GNSS navigation and positioning method assisted by camera device

Abstract

A GNSS navigation and positioning method assisted by a camera device, comprising: acquiring observation data of a plurality of satellites by means of a receiver, and acquiring a plurality of images acquired by means of a camera device (101), wherein the camera device and the receiver are located in the same area, and the camera device captures images at an angle facing the sky; for any satellite, determining the mapped position of the satellite on a corresponding image on the basis of the observation data of the satellite, and determining an obstruction status of the satellite on the basis of the mapped position of the satellite on the corresponding image (102); for any satellite, determining an impact weight for the observation data of the satellite on the basis of the obstruction status of the satellite and a quality index corresponding to the observation data of the satellite (103); and determining positioning information of the receiver on the basis of updated impact weights of the observation data of the plurality of satellites (104). The method can well solve the problems of signal obstruction and multi-path effects, and improve the positioning accuracy of receivers.

Description

A GNSS navigation and positioning method assisted by a camera device Technical Field

[0001] The present application relates to the field of satellite navigation technology, and in particular to a GNSS navigation and positioning method that can be assisted by a camera device. Background Art

[0002] Global Navigation Satellite System (GNSS) satellites provide users with a variety of observations, including pseudoranges and carrier phase measurements. GNSS is a space-based radio-based positioning system comprised of a constellation of satellites that provide global coverage and real-time positioning services. GNSS satellites continuously transmit signals to user devices, providing accurate navigation and positioning services. With the continuous development of satellite navigation systems, GNSS is playing an increasingly important role in military, civilian, and commercial applications.

[0003] During real-time continuous observation, GNSS satellite signals are inevitably affected by the observation environment. This is especially true in areas with complex terrain. GNSS satellite signals are affected by environmental reflection, refraction, and diffraction, resulting in multipath errors of up to 10 or even 100 meters, significantly reducing the accuracy and reliability of the mobile phone receiver's positioning. Therefore, positioning accuracy in complex environments is crucial for the further optimization and development of GNSS systems. These environments may include urban high-rise buildings, canyon areas, forested areas, or areas with significant signal obstruction. Addressing these challenges requires exploring new technical approaches, such as developing advanced signal processing algorithms, improving receiver design to enhance signal acquisition capabilities, and using augmented reality or machine learning technologies to improve positioning accuracy.

[0004] However, there is still no perfect solution to effectively solve the signal shielding and multipath effects.

[0005] Summary of the Invention

[0006] The present application provides a GNSS navigation and positioning method that can be assisted by a camera device, which can effectively solve signal shielding and multipath effects.

[0007] In a first aspect, an embodiment of the present application provides a GNSS navigation and positioning method that can be assisted by a camera device. The method can be executed by a positioning device, which can be a terminal device or a module for a terminal device, or a server or a module for a server. The present application does not limit the execution subject of the method. The method includes: obtaining observation data of multiple satellites through a receiver and obtaining multiple images captured by a camera device; the camera device and the receiver are located in the same location area and the camera device performs image capture at an angle facing the sky; for any satellite, determining the mapping position of the satellite on the corresponding image based on the observation data of the satellite; determining the obstruction status of the satellite based on the mapping position of the satellite on the corresponding image; the mapping position is used to represent the positional relationship between the satellite and the sky area in the image; the corresponding image and the observation data of the satellite belong to the same time period; for any satellite, determining the influence weight of the observation data of the satellite based on the obstruction status of the satellite and the quality index corresponding to the observation data of the satellite; and determining the positioning information of the receiver based on the influence weights of the updated observation data of multiple satellites.

[0008] In this solution, the receiver acquires observation data transmitted by satellites while receiving images captured by cameras. Based on the satellite observation data, the receiver determines the mapping positions of multiple satellites within the image. The different mapping positions determine the degree of influence of each satellite on the receiver's positioning. Based on the degree of obstruction of a satellite and the quality index corresponding to the satellite's observation data, the influence weight of the satellite's observation data can be accurately determined. This effectively mitigates signal obstruction and multipath effects, improving the receiver's positioning accuracy.

[0009] In one possible implementation method, the altitude angle and the azimuth angle of the satellite are determined based on the observation data of the satellite; wherein the altitude angle is used to indicate the distance between the satellite and the receiver in polar coordinates, and the azimuth angle is used to indicate the angle between the satellite and the receiver in polar coordinates; based on the altitude angle and the azimuth angle of the satellite, the mapping position of the satellite on the corresponding image is determined.

[0010] The above scheme can accurately determine the mapping position of the satellite on the corresponding image based on the satellite's altitude angle and azimuth angle. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning. Therefore, it can effectively solve the signal shielding and multipath effects and improve the accuracy of positioning.

[0011] In one possible implementation method, if the mapping position of the satellite on the corresponding image belongs to the sky area, the satellite is determined to be in a direct state; if the mapping position of the satellite on the corresponding image belongs to the non-sky area, the satellite is determined to be in an obstructed state; if the mapping position of the satellite on the corresponding image belongs to the boundary between the sky area and the non-sky area, the satellite is determined to be in a blurred state.

[0012] The above scheme divides satellites into the above three types, so that the degree of obstruction of the satellites can be accurately determined. Furthermore, the impact of satellites with different degrees of obstruction on the receiver positioning can be accurately determined. Therefore, it can effectively solve the signal shielding and multipath effects and improve the accuracy of positioning.

[0013] In one possible implementation method, if the signal type corresponding to the satellite is a direct signal type, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is not changed; if the signal type corresponding to the satellite is an occlusion type, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the signal type corresponding to the satellite is an ambiguous signal type, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is updated.

[0014] The above scheme determines the influence weight information of the observation data corresponding to the satellite on the positioning of the receiver according to the signal types corresponding to different satellites. According to the degree of obstruction of the satellite and the quality index corresponding to the observation data of the satellite, it is possible to accurately determine the influence weight of the observation data of the satellite. Therefore, it is possible to effectively solve the signal shielding and multipath effects and improve the accuracy of positioning.

[0015] In one possible implementation method, an adjustment strategy and an adjustment threshold corresponding to the signal type of the satellite are obtained; an adjustment action for the observation data of the satellite is determined from the adjustment strategy based on the relationship between the quality index corresponding to the observation data of the satellite and the adjustment threshold; the adjustment action represents the impact weight information on the observation data of the satellite.

[0016] The above scheme determines the adjustment strategy and adjustment threshold according to different signal types, thereby enabling the processing of satellites with different signal types. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning, thereby effectively solving signal shielding and multipath effects and improving positioning accuracy.

[0017] In a possible implementation method, if the signal type of the satellite is a direct signal type, the adjustment threshold is a first threshold, and the adjustment strategy includes retention and downgrade; if the signal type of the satellite is an obstruction signal type, the adjustment threshold is a second threshold, and the adjustment strategy includes downgrade and deletion; if the signal type of the satellite is an ambiguous signal type, the adjustment threshold is a third threshold, and the adjustment strategy includes retention, downgrade and deletion; according to the relationship between the quality index corresponding to the observation data of the satellite and the adjustment threshold, the adjustment action for the observation data of the satellite is determined from the adjustment strategy, including: if the signal type of the satellite is a direct signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the first threshold, then retain the influence weight information of the observation data sent by the satellite; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, then update the influence weight information of the observation data sent by the satellite on the positioning of the receiver according to the quality index; The signal type of the satellite is an occlusion signal type. If the quality index corresponding to the observation data sent by the satellite is greater than or equal to the second threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index; if the quality index corresponding to the observation data sent by the satellite is less than the second threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; the signal type of the satellite is an ambiguous signal type. If the quality index corresponding to the observation data sent by the satellite is greater than or equal to the maximum value of the third threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than or equal to the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the quality index corresponding to the observation data sent by the satellite is within the range of the third threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index.

[0018] The above scheme can accurately process satellites with different signal types. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning. Therefore, it can effectively solve the signal shielding and multipath effects and improve the accuracy of positioning.

[0019] In one possible implementation method, a weight matrix corresponding to the multiple satellites is obtained; the weight matrix is ​​used to indicate the degree of influence of the observation data on the receiver positioning; a scaling factor is determined based on the quality index corresponding to the observation data and the ideal quality index; the weight matrix is ​​updated based on the scaling factor; and based on the updated weight matrix, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated.

[0020] The above scheme determines the scaling factor based on the quality index corresponding to the observation data. Therefore, the scaling factor can accurately reflect the impact of observation data of different qualities on the receiver positioning. If the quality index corresponding to the satellite is higher, the impact weight information of the observation data sent by the satellite on the receiver positioning is increased; if the quality index corresponding to the satellite is lower, the impact weight information of the observation data sent by the satellite on the receiver positioning is reduced. Therefore, the impact of observation data of different qualities on the receiver positioning can be accurately determined, thereby effectively solving signal shielding and multipath effects and improving positioning accuracy.

[0021] In a possible implementation method, the quality indicator refers to a carrier-to-noise ratio.

[0022] In the above scheme, the carrier-to-noise ratio is one of the important indicators reflecting the signal reception quality. The carrier-to-noise ratio is highly correlated with the accuracy of the observation value. Using the carrier-to-noise ratio to determine the weight can better reflect the characteristics of the GNSS observation value.

[0023] In one possible implementation method, if the number of satellites with non-zero weights after update is less than a fourth threshold, a supplementary satellite set is determined from the satellites whose weights are reset to zero; wherein the sum of the number of satellites in the supplementary satellite set and the number of satellites with non-zero weights is greater than or equal to the fourth threshold.

[0024] In the above scheme, if the number of satellites is less than the fourth threshold, the position of the receiver cannot be determined. Therefore, when the number of satellites with non-zero updated weights is less than the fourth threshold, the number of available satellites is increased, thereby enabling the position of the receiver to be accurately determined.

[0025] In a possible implementation method, the period of the camera device collecting images is consistent with the period of the receiver acquiring observation data of multiple satellites.

[0026] In the above scheme, the period of image acquisition by the camera device is consistent with the period of the receiver acquiring observation data of multiple satellites, so that the image acquisition by the camera device and the observation data of multiple satellites are in the same time period. Therefore, it is possible to accurately determine the degree of obstruction of multiple satellites at the current time and current position. Furthermore, it is possible to accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning, thereby effectively solving signal shielding and multipath effects and improving positioning accuracy.

[0027] In a second aspect, an embodiment of the present application provides a GNSS navigation and positioning device that can be assisted by a camera device, comprising: an acquisition unit and a determination unit. The acquisition unit is used to acquire observation data of multiple satellites and multiple images captured by the camera device through a receiver; the camera device and the receiver are located in the same location area and the camera device captures images at an angle facing the sky; the determination unit is used to determine, for any satellite, the mapping position of the satellite on the corresponding image based on the observation data of the satellite; determine the obstruction condition of the satellite based on the mapping position of the satellite on the corresponding image; the mapping position is used to characterize the positional relationship between the satellite and the sky area in the image; the corresponding image and the observation data of the satellite belong to the same time period; for any satellite, determine the influence weight of the observation data of the satellite based on the obstruction condition of the satellite and the quality index corresponding to the observation data of the satellite; determine the positioning information of the receiver based on the influence weights of the updated observation data of multiple satellites.

[0028] In one possible implementation method, a determination unit is used to determine the altitude angle of the satellite and the azimuth angle of the satellite based on the observation data of the satellite; wherein the altitude angle is used to indicate the distance between the satellite and the receiver in polar coordinates, and the azimuth angle is used to indicate the angle between the satellite and the receiver in polar coordinates; and the mapping position of the satellite on the corresponding image is determined based on the altitude angle of the satellite and the azimuth angle of the satellite.

[0029] In one possible implementation method, the determination unit is used to determine that the satellite is in a direct state if the mapping position of the satellite on the corresponding image belongs to the sky area; determine that the satellite is in an obstructed state if the mapping position of the satellite on the corresponding image belongs to the non-sky area; and determine that the satellite is in a blurred state if the mapping position of the satellite on the corresponding image belongs to the boundary between the sky area and the non-sky area.

[0030] In one possible implementation method, the determination unit is used to, if the signal type corresponding to the satellite is a direct signal type, not change the influence weight information of the observation data corresponding to the satellite on the receiver positioning; if the signal type corresponding to the satellite is an occlusion type, set the influence weight information of the observation data corresponding to the satellite on the receiver positioning to zero; if the signal type corresponding to the satellite is an ambiguous signal type, update the influence weight information of the observation data corresponding to the satellite on the receiver positioning.

[0031] In one possible implementation method, an acquisition unit is used to obtain an adjustment strategy and an adjustment threshold corresponding to the signal type of the satellite; a determination unit is used to determine an adjustment action for the observation data of the satellite from the adjustment strategy based on a relationship between a quality indicator corresponding to the observation data of the satellite and the adjustment threshold; the adjustment action represents information on an impact weight on the observation data of the satellite.

[0032] In one possible implementation method, if the satellite signal type is a direct signal type, the adjustment threshold is a first threshold, and the adjustment strategy includes retention and downgrading; if the satellite signal type is an obstructed signal type, the adjustment threshold is a second threshold, and the adjustment strategy includes downgrading and deletion; if the satellite signal type is an ambiguous signal type, the adjustment threshold is a third threshold, and the adjustment strategy includes retention, downgrading, and deletion;

[0033] A determination unit, for the satellite signal type being a direct signal type, and if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a first threshold, retaining the influence weight information of the observation data sent by the satellite; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, updating the influence weight information of the observation data sent by the satellite on the receiver positioning according to the quality index; the satellite signal type being an occlusion signal type, and if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a second threshold, updating the influence weight information of the observation data sent by the satellite on the receiver positioning according to the quality index; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, updating the influence weight information of the observation data sent by the satellite on the receiver positioning according to the quality index. If the quality index corresponding to the observation data sent by the satellite is less than the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the signal type of the satellite is a fuzzy signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the maximum value of the third threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than or equal to the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the quality index corresponding to the observation data sent by the satellite is within the range of the third threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index.

[0034] In one possible implementation method, an acquisition unit is used to obtain a weight matrix corresponding to the multiple satellites; the weight matrix is ​​used to indicate the degree of influence of the observation data on the receiver positioning; a determination unit is used to determine a scaling factor based on a quality index corresponding to the observation data and an ideal quality index; the weight matrix is ​​updated according to the scaling factor; and based on the updated weight matrix, the weight information of the influence of the observation data sent by the satellite on the receiver positioning is updated.

[0035] In a possible implementation method, the quality indicator refers to a carrier-to-noise ratio.

[0036] In one possible implementation method, a determination unit is configured to determine a supplementary satellite set from satellites whose weights are reset to zero if the number of satellites whose weights are not zero after the update is less than a fourth threshold; wherein the sum of the number of satellites in the supplementary satellite set and the number of satellites whose weights are not zero is greater than or equal to the fourth threshold.

[0037] In a possible implementation method, the period of the camera device collecting images is consistent with the period of the receiver acquiring observation data of multiple satellites.

[0038] In a third aspect, an embodiment of the present application further provides a computing device, including:

[0039] a memory for storing program instructions;

[0040] The processor is configured to call the program instructions stored in the memory and execute any method for implementing the first aspect according to the obtained program instructions.

[0041] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which computer-readable instructions are stored. When a computer reads and executes the computer-readable instructions, any method of the above-mentioned first aspect is implemented.

[0042] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising a computer program executable by a computer device, wherein when the program is run on the computer device, the computer device executes any method for implementing the above-mentioned first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] FIG1 is a flow chart of a GNSS navigation and positioning method assisted by a camera device according to an embodiment of the present application;

[0044] FIG2 is a schematic diagram of a process for training a sky segmentation model according to an embodiment of the present application;

[0045] FIG3 is a schematic structural diagram of a GNSS navigation and positioning device that can be assisted by a camera device, provided in an embodiment of the present application;

[0046] FIG4 is a schematic structural diagram of a GNSS navigation and positioning device that can be assisted by a camera device, provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The following is an explanation of some of the professional terms used in this application.

[0048] Global Navigation Satellite System (GNSS): The Global Navigation Satellite System is a space-based radio receiver positioning system that can provide users with all-weather 3D coordinates, velocity, and time information at any location on the Earth's surface or in near-Earth space.

[0049] Multipath effect: If a satellite signal reaches a receiver via a straight-line path, the signal received by the receiver is delayed by the satellite's transmitted signal and has the highest signal strength. During signal propagation, reflections from objects change the signal's direction, amplitude, polarization, and phase. These altered signals arrive at the receiver and overlap with the signal that reached the receiver via the straight-line path. This phenomenon is called multipath. Multipath is one of the main causes of interference with GPS measurement quality. Multipath is similar to the phenomenon of echo: while the receiver receives the direct signal from the satellite, it also receives satellite signals reflected by other objects. If changing the measurement location is not possible in GPS measurements, the main method to reduce multipath is to increase the satellite cutoff angle. However, this also blocks signals from satellites at low altitudes (i.e., those just rising above the horizon). Other options include adding chokes and path-stopping shields. However, multipath can only be reduced, not eliminated.

[0050] Figure 1 is a flow chart illustrating a camera-assisted GNSS navigation and positioning method provided in an embodiment of the present application. This method can be performed by a positioning device, which can be a terminal device or a module for a terminal device, or a server or a module for a server. This application does not limit the execution entity of this method.

[0051] The method comprises the following steps:

[0052] Step 101: Obtain observation data of multiple satellites through a receiver and obtain multiple images captured by a camera device.

[0053] The camera device and the receiver are located in the same location area and the camera device collects images at an angle facing the sky.

[0054] In one possible implementation, the receiver is configured to receive observation data transmitted by multiple satellites, and the observation data is used to determine the receiver's positioning information. The camera device and the receiver are located in the same location area. Exemplarily, the receiver is equipped with at least one camera device, and the camera device captures images at an angle facing the sky.

[0055] In a possible implementation method, the receiver is in motion, and multiple images captured by a camera device and observation data of multiple satellites obtained by the receiver are used to locate the moving receiver.

[0056] In one possible implementation method, the image acquisition cycle of the camera device is consistent with the cycle of the receiver acquiring observation data from multiple satellites. For example, the receiver acquires observation data transmitted by multiple satellites at every epoch, while the camera device simultaneously acquires at least one image at every epoch. In this solution, the image acquisition cycle of the camera device is consistent with the cycle of the receiver acquiring observation data from multiple satellites. This allows the camera device to acquire images and the observation data from multiple satellites to occur in the same time period, thereby accurately determining the degree of obstruction of multiple satellites at the current time and location. Furthermore, the impact of satellites with different degrees of obstruction on the receiver's positioning can be accurately determined, thereby effectively addressing signal shielding and multipath effects and improving positioning accuracy.

[0057] Step 102: For any satellite, determine the mapping position of the satellite on the corresponding image based on the observation data of the satellite; and determine the obstruction status of the satellite based on the mapping position of the satellite on the corresponding image.

[0058] The mapping position is used to characterize the positional relationship between the satellite and the sky area in the image; and the corresponding image and the observation data of the satellite belong to the same time period.

[0059] In one possible implementation, the satellite's elevation angle and azimuth angle are determined based on the satellite's observation data. The elevation angle indicates the distance between the satellite and the receiver in polar coordinates, and the azimuth angle indicates the angle between the satellite and the receiver in polar coordinates. The satellite's mapping position on the corresponding image is determined based on the satellite's elevation angle and azimuth angle. This solution accurately determines the satellite's mapping position on the corresponding image based on the satellite's elevation angle and azimuth angle. Furthermore, it accurately determines the impact of satellites with varying degrees of obstruction on the receiver's positioning. This effectively addresses signal shielding and multipath effects, improving positioning accuracy.

[0060] In one possible implementation method, if the mapping position of the satellite on the corresponding image belongs to the sky area, the satellite is determined to be in a direct state, and the satellite is considered to be unobstructed; if the mapping position of the satellite on the corresponding image belongs to the non-sky area, the satellite is determined to be in an obstructed state, and the satellite is considered to be completely obstructed; if the mapping position of the satellite on the corresponding image belongs to the junction of the sky area and the non-sky area, the satellite is determined to be in a blurred state, and the satellite is considered to be partially obstructed. This solution divides satellites into the above three types, so that the degree of obstruction of the satellite can be accurately determined. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning, thereby effectively solving signal shielding and multipath effects and improving positioning accuracy.

[0061] Step 103 : For any satellite, determine the influence weight of the observation data of the satellite according to the obstruction condition of the satellite and the quality index corresponding to the observation data of the satellite.

[0062] In one possible implementation method, the more obstructed the satellite is, the smaller the impact of the satellite's observation data on the receiver's positioning is considered to be.

[0063] Step 104: Determine the positioning information of the receiver according to the influence weights of the updated observation data of multiple satellites.

[0064] In one possible implementation method, the influence weight of the satellite's observation data on the receiver's positioning information is updated according to the satellite's obstruction status, and the receiver's positioning information is determined based on the influence weights of the updated observation data of multiple satellites.

[0065] In this solution, the receiver acquires observation data transmitted by satellites while receiving images captured by cameras. Based on the satellite observation data, the receiver determines the mapping positions of multiple satellites within the image. The different mapping positions determine the degree of influence of each satellite on the receiver's positioning. Based on the degree of obstruction of a satellite and the quality index corresponding to the satellite's observation data, the influence weight of the satellite's observation data can be accurately determined. This effectively mitigates signal obstruction and multipath effects, improving the receiver's positioning accuracy.

[0066] In one possible implementation method, in step 102, after the receiver acquires multiple images captured by the camera device, it divides each image into a sky area and a non-sky area. This application does not limit the image processing method.

[0067] In one possible implementation, in step 102, the satellite's elevation and azimuth are determined based on the satellite's observation data. The elevation indicates the distance between the satellite and the receiver in polar coordinates, and the azimuth indicates the angle between the satellite and the receiver in polar coordinates. Polar coordinates refer to a coordinate system established with the receiver as the origin. A polar coordinate diagram is matched with an image obtained by a camera to determine the satellite's mapped position in the corresponding image. The azimuth is an angle measured clockwise relative to north, with 0 degrees representing north, 90 degrees east, 180 degrees south, and 270 degrees west. The elevation is the angle from the horizon to the satellite, with 90 degrees representing zenith. A satellite sky map (i.e., an image obtained by mapping satellites to corresponding images captured by a camera) is a sky map centered on the observation location (i.e., the center of the corresponding image captured by the camera) based on each satellite's azimuth and elevation. The sky map (i.e., the image captured by the camera) is a circular coordinate system obtained by transforming the X and Y coordinate systems. The variables here, altitude and azimuth, are equivalent to the X and Y components of a conventional coordinate system. Altitude indicates the satellite's distance from the center of the circle (i.e., the center of the image captured by the camera), while azimuth indicates the satellite's position, which in turn determines the coordinates within the sky map.

[0068] In one possible implementation method, in step 103, the influence weight of the satellite's observation data is determined based on the satellite's obstruction status and the quality index corresponding to the satellite's observation data. This includes: if the satellite's corresponding signal type is a direct signal type, the influence weight information of the satellite's observation data on the receiver's positioning is not changed; if the satellite's corresponding signal type is an obstruction type, the influence weight information of the satellite's observation data on the receiver's positioning is set to zero; if the satellite's corresponding signal type is an ambiguous signal type, the influence weight information of the satellite's observation data on the receiver's positioning is updated. This solution determines the influence weight information of the satellite's observation data on the receiver's positioning based on the satellite's corresponding signal type, and accurately determines the influence weight of the satellite's observation data based on the degree of satellite obstruction. This effectively addresses signal shielding and multipath effects, improving positioning accuracy.

[0069] In one possible implementation, if the number of satellites with non-zero weights after updating is less than a fourth threshold, a supplementary satellite set is determined from the satellites whose weights have been reset to zero; the sum of the number of satellites in the supplementary satellite set and the number of satellites with non-zero weights is greater than or equal to the fourth threshold. The fourth threshold is the minimum number of satellites required for receiver positioning. Exemplarily, the fourth threshold is 4, meaning that at least 4 satellites are required to locate the receiver. In the case of severe obstruction, such as when all satellites are obstructed but the receiver still needs to be located, a number of satellites exceeding the fourth threshold is selected from the obstructed satellites to locate the receiver. In this solution, if the number of satellites is less than the fourth threshold, the receiver's position cannot be determined. Therefore, when the number of satellites with non-zero weights after updating is less than the fourth threshold, the number of available satellites is increased, thereby enabling accurate determination of the receiver's position.

[0070] In one possible implementation, a supplementary satellite set is determined based on a quality indicator of observation data corresponding to each satellite among the satellites whose weights are reset to zero. For example, the quality indicators of the observation data corresponding to each satellite are sorted from high to low, and satellites with higher quality indicators and a number greater than or equal to a fourth threshold are selected to form the supplementary satellite set.

[0071] In one possible implementation method, in step 103, the influence weight of the satellite's observation data is determined based on the satellite's obstruction status and the quality index corresponding to the satellite's observation data. The method also includes: obtaining an adjustment strategy and adjustment threshold corresponding to the satellite's signal type; determining an adjustment action for the satellite's observation data from the adjustment strategy based on the relationship between the quality index corresponding to the satellite's observation data and the adjustment threshold; and the adjustment action represents information about the influence weight on the satellite's observation data. This solution determines adjustment strategies and adjustment thresholds based on different signal types, thereby enabling processing of satellites with different signal types. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on receiver positioning, thereby effectively addressing signal shielding and multipath effects and improving positioning accuracy.

[0072] In one possible implementation method, if the signal type of the satellite is a direct signal type, it means that the satellite is located in the sky area in the image; the adjustment threshold is a first threshold, and the adjustment strategy includes retention and demotion; retention means not changing the influence weight information of the observation data sent by the satellite; and demotion means updating the influence weight information of the observation data sent by the satellite.

[0073] In one possible implementation method, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a first threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index.

[0074] In one possible implementation method, if the satellite signal type is an occlusion signal type, indicating that the satellite is located in a non-sky area of ​​the image; the adjustment threshold is a second threshold, and the adjustment strategy includes de-weighting and deletion. The deletion is to set the influence weight information of the observation data sent by the satellite to zero.

[0075] In one possible implementation method, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a second threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index; if the quality index corresponding to the observation data sent by the satellite is less than the second threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero.

[0076] In one possible implementation method, if the signal type of the satellite is a fuzzy signal type, it means that the satellite is located at the junction of the sky area and the non-sky area in the image; the adjustment threshold is a third threshold, and the adjustment strategy includes retention, demotion and deletion.

[0077] In one possible implementation method, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the maximum value of the third threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than or equal to the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the quality index corresponding to the observation data sent by the satellite is within the range of the third threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index.

[0078] In a possible implementation method, the first threshold, the second threshold, and the third threshold are divided into threshold ranges determined through a large number of experiments.

[0079] The above scheme can accurately process satellites with different signal types. Furthermore, it can accurately determine the impact of satellites with different degrees of obstruction on the receiver positioning. Therefore, it can effectively solve the signal shielding and multipath effects and improve the accuracy of positioning.

[0080] In one possible implementation method, updating the weight information of the impact of the observation data transmitted by the satellite on the receiver's positioning includes: obtaining a weight matrix corresponding to the multiple satellites; the weight matrix is ​​used to indicate the degree of impact of the observation data on the receiver's positioning; the observation data can be the observation data of each satellite, or the degree of impact of a combination of observation data of each satellite and a preset (meeting certain requirements) reference satellite on the receiver. Determining a scaling factor based on a quality indicator corresponding to the observation data and an ideal quality indicator; updating the weight matrix based on the scaling factor; and updating the weight information of the impact of the observation data transmitted by the satellite on the receiver's positioning based on the updated weight matrix. This solution determines a scaling factor based on the quality index corresponding to the observation data. Therefore, the scaling factor can accurately reflect the impact of observation data of different qualities on the receiver positioning. If the quality index corresponding to the satellite is higher, the weight information of the impact of the observation data sent by the satellite on the receiver positioning is increased; if the quality index corresponding to the satellite is lower, the weight information of the impact of the observation data sent by the satellite on the receiver positioning is reduced. Therefore, the impact of observation data of different qualities on the receiver positioning can be accurately determined, and signal shielding and multipath effects can be well resolved, thereby improving positioning accuracy.

[0081] In one possible implementation, the quality metric refers to the carrier-to-noise ratio (CNR). CNR is a key indicator of signal reception quality and is defined as the ratio between the received signal power and the receiver noise. For low-cost, high-sensitivity mobile phone receiving antennas, CNR is highly correlated with the accuracy of observations. Using CNR for weighting can better reflect the characteristics of GNSS observations.

[0082] In one possible implementation method, the calculation method of the classic carrier-to-noise ratio random model is shown in the following formula (1):

[0083] The value of α is related to the wavelength of the carrier signal and the internal tracking hardware of the receiver. For example, the L1 frequency and L2 frequency of GPS are respectively α1=0.00224m 2 HZ, α2=0.00077m 2 HZ; Carrier-to-noise ratio (C / N0) is an important indicator to measure the quality of the signal received by the receiver.

[0084] In one possible implementation method, the calculation method of α is shown in the following formula (2):

[0085] Where B is the phase tracking loop bandwidth (Hz) and λ is the carrier phase wavelength (m).

[0086] In one possible implementation method, the scaling factor is calculated as shown in the following formula (3):

[0087] in, is the ideal carrier-to-noise ratio of system s at frequency i, is the measured carrier-to-noise ratio of system s at frequency i.

[0088] In one possible implementation method, system s refers to the GNSS systems of different countries and regions. The complementarity and integration of GNSS systems in different countries and regions is also an important way to improve positioning accuracy. Through the synergy between multiple systems, signal shielding and multipath effects can be reduced.

[0089] In one possible implementation method, the ideal carrier-to-noise ratio refers to data acquired by the same receiver in the same time period in an open, unobstructed environment with good vision, no electromagnetic interference, and good weather conditions.

[0090] In another possible implementation method, the scaling factor is calculated as shown in the following formula (4):

[0091] Where k0 and k1 are two constant thresholds. Typically, k0 = 1.0 and k1 = 3.0. are the standardized residuals.

[0092] In one possible implementation, the standardized residuals The calculation method is shown in the following formula (5):

[0093] Among them, v i is the i-th element of the residual vector v, is the covariance matrix Q vv The i-th diagonal element of is the posterior variance factor.

[0094] In one possible implementation, the posterior variance factor The calculation method is shown in the following formula (6):

[0095] Where r is the number of redundant measurements and the weight matrix P is the inverse matrix of Q.

[0096] In one possible implementation method, the weight matrix P is expressed as shown in the following formula (7):

[0097] Among them, P 1n P represents the inverse of the covariance between the first observation and the nth observation when the unit weight variance is 1; 2nP represents the inverse of the covariance between the second observation and the nth observation when the unit weight variance is 1; nn It represents the inverse of the covariance between the nth observation and the nth observation when the unit weight variance is 1.

[0098] In one possible implementation, the updated weight matrix The expression of is shown in the following formula (8):

[0099] Among them, γ ij is the scaling factor,

[0100] In one possible implementation method, in the above step 102, after the receiver obtains multiple images captured by the camera device, it divides each image into a sky area and a non-sky area, including: obtaining a sky map of the current position through the camera device, and using image processing to identify and segment the sky area and the non-sky area. The image processing method can be an image segmentation model, the image segmentation model can be a sky segmentation model, the sky segmentation model can be a Unet model, and of course other image segmentation methods can be used, which is not limited in this application. The sky segmentation model can also be a CNN model, a GNN model, etc., which is not limited in this application.

[0101] In one possible implementation method, a method for training a sky segmentation model is shown in FIG2 , and the method includes the following steps:

[0102] Step 201: Data preparation.

[0103] In one possible implementation, a dataset of images featuring the sky and other objects is collected using a simple camera. A subset of images is selected from the dataset, and corresponding labels are created for them. The sky region is identified through manual annotation or segmentation using image processing software. These serve as training and test sets. The training set is used for subsequent model training, while the test set is used to test the model's ability to identify the sky region. The labels are binary images of the same size as the images, with the sky region set to 1 and the rest of the image set to 0. A subset of these images is then manually identified to distinguish the sky region from the rest of the image.

[0104] Step 202: data preprocessing.

[0105] One possible implementation involves adjusting the image size and format, bringing the image and labels to the same size and resolution to fit the model's input requirements. Rotating, flipping, and scaling the images can also be performed to increase data diversity and improve the model's generalization capabilities.

[0106] Step 203: Model preparation.

[0107] One possible implementation involves using the Unet model. Unet is a deep learning model specifically designed for image segmentation. Its network structure consists of an encoder and a decoder. This model is designed to learn the features of each region in an image and accurately segment it. The encoder captures high-level, abstract features in the image, while the decoder maps these features back to the original resolution through upsampling and skip connections, generating detailed segmentation results.

[0108] Step 204: model training.

[0109] In one possible implementation, the model is fed with a prepared training and test set, along with their corresponding labels. The model aims to accurately segment the sky and non-sky regions of the input image. A loss function is then set to calculate the difference between the network's predictions and the labels. Hyperparameters such as the learning rate, optimizer choice, and training batch size are then adjusted to determine the optimal training strategy, ensuring rapid and stable model convergence on the dataset.

[0110] Step 205: Model evaluation.

[0111] One possible implementation involves evaluating the model's performance using the test set obtained during the data preparation step. Specifically, the model's accuracy in identifying sky regions is evaluated based on its segmentation accuracy on the test set. By applying the model to sky segmentation on the test set, we can comprehensively assess its performance in real-world scenarios and determine its accuracy and robustness for this segmentation task.

[0112] Step 206: Model usage.

[0113] In one possible implementation method, an evaluated accurate and robust sky segmentation model is used to segment the sky image acquired by the camera device to identify the sky area and non-sky area of ​​all data.

[0114] One possible implementation involves calculating the satellite's altitude and azimuth. The received navigation message is parsed to extract the ephemeris data. This data includes the satellite's orbital parameters (such as satellite position, velocity, and orbital inclination), as well as the estimated value of the predicted satellite position at the receiving epoch. The receiver position at the current epoch is calculated, and the satellite's altitude and azimuth are determined using the acquired satellite and receiver position information.

[0115] One possible implementation method determines the satellite signal type based on the results of image segmentation. The acquired satellite elevation and azimuth information is matched with the segmented image. The satellite is then mapped onto a sky map using these information. Based on the image matching results, the observed signal is then classified into three categories: an occluded signal, characterized by being located in a non-sky area; an ambiguous signal, located at the boundary between a non-sky area and a sky area, where the signal type cannot be accurately identified; and a direct signal, located in the sky area.

[0116] Based on the same technical concept, FIG3 exemplarily shows a GNSS navigation and positioning device 300 that can be assisted by a camera device provided in an embodiment of the present application. As shown in FIG3 , the device includes: an acquisition unit 301 and a determination unit 302. The acquisition unit 301 is configured to acquire observation data of multiple satellites and multiple images captured by the camera device through a receiver; the camera device and the receiver are located in the same location area and the camera device captures images at an angle facing the sky; the determination unit 302 is configured to determine, for any satellite, the mapping position of the satellite on the corresponding image based on the observation data of the satellite; determine the obstruction status of the satellite based on the mapping position of the satellite on the corresponding image; the mapping position is used to characterize the positional relationship between the satellite and the sky area in the image; the corresponding image and the observation data of the satellite belong to the same time period; for any satellite, determine the influence weight of the observation data of the satellite based on the obstruction status of the satellite and the quality index corresponding to the observation data of the satellite; and determine the positioning information of the receiver based on the influence weights of the updated observation data of multiple satellites.

[0117] In one possible implementation method, the determination unit 302 is used to determine the altitude angle of the satellite and the azimuth angle of the satellite based on the observation data of the satellite; wherein the altitude angle is used to indicate the distance between the satellite and the receiver in polar coordinates, and the azimuth angle is used to indicate the angle between the satellite and the receiver in polar coordinates; based on the altitude angle of the satellite and the azimuth angle of the satellite, the mapping position of the satellite on the corresponding image is determined.

[0118] In one possible implementation method, the determination unit 302 is used to determine that the satellite is in a direct state if the mapping position of the satellite on the corresponding image belongs to the sky area; to determine that the satellite is in an obstructed state if the mapping position of the satellite on the corresponding image belongs to the non-sky area; and to determine that the satellite is in a blurred state if the mapping position of the satellite on the corresponding image belongs to the boundary between the sky area and the non-sky area.

[0119] In one possible implementation method, the determination unit 302 is used to, if the signal type corresponding to the satellite is a direct signal type, not change the influence weight information of the observation data corresponding to the satellite on the receiver positioning; if the signal type corresponding to the satellite is an occlusion type, set the influence weight information of the observation data corresponding to the satellite on the receiver positioning to zero; if the signal type corresponding to the satellite is an ambiguous signal type, update the influence weight information of the observation data corresponding to the satellite on the receiver positioning.

[0120] In one possible implementation method, an acquisition unit 301 is used to obtain an adjustment strategy and an adjustment threshold corresponding to the signal type of the satellite; a determination unit 302 is used to determine an adjustment action for the observation data of the satellite from the adjustment strategy based on a relationship between a quality indicator corresponding to the observation data of the satellite and the adjustment threshold; the adjustment action represents information on an impact weight on the observation data of the satellite.

[0121] In one possible implementation method, if the satellite signal type is a direct signal type, the adjustment threshold is a first threshold, and the adjustment strategy includes retention and downgrading; if the satellite signal type is an obstructed signal type, the adjustment threshold is a second threshold, and the adjustment strategy includes downgrading and deletion; if the satellite signal type is an ambiguous signal type, the adjustment threshold is a third threshold, and the adjustment strategy includes retention, downgrading, and deletion;

[0122] Determination unit 302, for the satellite signal type is a direct signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a first threshold, then retain the influence weight information of the observation data sent by the satellite; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, then update the influence weight information of the observation data sent by the satellite on the positioning of the receiver according to the quality index; the satellite signal type is an occlusion signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to a second threshold, then update the influence weight information of the observation data sent by the satellite on the positioning of the receiver according to the quality index; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, then update the influence weight information of the observation data sent by the satellite on the positioning of the receiver according to the quality index; If the indicator is less than the second threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the signal type of the satellite is a fuzzy signal type, if the quality indicator corresponding to the observation data sent by the satellite is greater than or equal to the maximum value of the third threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality indicator corresponding to the observation data sent by the satellite is less than or equal to the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the quality indicator corresponding to the observation data sent by the satellite is within the range of the third threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality indicator.

[0123] In one possible implementation method, an acquisition unit 301 is used to obtain a weight matrix corresponding to the multiple satellites; the weight matrix is ​​used to indicate the degree of influence of the observation data on the receiver positioning; a determination unit 302 is used to determine a scaling factor based on a quality index corresponding to the observation data and an ideal quality index; the weight matrix is ​​updated according to the scaling factor; and based on the updated weight matrix, the weight information of the influence of the observation data sent by the satellite on the receiver positioning is updated.

[0124] In a possible implementation method, the quality indicator refers to a carrier-to-noise ratio.

[0125] In one possible implementation method, the determination unit 302 is configured to determine a supplementary satellite set from the satellites whose weights are reset to zero if the number of satellites with non-zero weights after the update is less than a fourth threshold; wherein the sum of the number of satellites in the supplementary satellite set and the number of satellites with non-zero weights is greater than or equal to the fourth threshold.

[0126] In a possible implementation method, the period of the camera device collecting images is consistent with the period of the receiver acquiring observation data of multiple satellites.

[0127] Based on the same technical concept, an embodiment of the present application provides a GNSS navigation and positioning device 400 that can be assisted by a camera. This GNSS navigation and positioning device 400 that can be assisted by a camera can be, for example, a computing device. As shown in Figure 4, a GNSS navigation and positioning device 400 that can be assisted by a camera includes at least one processor 401 and a memory 402 connected to the at least one processor. The specific connection medium between the processor 401 and the memory 402 is not limited in this embodiment of the application. In Figure 4, the processor 401 and the memory 402 are connected via a bus as an example. Buses can be divided into address buses, data buses, control buses, etc.

[0128] In an embodiment of the present application, the memory 402 stores instructions that can be executed by at least one processor 401. By executing the instructions stored in the memory 402, the at least one processor 401 can execute the above-mentioned GNSS navigation and positioning method that can be assisted by a camera device.

[0129] Processor 401 serves as the control center for the camera-assisted GNSS navigation and positioning device 400. It can connect various components of the computer device using various interfaces and circuits, and configure resources by running or executing instructions stored in memory 402 and accessing data stored in memory 402. Optionally, processor 401 may include one or more determination units. Processor 401 may integrate an application processor and a modem processor, with the application processor primarily processing the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 401. In some embodiments, processor 401 and memory 402 may be implemented on the same chip, or in some embodiments, they may be implemented on separate chips.

[0130] The processor 401 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit (ASIC), a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0131] The memory 402 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 402 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 402 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 402 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0132] An embodiment of the present application further provides a computer-readable storage medium storing a computer-executable program, which is used to enable a computer to execute a GNSS navigation and positioning method that can be assisted by a camera device as listed in any of the above methods.

[0133] An embodiment of the present application provides a computer program product, including a computer program that can be executed by a computer device. When the program is run on the computer device, the computer device executes a GNSS navigation and positioning method that can be assisted by a camera device listed in any of the above methods.

[0134] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0135] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each flow and / or box in the flow chart and / or block diagram, as well as the combination of the flow chart and / or box in the flow chart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more flow charts and / or one or more boxes in the block diagram.

[0136] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0138] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A GNSS navigation and positioning method assisted by a camera device, characterized in that, Including: Obtaining observation data of multiple satellites through a receiver and obtaining multiple images collected by an imaging device; The imaging device and the receiver are located in the same location area, and the imaging device collects images at an angle facing the sky; For any satellite, determining the mapping position of the satellite on the corresponding image according to the observation data of the satellite; determining the occlusion status of the satellite according to the mapping position of the satellite on the corresponding image; wherein, the mapping position is used to characterize the positional relationship between the satellite and the sky area in the image; the corresponding image and the observation data of the satellite belong to the same time period; For any satellite, determining the influence weight of the observation data of the satellite according to the occlusion status of the satellite and the quality index corresponding to the observation data of the satellite; Determining the positioning information of the receiver according to the influence weights of the updated observation data of multiple satellites.

2. The method according to claim 1, characterized in that, The determining the mapping position of the satellite on the corresponding image according to the observation data of the satellite includes: Determining the elevation angle of the satellite and the azimuth angle of the satellite according to the observation data of the satellite; wherein, The elevation angle is used to indicate the distance of the satellite from the receiver in polar coordinates, and the azimuth angle is used to indicate the angle between the satellite and the receiver in polar coordinates; Determining the mapping position of the satellite on the corresponding image according to the elevation angle of the satellite and the azimuth angle of the satellite.

3. The method according to claim 1, characterized in that, The determining the occlusion status of the satellite according to the mapping position of the satellite on the corresponding image includes: If the mapping position of the satellite on the corresponding image belongs to the sky area, determining that the satellite is in a direct state; If the mapping position of the satellite on the corresponding image belongs to a non-sky area, determining that the satellite is in an occluded state; If the mapping position of the satellite on the corresponding image belongs to the junction of the sky area and the non-sky area, determining that the satellite is in a blurred state.

4. The method according to claim 3, characterized in that, The determining the influence weight of the observation data of the satellite according to the occlusion status of the satellite and the quality index corresponding to the observation data of the satellite includes: If the signal type corresponding to the satellite is a direct signal type, not changing the influence weight information of the observation data corresponding to the satellite on the positioning of the receiver; If the signal type corresponding to the satellite is an occlusion type, setting the influence weight information of the observation data corresponding to the satellite on the positioning of the receiver to zero; If the signal type corresponding to the satellite is a blurred signal type, updating the influence weight information of the observation data corresponding to the satellite on the positioning of the receiver.

5. The method according to claim 1, wherein The determining the influence weight of the observation data of the satellite according to the occlusion status of the satellite and the quality index corresponding to the observation data of the satellite includes: Obtaining the adjustment strategy and adjustment threshold corresponding to the signal type of the satellite; Determining the adjustment action for the observation data of the satellite from the adjustment strategy according to the relationship between the quality index corresponding to the observation data of the satellite and the adjustment threshold; the adjustment action characterizes the influence weight information of the observation data of the satellite.

6. The method according to claim 5, wherein Obtaining an adjustment strategy and an adjustment threshold corresponding to the signal type of the satellite includes: If the signal type of the satellite is a direct signal type, the adjustment threshold is a first threshold, and the adjustment strategy includes retention and downweighting; if the signal type of the satellite is an occluded signal type, the adjustment threshold is a second threshold, and the adjustment strategy includes downweighting and deletion; if the signal type of the satellite is a fuzzy signal type, the adjustment threshold is a third threshold, and the adjustment strategy includes retention, downweighting, and deletion; Determining an adjustment action for the observation data of the satellite from the adjustment strategy according to the relationship between the quality index corresponding to the observation data of the satellite and the adjustment threshold includes: When the signal type of the satellite is a direct signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the first threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than the first threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index; When the signal type of the satellite is an occluded signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the second threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index; if the quality index corresponding to the observation data sent by the satellite is less than the second threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; When the signal type of the satellite is a fuzzy signal type, if the quality index corresponding to the observation data sent by the satellite is greater than or equal to the maximum value of the third threshold, the influence weight information of the observation data sent by the satellite is retained; if the quality index corresponding to the observation data sent by the satellite is less than or equal to the minimum value of the third threshold, the influence weight information of the observation data corresponding to the satellite on the receiver positioning is set to zero; if the quality index corresponding to the observation data sent by the satellite is within the range of the third threshold, the influence weight information of the observation data sent by the satellite on the receiver positioning is updated according to the quality index.

7. The method according to claim 4 or 6, characterized in that Updating the influence weight information of the observation data sent by the satellite on the receiver positioning includes: Obtaining a weight matrix corresponding to the multiple satellites; the weight matrix is used to indicate the influence degree of the observation data on the receiver positioning; Determining a scaling factor according to the quality index corresponding to the observation data and an ideal quality index; Updating the weight matrix according to the scaling factor; Updating the influence weight information of the observation data sent by the satellite on the receiver positioning according to the updated weight matrix.

8. The method according to claim 7, characterized in that The quality index refers to the carrier-to-noise ratio.

9. The method according to claim 7, wherein Determining the positioning information of the receiver according to the influence weights of the updated observation data of multiple satellites includes: If the number of satellites with non-zero updated weights is less than a fourth threshold, a supplementary satellite set is determined from the satellites with zero weights; wherein, the sum of the number of satellites in the supplementary satellite set and the number of satellites with non-zero weights is greater than or equal to the fourth threshold.

10. The method according to claim 1, characterized in that, The method further includes: The period for the imaging device to acquire images is consistent with the period for the receiver to obtain the observation data of multiple satellites.

Images