Positioning system and method suitable for intelligent pseudo-ginseng combine harvester in hills and mountains

Abstract

The invention belongs to the technical field of intelligent agricultural machinery navigation, and relates to a positioning system and method suitable for an intelligent pseudo-ginseng combine harvester in hills and mountains, and the system comprises a global satellite navigation system (GNSS), an inertial navigation system (INS), a visual system and a multi-source information fusion system. The global satellite navigation system comprises a base station and a mobile station and is used for determining position coordinate data of the pseudo-ginseng combine harvester; the inertial navigation system comprises an inertial measurement unit (IMU) for acquiring the posture, speed and displacement change of the pseudo-ginseng combine harvester; the visual system comprises a fisheye camera and is used for screening visual satellites; the multi-source information fusion system comprises a data receiving module, a visual processing module and an information fusion module. The system can receive operation information of the pseudo-ginseng combine harvester in real time, intelligently adjust a positioning strategy, adapt to a satellite signal limited environment, and ensure that the pseudo-ginseng combine harvester in hilly and mountainous regions adaptively obtains high-precision and continuous position information.

Description

Technical Field

[0001] The invention relates to a positioning system and method for an intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas, belonging to the technical field of intelligent agricultural machinery navigation. Background Art

[0002] The harvesting of Panax notoginseng in hilly and mountainous areas faces many technical challenges due to its special topographical conditions. Traditional Panax notoginseng harvesting methods usually rely on a large number of manual operations, which is not only labor-intensive but also costly. With the development of global satellite navigation system technology, auxiliary applications based on inertial navigation systems and visual processing technologies have gradually become a research hotspot, but in hilly and mountainous environments, these single systems still cannot meet the needs of high-precision and continuous positioning.

[0003] Hilly and mountainous farmlands are often limited in satellite signals due to the large terrain undulations and severe vegetation obstruction, resulting in signal loss or multipath effects. Existing inertial navigation systems are prone to accumulating errors during long-term use, while visual navigation alone is easily affected by lighting, weather conditions and obstacles, making it difficult to provide stable navigation performance. In recent years, the development of multi-source information fusion technology has provided new ideas for solving the above problems. By combining the global satellite navigation system (GNSS), inertial navigation system (INS) and visual processing technology, a multi-source fusion navigation and positioning method can be constructed, which can not only improve the positioning accuracy in an environment with limited satellite signals, but also enhance the reliability and stability of the system through multi-sensor collaboration. This factor graph-based fusion positioning method is particularly suitable for complex terrain in hilly and mountainous areas, and can dynamically adjust the positioning strategy to provide technical support for the efficient operation of Panax notoginseng combine harvesters. The research on precision agriculture and intelligent agricultural machinery technology is deepening. In order to meet the needs of high-precision positioning and stable navigation in hilly and mountainous environments, a multi-source information fusion intelligent Panax notoginseng combine harvester positioning system and method is urgently needed to solve the limitations of traditional single navigation technology and provide support for intelligent agricultural operations. Summary of the invention

[0004] The present invention provides an intelligent Panax notoginseng combine harvester positioning system and method suitable for complex terrain in hilly and mountainous areas, which is used to solve the problems of low positioning accuracy and unstable navigation of Panax notoginseng combine harvesters in complex terrains, provides a technical reference for precision agricultural operations, and lays a foundation for the efficient operation of intelligent Panax notoginseng combine harvesters and the development of intelligent agriculture.

[0005] The technical solution adopted by the present invention to solve its technical problem is: A positioning system for intelligent Panax notoginseng combine harvesters suitable for hilly and mountainous areas. It includes a global satellite navigation system, an inertial navigation system, a visual system, and a multi-source information fusion system. The global satellite navigation system includes a base station and a mobile station. The base station includes a satellite antenna, a signal receiving end, and a radio transmitting end. The mobile station includes a satellite antenna, a signal receiving end, and a radio receiving end, which are used to receive satellite positioning data and determine the position coordinates of the Panax notoginseng combine harvester. The inertial navigation system includes an inertial measurement unit (IMU) composed of an accelerometer and a gyroscope, which measures acceleration and angular velocity to calculate the attitude, speed and displacement of the Panax notoginseng combine harvester in real time; The visual system uses a fisheye camera to obtain a sky view and screen visible satellites to exclude satellite signals that are blocked or have multipath effects; The multi-source information fusion system includes a data receiving module, a visual processing module, and an information fusion module. A global satellite navigation system / inertial navigation system (GNSS / INS) fusion positioning method is constructed based on visible satellites screened by a visual system and assisted by a global satellite navigation system and an inertial navigation system. The data receiving module receives information input by the global satellite navigation system, the inertial navigation system and the visual system, and synchronizes and preprocesses multi-source data. The visual processing module uses the sky view obtained by a fisheye camera to identify visible satellites and screen out low-quality satellite signals that are blocked or have multipath effects. The information fusion module performs GNSS / INS fusion based on a factor graph based on the screened visual system information, combined with the pseudorange factor, Doppler frequency factor, carrier phase factor provided by the GNSS, and the acceleration and angular velocity information received by the INS.

[0006] A positioning method for an intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas comprises the following steps: Step 1: The fisheye camera collects the sky view: the global satellite navigation system initializes the positioning of the Panax notoginseng combine harvester based on the acquired pseudorange, Doppler frequency, carrier phase, and carrier-to-noise ratio; the inertial navigation system collects acceleration and angular velocity information, and finally transmits all the aforementioned information to the data receiving module in the multi-source information fusion system; Step 2: The visual processing module in the multi-source information fusion system converts the collected image into a grayscale image, and transforms the grayscale image into a binary image with an adaptive threshold, and uses the median filter algorithm to filter the noise points inside the binary image; Step 3: Image segmentation: Segment the filtered image to separate the sky area and the non-sky area. If the satellite is located in the sky area, the GNSS receiver can receive the satellite signal normally. Step 4: Project the satellite and the image in the same coordinate system: Based on the satellite orbit azimuth and elevation data provided by the GNSS receiver, project the satellite's spatial coordinates into the image captured and processed by the fisheye camera; Step 5: Traverse the image: take the center of the image as the initial search point, gradually update the position of the search point along the specified direction, and traverse the image comprehensively in turn; Step 6: Identify visible satellites: Use the current search point as the center and the radius as Extract the grayscale values ​​of all pixels in the search circle and calculate the average grayscale value of the pixels in the area , and by setting the threshold Determine the satellite's line-of-sight status. If the average Greater than threshold , the satellite is judged to be a line-of-sight satellite; otherwise, it is judged to be a non-line-of-sight satellite, providing high-quality satellite signal input for the satellite positioning system. For the signal identified as a line-of-sight satellite, it is further combined with the carrier-to-noise ratio and Doppler frequency shift stability parameters provided by the GNSS receiver to determine whether there is multipath interference: If the satellite is located in the sky segmentation area, but the carrier-to-noise ratio is lower than the dynamic threshold or the frequency shift fluctuation exceeds the preset range, it is determined that the satellite is affected by the multipath effect and the signal is excluded; Step 7: The information fusion module in the multi-source information fusion system constructs a GNSS / INS fusion framework based on the factor graph based on the selected line-of-sight satellites: coarse positioning is performed through pseudo-range observation factors; the speed and heading angle of the Panax notoginseng combine harvester are optimized using the Doppler frequency factor; then the observation model is constructed based on the carrier phase factor using the time difference method; the inertial guidance factor is stably added between the aforementioned factors in the form of pre-integration to avoid re-integration of the posture each time optimization; Step 8: Based on the line-of-sight discrimination results, the multi-source information fusion system dynamically adjusts the optimization window of the factor graph and adapts to the changes in the line-of-sight satellite.

[0007] In the fourth step, you can get the satellite Have a pixel position in the sky segmentation map, project the satellite into the sky segmentation map, the satellite and the image center Distance Its altitude angle The satellite position projection is obtained according to the following formula:

[0008] in, is the focal length of the fisheye camera, is the elevation angle of the i-th satellite; is the initial search direction angle of the image; The azimuth of the i-th satellite. In the fifth step, traverse the image and assume that the initial state of the satellite is , indicating that the satellite is initially visible, and the search point is updated gradually along the specified direction, with the step length of each update being determined by the increment value Sure, and They are the update results of the search point in the horizontal and vertical directions, respectively, and the initial search direction angle Used to control the direction of the search, the update formula of the search point is as follows: .

[0009] In the sixth step, in the GNSS / INS fusion framework based on the factor graph, when the satellite is within the line of sight, the geometric distance from the receiver to the satellite can be , receiver clock error and the satellite clock error , Tropospheric delay , ionospheric delay Add the pseudorange factor and use the following formula:

[0010] in, is the geometric distance of the i-th satellite; is the speed of light, is the clock error of the i-th satellite; is the tropospheric delay of the i-th satellite; is the ionospheric delay of the i-th satellite; To measure noise, When the speed is high, the Doppler shift factor is added, using the following formula:

[0011] in, The rate of change of the distance from the receiver to the satellite, and are the frequency drifts of the receiver and satellite, respectively, To measure noise, When the satellite is continuously tracked for a period of time within the line of sight, the carrier phase factor is added, and the carrier phase measurement is performed at the geometric distance. Based on the carrier wavelength And the whole week ambiguity processing,

[0012] in, To measure noise.

[0013] Beneficial effects of the present invention: The positioning system and method for intelligent Panax notoginseng combine harvesters in hilly and mountainous areas provided by the present invention combines the global satellite navigation system, inertial navigation system and visual system, and performs GNSS / INS fusion positioning based on factor graph through a multi-source information fusion system, effectively overcoming the problems of limited satellite signals, serious signal multipath effects and insufficient positioning accuracy of a single navigation system in hilly and mountainous environments. The entire positioning system can synchronize and preprocess multi-source data, dynamically adjust the optimization window of the factor graph, and adapt to environmental changes, thereby ensuring that the combine harvester can continuously obtain high-precision location information in complex terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the overall structure of a preferred embodiment of the present invention; Figure 2 It is a composition diagram of the intelligent Panax notoginseng combine harvester positioning system of the preferred embodiment of the present invention; Figure 3 It is a composition diagram of a multi-source information fusion positioning system according to a preferred embodiment of the present invention; Figure 4 is a schematic diagram of satellite coordinates projected onto an image in a preferred embodiment of the present invention; Figure 5 It is a flow chart of obtaining the operating status of a Panax notoginseng combine harvester according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0015] The present invention will now be further described in detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams that only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0016] Figure 1 As shown, a positioning system suitable for intelligent Panax notoginseng combine harvesters in hilly and mountainous areas: Including global satellite navigation system, inertial navigation system, vision system and multi-source information fusion system; The global satellite navigation system determines the position coordinates of the Panax notoginseng combine harvester by receiving satellite positioning data; The inertial navigation system calculates the attitude, speed and displacement of the Panax notoginseng combine harvester in real time by measuring acceleration and angular velocity; Figure 2 As shown, the global satellite navigation system includes a base station and a mobile station. The base station includes a satellite antenna, a signal receiving end, and a radio transmitting end; the mobile station includes a satellite antenna, a signal receiving end, and a radio receiving end, which are used to receive satellite positioning data and determine the position coordinates of the Panax notoginseng combine harvester.

[0017] The inertial navigation system includes an IMU measurement unit composed of an accelerometer and a gyroscope, which measures acceleration and angular velocity to calculate the attitude, speed and displacement of the Panax notoginseng combine harvester in real time; A visual system that uses a fisheye camera to obtain a view of the sky and screen visible satellites, excluding satellite signals that are blocked or have multipath effects; Figure 3 As shown, it also includes a multi-source information fusion system, which includes a data receiving module, a visual processing module, and an information fusion module, wherein the data receiving module receives information input from the global satellite navigation system, the inertial navigation system, and the visual system, and synchronizes and preprocesses the multi-source data; the visual processing module uses the sky view obtained by the fisheye camera to identify visible satellites and filter out low-quality satellite signals that are blocked or have multipath effects; the information fusion module performs GNSS / INS fusion based on the factor graph based on the filtered visual system information, combined with the pseudorange factor, Doppler frequency factor, carrier phase factor provided by the GNSS, and the acceleration and angular velocity information received by the INS.

[0018] A positioning method for an intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas comprises the following steps: Step 1: The fisheye camera collects the sky view: The global satellite navigation system initializes the positioning of the Panax notoginseng combine harvester based on the acquired pseudorange, Doppler frequency, carrier phase, and carrier-to-noise ratio; the inertial navigation system collects acceleration and angular velocity information, and all the aforementioned information is transmitted to the data receiving module in the multi-source information fusion system; Step 2: The visual processing module in the multi-source information fusion system converts the collected image into a grayscale image, and transforms the grayscale image into a binary image with an adaptive threshold, and uses the median filter algorithm to filter the noise points inside the binary image; Step 3: Image segmentation: Segment the filtered image to separate the sky area and the non-sky area. If the satellite is located in the sky area, the GNSS receiver can receive the satellite signal normally. Step 4: Project the satellite and the image in the same coordinate system: Based on the satellite orbit azimuth and elevation data provided by the GNSS receiver, project the satellite's spatial coordinates into the image captured and processed by the fisheye camera; Step 5: Traverse the image: take the center of the image as the initial search point, gradually update the position of the search point along the specified direction, and traverse the image comprehensively in turn; Step 6: Identify visible satellites: Use the current search point as the center and the radius as Extract the grayscale values ​​of all pixels in the search circle and calculate the average grayscale value of the pixels in the area , and by setting the threshold Determine the satellite's line-of-sight status. If the average Greater than threshold , then the satellite is judged to be a line-of-sight satellite; otherwise, it is judged to be a non-line-of-sight satellite, providing high-quality satellite signal input for the satellite positioning system. For the signal identified as a line-of-sight satellite, the carrier-to-noise ratio and Doppler frequency shift stability parameters provided by the GNSS receiver are further combined to determine whether there is multipath interference: if the satellite is located in the sky segmentation area, but the carrier-to-noise ratio is lower than the dynamic threshold or the frequency shift fluctuation exceeds the preset range, it is determined that the satellite is affected by the multipath effect and the signal is excluded; Step 7: The information fusion module in the multi-source information fusion system constructs a GNSS / INS fusion framework based on the factor graph based on the screened line-of-sight satellites: coarse positioning is performed through pseudorange observation factors; the Doppler frequency factor is then used to optimize the speed and heading angle of the Panax notoginseng combine harvester; then based on the carrier phase factor, the observation model is constructed by time difference; the inertial guidance factor is stably added between the aforementioned factors in the form of pre-integration to avoid re-integration of the posture each time optimization; Step 8: Based on the line-of-sight discrimination results, the multi-source information fusion system dynamically adjusts the optimization window of the factor graph and adapts to the changes in the line-of-sight satellite.

[0019] Figure 4 As shown, in the fourth step, the satellite Have a pixel position in the sky segmentation map, project the satellite into the sky segmentation map, the satellite and the image center Distance Its altitude angle The satellite position projection is obtained according to the following formula:

[0020] in, is the focal length of the fisheye camera, is the elevation angle of the i-th satellite; is the initial search direction angle of the image; The azimuth of the i-th satellite. In the fifth step, traverse the image and assume that the initial state of the satellite is , indicating that the satellite is initially visible, and the search point is updated gradually along the specified direction, with the step length of each update being determined by the increment value Sure, and They are the update results of the search point in the horizontal and vertical directions, respectively, and the initial search direction angle Used to control the direction of the search, the update formula of the search point is as follows: .

[0021] Figure 5As shown in the figure, in the sixth step, in the GNSS / INS fusion framework based on the factor graph, when the satellite is within the line of sight, the geometric distance from the receiver to the satellite can be , receiver clock error and the satellite clock error , Tropospheric delay , ionospheric delay Add the pseudorange factor and use the following formula:

[0022] in, is the geometric distance of the i-th satellite; is the speed of light, is the clock error of the i-th satellite; is the tropospheric delay of the i-th satellite; is the ionospheric delay of the i-th satellite; To measure noise, When the speed is high, the Doppler shift factor is added, using the following formula:

[0023] in, The rate of change of the distance from the receiver to the satellite, and are the frequency drifts of the receiver and satellite, respectively, To measure noise, When the satellite is continuously tracked for a period of time within the line of sight, the carrier phase factor is added, and the carrier phase measurement is performed at the geometric distance. Based on the carrier wavelength And the whole week ambiguity processing,

[0024] in, To measure noise.

[0025] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0026] The meaning of "and / or" in this application refers to the situation where each exists alone or both exist at the same time. Based on the above ideal embodiments of the present invention, the relevant staff can make various changes and modifications without departing from the technical concept of the present invention through the above description. The technical scope of the present invention is not limited to the contents of the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A positioning system for an intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas, characterized by: Including global satellite navigation system, inertial navigation system, vision system and multi-source information fusion system; The global satellite navigation system determines the position coordinates of the Panax notoginseng combine harvester by receiving satellite positioning data; The inertial navigation system calculates the attitude, speed and displacement of the Panax notoginseng combine harvester in real time by measuring acceleration and angular velocity; The visual system uses a fisheye camera to obtain a sky view and screen visible satellites to exclude satellite signals that are blocked or have multipath effects; The multi-source information fusion system receives visible satellite signals filtered by the visual system to assist in the construction of a fusion positioning method of the global satellite navigation system and the inertial navigation system; The global satellite navigation system includes a base station and a mobile station; The base station includes a satellite antenna, a signal receiving end, and a radio transmitting end; the mobile station includes a satellite antenna, a signal receiving end, and a radio receiving end; The visual system includes a fisheye camera; The inertial navigation system includes an IMU measurement unit composed of an accelerometer and a gyroscope; The multi-source information fusion system includes a data receiving module, a visual processing module, and an information fusion module. The data receiving module receives information input from a global satellite navigation system, an inertial navigation system, and a visual system, and then synchronizes and preprocesses the multi-source data to ensure the temporal and spatial consistency of the data. The visual processing module uses the sky view obtained by a fisheye camera to identify visible satellites and filter out low-quality satellites that are blocked or have multipath effects. The information fusion module performs GNSS / INS fusion based on a factor graph based on the filtered visual system information, combined with the pseudorange factor, Doppler frequency factor, carrier phase factor provided by the GNSS, and the acceleration and angular velocity information received by the INS.

2. A positioning method for an intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas, characterized in that: The steps include: Step 1: The fisheye camera collects the sky view: The global satellite navigation system initializes the positioning of the Panax notoginseng combine harvester based on the acquired pseudorange, Doppler frequency, carrier phase, and carrier-to-noise ratio; the inertial navigation system collects acceleration and angular velocity information, and all the aforementioned information is transmitted to the data receiving module in the multi-source information fusion system; Step 2: The visual processing module in the multi-source information fusion system converts the collected image into a grayscale image, and transforms the grayscale image into a binary image with an adaptive threshold, and uses the median filter algorithm to filter the noise points inside the binary image; Step 3: Image segmentation: Segment the filtered image to separate the sky area and the non-sky area. If the satellite is located in the sky area, the GNSS receiver can receive the satellite signal normally. Step 4: Project the satellite and the image in the same coordinate system: Based on the satellite orbit azimuth and elevation data provided by the GNSS receiver, project the satellite's spatial coordinates into the image captured and processed by the fisheye camera; Step 5: Traverse the image: take the center of the image as the initial search point, gradually update the position of the search point along the specified direction, and traverse the image in turn; Step 6: Identify visible satellites: Use the current search point as the center and the radius as Extract the grayscale values ​​of all pixels within the search circle and calculate the average grayscale value of the pixels in the area , and by setting the threshold Determine the satellite's line-of-sight status. If the average Greater than threshold , the satellite is judged to be a line-of-sight satellite; otherwise, it is judged to be a non-line-of-sight satellite, providing high-quality satellite signal input for the satellite positioning system. For the signal identified as a line-of-sight satellite, it is further combined with the carrier-to-noise ratio and Doppler frequency shift stability parameters provided by the GNSS receiver to determine whether there is multipath interference: If the satellite is located in the sky segmentation area, but the carrier-to-noise ratio is lower than the dynamic threshold or the frequency shift fluctuation exceeds the preset range, it is determined that the satellite is affected by the multipath effect and the signal is excluded; Step 7: The information fusion module in the multi-source information fusion system constructs a GNSS / INS fusion framework based on the factor graph based on the selected line-of-sight satellites: coarse positioning is performed through pseudo-range observation factors; the speed and heading angle of the Panax notoginseng combine harvester are optimized using the Doppler frequency factor; then the observation model is constructed based on the carrier phase factor using the time difference method; the inertial guidance factor is stably added between the aforementioned factors in the form of pre-integration to avoid re-integration of the posture each time optimization; Step 8: Based on the line-of-sight discrimination results, the multi-source information fusion system dynamically adjusts the optimization window of the factor graph and adapts to the changes in the line-of-sight satellite.

3. The positioning method of the intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas according to claim 2, characterized in that: In the fourth step, you can get the satellite Have a pixel position in the sky segmentation map, project the satellite into the sky segmentation map, the satellite and the image center Distance Its altitude angle The satellite position projection is obtained according to the following formula: in, is the focal length of the fisheye camera, is the elevation angle of the i-th satellite; is the initial search direction angle of the image; The azimuth of the i-th satellite.

4. The positioning method of the intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas according to claim 2, characterized in that: In the fifth step, traverse the image and assume that the satellite is in the initial state , indicating that the satellite is initially visible, and the search point is updated gradually along the specified direction, with the step length of each update being determined by the increment value Sure, and They are the update results of the search point in the horizontal and vertical directions, respectively, and the initial search direction angle Used to control the direction of the search, the update formula of the search point is as follows: 。 5. The positioning method of the intelligent Panax notoginseng combine harvester suitable for hilly and mountainous areas according to claim 2, characterized in that: In the sixth step, in the GNSS / INS fusion framework based on the factor graph, when the satellite is within the line of sight, the geometric distance from the receiver to the satellite can be , receiver clock error and the satellite clock error , Tropospheric delay , ionospheric delay Add the pseudorange factor and use the following formula: in, is the geometric distance of the i-th satellite; is the speed of light, is the clock error of the i-th satellite; is the tropospheric delay of the i-th satellite; is the ionospheric delay of the i-th satellite; To measure noise, When the speed is high, the Doppler shift factor is added, using the following formula: in, The rate of change of the distance from the receiver to the satellite, and are the frequency drifts of the receiver and satellite, respectively, To measure noise, When the satellite is continuously tracked for a period of time within the line of sight, the carrier phase factor is added, and the carrier phase measurement is performed at the geometric distance. Based on the carrier wavelength And the whole week ambiguity processing, in, To measure noise.

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