## 1 Introduction  
According to a report by the Population Division of the United Nations Department of Economic and Social Affairs in 2019, it is expected that the total world population will reach 9.7 billion by the middle of this century, and the demand for food will grow rapidly [1]. For a long time, intensive and extensive agriculture has been a priority solution to the imbalance between population growth and food shortages, but this approach is costly and labor-intensive [2]. On the one hand, many countries' agricultural sectors are facing an aging agricultural workforce [3]. On the other hand, due to the development of urbanization, more and more young laborers are moving away from agricultural production activities and towards cities, which will lead to a difficult problem of food shortage in the future. To address food shortages and other issues in agriculture, agriculturally developed countries are researching autonomous agricultural vehicles, replacing the basic technique and labor force required by traditional farming with sensor technology and electro-hydraulic control technology [4]. The global population aging and labor shortage have promoted the demand for mechanization and automation in industries, agriculture, and other fields [5]. Benefiting from the development and improvement of satellite positioning technology, inertial navigation technology, and control theory, the agricultural vehicle automatic navigation technology is increasingly being applied in agricultural production activities such as plowing, sowing, fertilization, and harvesting, becoming a key technology for precision agriculture [6]. The agricultural vehicle automatic navigation technology enables vehicles to better adapt to the complex field, improves the accuracy and efficiency of agricultural machinery operations, and reduces repeated and missed operations. Not only that, but it can also reduce the prolonged fatigue and repetitive driving work of the driver, thereby obtaining sufficient time to monitor and control agricultural machinery [7]. The key technologies of agricultural machinery automatic navigation mainly include positioning and attitude measurement, path planning, and path tracking control [8]. Figure 1 shows the composition of the agricultural machinery's automatic navigation system. In order to achieve automatic navigation driving, it is necessary to install sensors on the vehicle that can provide a location, heading information, and environment information. The most frequently used positioning and attitude measurement technologies in the research of agricultural machinery automatic navigation driving include global navigation satellite system (GNSS), inertial navigation system (INS), machine vision (MV) navigation system, and light detection and ranging (LiDAR). The comparison of three commonly used positioning and attitude sensors is shown in Table 1. GNSS can provide accurate navigation information, such as location, orientation, and speed, in an unobstructed environment, and is widely used in vehicles' automatic driving. [PERSON] et al. [9] used low-cost GPS receivers as positioning sensors for agricultural tractors and evaluated the performance of tractor automatic navigation systems through tracking straight-line trajectory tests. The inertial navigation system (INS) collects acceleration and angular velocity information through the inertial measurement unit (IMU) and is not subject to external interference. However, as time goes by, the accumulation of sensor errors will lead to a decline in accuracy. LiDAR has the advantages of high precision, and strong anti-interference ability, and is widely used in orchard environment perception and navigation. [PERSON] et al. [10] used LiDAR to obtain the measurement data of the orchard tree, and finally fitted the straight line of the fruit tree, using the center of the tree row as the navigation path. A single sensor inevitably has certain limitations, which are not conducive to improving navigation and positioning accuracy and reliability.