by environmental and system factors during the fertilizer application process, a fusion filtering algorithm suitable for dynamic weighing of fertilizer is proposed. First, a second-order model is established between the wheel speed and the fertilizer application rate. The three coefficients in the second-order mapping relationship formula between the fertilizer weight and the wheel speed are used as the four-dimensional state variables of the Kalman filter, with the wheel speed on the drone set as the control variable. Then the weight data measured by the weighing sensor is sent to the Kalman filter for primary filtering. At the same time, the sliding average filtering algorithm is used to smooth out the oscillation phenomenon in the filtering results. Simulation experiments and real data processing results show that the drone dynamic weighing fusion algorithm, based on the four-dimensional Kalman filter and sliding average filtering has good noise reduction and smoothing effects on fertilizer weight data.

Citation Download Citation

Tingting Deng, Xiang Zhu, and Yechao Bai "Dynamic weighing algorithm for unmanned aerial vehicles based on filtering fusion", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130910J (28 March 2024); https://doi.org/10.1117/12.3023197

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available