Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network

Dansong Yue, Shuqi Shang, Kai Feng, Haiqing Wang, Xiaoning He, Zelong Zhao, Ning Zhang, Baiqiang Zuo and Dongwei Wang ()
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Dansong Yue: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Shuqi Shang: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Kai Feng: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Haiqing Wang: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Xiaoning He: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Zelong Zhao: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Ning Zhang: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Baiqiang Zuo: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
Dongwei Wang: College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China

Agriculture, 2023, vol. 13, issue 9, 1-24

Abstract: Improving the positioning accuracy and stability of a single BDS/INS sensor system in agricultural machinery is important for expanding the application scenarios of agricultural machinery. This paper proposes a navigation and positioning model based on an improved bee-colony-algorithm-optimized BP network (the IABC-BP model). The main aspect of this work involves introducing adaptive coefficients and speed adjustment coefficients that obey Gaussian distribution to ensure the balance between the rate of convergence, group flexibility, and searchability in the search process. The implicit adaptive layer formula of the BP network is proposed, and the BDS/INS navigation and positioning model for agricultural machinery is established using the IABC algorithm and the Kalman filter. Simulation tests and analyses of real-world application scenarios were conducted on the model, and the results showed that, compared with the original model, the performance of the model improved by 90.65%, 84.11%, and 25.96%, indicating that the proposed model has high accuracy and effectiveness. In the information fusion and compensation correction mode, the algorithm processes errors such as longitude and latitude within the target range and can achieve reliable navigation and positioning accuracy in a short period. At the same time, the model has good stability and generalization ability, and can be applied to other navigation scenarios in the future to expand its application scope.

Keywords: BDS/INS; navigation and positioning; BP neural network; bee colony algorithm (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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