Abstract:
Abstract: The rapid development of modern agriculture in China has put forward higher requirements for agricultural machinery operation. In terms of area measurement, GPS (global positioning system) has become an important measuring tool, completely changed the traditional mode of operation, liberated the labor force, and improved the operation efficiency. Field operation is still basically in the stage of manual operation, so it is inevitable that there is much repetitive operation and missing operation. How to accurately measure the area of operation, this is a necessary issue. In this paper, the adaptive Kalman filter was used to improve GPS positioning accuracy for accurately measuring the tractor operation area. The adaptive Kalman filtering algorithm was mainly to solve the problem of the degradation of the system's filtering accuracy and the divergence of the system in the case of noise statistics being unknown or not accurate. In order to achieve the system noise estimation of adaptive filtering, we used the covariance matching technology and the Kalman filter residual error to realize the algorithm. In this research, the LABVIEW software was used to get latitude and longitude data of GPS receiver. And then the Gauss projection algorithm was used to change the longitude and latitude data into plane coordinates to calculate the area. To test and verify the influence of different ways of operation on the operation efficiency, back tillage, spindle tillage and alternative plough method were chosen. Firstly, this research used MATLAB to identify the operation trajectory, then used different color to show the area of operation, and used the image processing method to calculate the effective operation area, the actual operation area, and the missed and repeated tillage rate, which were used to evaluate the operation efficiency of the tractor. In order to verify the feasibility of the algorithm, the accuracy of single point positioning and the accuracy of area measurement were tested. The single point positioning experiment showed that the Kalman filter improved the accuracy of GPS single point positioning. The numerical changes at the x and y direction before filtering had relatively big fluctuation, and became flat after filtering. The mean value of coordinates changed after filtering, and the mean square error became smaller. The x coordinate reduced from 0.06317 to 0.05807 m after filtering, and the y coordinate reduced from 0.07901 to 0.04097 m after filtering. In the test of GPS area measuring precision, which was the preparation for its work in the measurement of field area, this research used the GPS to measure some regular and irregular figures. The result showed that the relative error of area measurement was 2.09%. Finally, the field experiment was conducted. The result showed that Block 1 missed tillage rate was 14.29%, and repeated tillage rate was 6.19%; Block 2 balk rate was 10.72%, and backset rate was 5.54%; Block 3 balk rate was 1.81%, and backset rate was 6.82%. With the measurement area increasing, the measurement accuracy was higher. The most efficient farming method was alternative tillage, and the second was spindle tillage. Back tillage's balk rate was the highest, and its operating efficiency was the lowest. Image processing method was used to calculate the backset and balk acreage in this paper. Different colors were used to display normal area, repeated tillage area and missed tillage area, through which it could visually display missed and repeated tillage locations, and then calculate the working efficiency. We can use this method to guide the actual agricultural production operation, and select the operation mode with high efficiency.