An iterative optimization method for positioning coordinates based on satellite communication

Abstract

The application provides an iterative optimization method based on satellite communication positioning coordinates, which comprises an effective coordinate calculation step: obtaining N sets of satellite positioning latitude and longitude coordinate data, calculating the mean value of the N sets of latitude and longitude coordinate data to obtain a center point coordinate; calculating the secant spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinate; taking the derivative of the secant spherical distance as a weight value, and performing weighted average calculation on the N sets of satellite positioning latitude and longitude coordinates to obtain a current effective latitude and longitude coordinate value; an iterative optimization step: repeatedly performing the effective coordinate calculation step to obtain the satellite positioning latitude and longitude coordinate value after iterative optimization. The application uses the secant spherical distance from the center point to each coordinate point as the weight value to calculate the effective latitude and longitude value, excludes the influence of non-effective coordinates from the continuous real-time satellite coordinate value, and dynamically and iteratively approaches the actual correct satellite coordinate positioning latitude and longitude value based on the historical and current effective coordinate data.

Description

Technical Field

[0001] This invention relates to the field of satellite communication and positioning technology, and specifically to an iterative optimization method based on satellite communication and positioning coordinates, which is particularly suitable for scenarios involving continuous optimization of latitude and longitude coordinates of ground satellite positioning hardware at fixed locations. Background Technology

[0002] Global Navigation Satellite System (GNSS) provides location, velocity, and time information to ground users via satellites and is widely used in geodesy, deformation monitoring, urban rail transit, autonomous driving, and various location services. However, satellite signals are susceptible to interference from the external environment, such as obstruction by tall buildings, tree canopies, and severe weather, leading to positioning inaccuracies. Abnormal observations can cause a sharp decline in positioning performance.

[0003] For ground-based satellite positioning hardware in fixed locations (such as satellite positioning terminals in medical insurance pharmacies, base station monitoring equipment, etc.), their actual physical location is fixed, but the latitude and longitude coordinates output by the satellite positioning system often fluctuate and jump. This problem has not been effectively solved in the existing technology.

[0004] The simplest and most direct method in existing technology is to directly use the latitude and longitude coordinates output by the satellite positioning hardware in a single operation as the final positioning result. The main drawback of this approach is that single-point satellite coordinates are easily affected by various factors such as the performance of the satellite receiver antenna, satellite signal quality, cloud cover, weather conditions, and environmental electromagnetic interference, leading to inaccurate positioning, data jumps, and other problems. The reliability and stability of the positioning result cannot be guaranteed. Furthermore, the existing method of averaging multiple sets of satellite coordinates cannot eliminate the influence of large deviations in coordinate values ​​on the average, which can also result in positioning inaccuracies.

[0005] Most existing coordinate optimization methods process raw satellite observations (pseudorange, carrier phase, etc.), requiring a large amount of raw observation data to be obtained at the signal processing level. However, in practical applications (such as satellite positioning terminals in medical insurance pharmacies), only the latitude and longitude coordinates output by the satellite positioning hardware can be obtained, and the raw observation data cannot be acquired.

[0006] Existing technologies are mostly single-process or limited-process, lacking technical means to continuously iterate based on historical valid data and gradually approximate the real coordinates. Summary of the Invention

[0007] To address the various shortcomings of existing technologies, this invention provides an iterative optimization method based on satellite communication positioning coordinates. This method uses multiple sets of satellite coordinate values ​​for calculation, and uses the semi-sine spherical distance from the center point to each coordinate point as a weight value to calculate the effective latitude and longitude values. It eliminates the influence of ineffective coordinates from continuous real-time satellite coordinate values, and dynamically and iteratively approximates the actual correct satellite coordinate positioning latitude and longitude values ​​based on historical and current effective coordinate data.

[0008] The present invention achieves the above objectives through the following technical solutions: An iterative optimization method based on satellite communication positioning coordinates includes: Valid coordinate calculation steps: Obtain N sets of satellite positioning latitude and longitude coordinate data, calculate the mean of the N sets of latitude and longitude coordinate data to obtain the center point coordinates; calculate the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates; use the derivative of the semi-spherical distance as a weight value to calculate the weighted average of the N sets of satellite positioning latitude and longitude coordinates to obtain the current valid latitude and longitude coordinate values; Iterative optimization steps: Repeat the effective coordinate calculation steps to obtain the 1st to nth effective latitude and longitude coordinate values ​​in sequence; calculate the center point coordinates of the 1st to nth effective latitude and longitude coordinate values; calculate the semi-spherical distance between each effective latitude and longitude coordinate value and the center point coordinates; use the derivative of the semi-spherical distance as the weight value to calculate the weighted average of the 1st to nth effective latitude and longitude coordinate values ​​to obtain the iteratively optimized satellite positioning latitude and longitude coordinate values.

[0009] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, before acquiring N sets of satellite positioning latitude and longitude coordinate data, a data validity pre-screening step is also included: Obtain M sets of raw satellite positioning latitude and longitude coordinate data continuously output by the ground satellite positioning hardware, where M > N; perform validity determination on each of the M sets of raw satellite positioning latitude and longitude coordinate data: determine whether the longitude and latitude values ​​in each set of raw satellite positioning latitude and longitude coordinate data simultaneously meet the conditions that the longitude value is greater than 0 and less than 180 and the latitude value is greater than 0 and less than 90; mark the raw satellite positioning latitude and longitude coordinate data that do not meet the above conditions as invalid data and discard them; retain the raw satellite positioning latitude and longitude coordinate data that meet the above conditions as valid data, until N sets of valid satellite positioning latitude and longitude coordinate data are accumulated.

[0010] According to an iterative optimization method based on satellite communication positioning coordinates provided by the present invention, the mean of N sets of latitude and longitude coordinate data is calculated to obtain the center point coordinates, including: Calculate the arithmetic mean of all longitude values ​​in the N sets of satellite positioning latitude and longitude coordinate data as the longitude value of the center point, and the arithmetic mean of all latitude values ​​as the latitude value of the center point; The formula for calculating the longitude value of the center point is:

[0011] The formula for calculating the latitude value of the center point is:

[0012] Where N is the total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation. X i For the longitude value in the i-th group of satellite positioning coordinate data, Y i represents the latitude value in the i-th group of satellite positioning coordinate data.

[0013] According to an iterative optimization method based on satellite communication positioning coordinates provided by the present invention, the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates is calculated, including: Based on the longitude and latitude values ​​of the center point, and the longitude value in the i-th set of satellite positioning coordinate data. X i and latitude value Y i Calculate the spherical distance d between the i-th satellite positioning coordinate point and the center point according to the following semi-versus formula. i :

[0014] Where R is the Earth's radius. The coordinates of the center point, Let be the longitude and latitude values ​​in the i-th group of satellite positioning coordinate data.

[0015] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, in the effective coordinate calculation step, the semi-sine spherical distance d between the i-th satellite positioning coordinate point and the center point is used. i The weight value of the i-th coordinate point is determined as follows: w i :

[0016] in, f For the spherical distance d in the semi-sine direction i The monotonically decreasing function makes the semi-sine spherical distance d i The larger the value, the higher the corresponding weight value. w i The smaller; Based on weight values w i Calculate the comprehensive weight value of the i-th coordinate point ; Based on the weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average using the following formula. Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates: in, N The total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation. X i For the longitude value in the i-th group of satellite positioning coordinate data, Y i The latitude value is from the i-th set of satellite positioning coordinate data. This represents the comprehensive weight value corresponding to the i-th set of coordinate data.

[0017] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, in the iterative optimization step, each iteration is based on all the currently accumulated valid satellite positioning latitude and longitude coordinate data, calculates the current valid latitude and longitude coordinate value according to the valid coordinate calculation steps, and performs a weighted average calculation on all the valid latitude and longitude coordinate values ​​obtained by continuous iteration to continuously approximate the actual latitude and longitude coordinate value.

[0018] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, in the effective coordinate calculation step, the effective latitude and longitude coordinate values ​​output in the previous M consecutive historical calculation cycles are taken to construct a historical coordinate sequence; based on the time position of the i-th satellite positioning coordinate point in the historical coordinate sequence and the coordinate change between the i-th coordinate point and the adjacent historical coordinate points, the temporal continuity evaluation value of the coordinate point is calculated. t i ; Based on time continuity assessment value t i Determine the second-level weight adjustment coefficient for the i-th coordinate point. g ( t i ),in g For the evaluation value of time continuity t i The monotonic function makes the second-level weight adjustment coefficient larger when the time continuity evaluation value is higher; Based on the first-level weight value w i Adjustment coefficient for the second level weight g ( t i The product of ) is used to calculate the comprehensive weight value of the i-th coordinate point. :

[0019] Based on the comprehensive weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates.

[0020] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, after calculating the current valid latitude and longitude coordinates in each iteration, an iterative convergence determination step is also included: Obtain the valid latitude and longitude coordinates obtained from the previous iteration. P k 1=( X k 1, Y k 1) and the effective latitude and longitude coordinates obtained from the current iteration. P k =( X k , Y k ); Calculate the current valid latitude and longitude coordinates. P k Compared with the previous valid latitude and longitude coordinates P k The coordinate change Δ between 1 k ; The coordinate change Δ k With preset convergence threshold ε Comparison: When Δ k < ε When the iteration is considered to have converged, the current valid latitude and longitude coordinates are determined. P k This serves as the final localization result output, stopping subsequent iterations of the calculation. When Δ k ≥ ε If the iteration has not yet converged, proceed to the next iteration. Among them, the coordinate change Δ k It represents the difference between latitude and longitude coordinates or the semi-sine spherical distance.

[0021] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, when the satellite positioning hardware is equipped with an inertial sensor, the inertial data can be used to assist in verifying the validity of the satellite positioning latitude and longitude coordinates: if the satellite positioning latitude and longitude coordinates change but the inertial sensor data shows that the hardware has not moved, then the satellite positioning latitude and longitude coordinates are determined to be invalid data and are discarded; conversely, if the inertial data shows that the hardware has moved, the iterative strategy can be adjusted accordingly.

[0022] According to the iterative optimization method based on satellite communication positioning coordinates provided by the present invention, an alarm is automatically triggered when the following abnormal states are detected: The iterations failed to converge after multiple consecutive iterations. The coordinate values ​​output by the iteration exceed the preset geofence range; The percentage of valid data remains below the preset threshold. The deviation between the iteration results and the historical true values ​​continues to increase. Therefore, compared with the prior art, the iterative optimization method and system based on satellite communication positioning coordinates proposed in this invention have the following beneficial effects: 1. This invention does not rely on raw satellite observation data such as pseudorange and carrier phase. It only requires the latitude and longitude coordinates output by the satellite positioning hardware to complete the optimization calculation. It is suitable for practical application scenarios where only latitude and longitude coordinates can be obtained (such as satellite positioning terminals in medical insurance pharmacies) and has wide applicability.

[0023] 2. This invention uses the semi-sine spherical distance between the coordinate point and the center point as the basis for weight allocation, rather than relying on external parameters such as signal strength and signal-to-noise ratio. This makes the weight allocation based entirely on the quality characteristics of the coordinate data itself, without the need for any additional sensors or observation data.

[0024] 3. This invention determines the weights using a monotonically decreasing function of the semi-sine spherical distance, so that coordinate points farther from the center point (which are more likely to be outliers affected by environmental interference) are assigned smaller weights, thereby effectively reducing the impact of outliers on the final positioning results.

[0025] 4. This invention uses the semi-sine formula to calculate spherical distances, fully considering the influence of the Earth's curvature on the calculation of latitude and longitude distances. Compared with the Euclidean distance calculation method that treats latitude and longitude as planar coordinates, the distance calculation of this invention is more accurate and the weight allocation is more reasonable.

[0026] 5. This invention adopts a two-level architecture of effective coordinate calculation → iterative weighted optimization. As data accumulates and the number of iterations increases, it gradually approaches the true coordinate value, and the positioning accuracy continues to improve.

[0027] 6. Before entering any optimization calculation, the present invention performs a validity pre-screening of the original latitude and longitude coordinate data, eliminating invalid data with latitude and longitude values ​​of 0 or negative values, ensuring from the source that all coordinate data participating in the calculation are valid data, and avoiding the contamination of the optimization process by invalid data.

[0028] 7. This invention achieves autonomous convergence determination and intelligent termination of the iteration process by comparing the coordinate change between two adjacent iterations with a preset threshold, thus avoiding the waste of computing resources and increased power consumption caused by infinite iteration while ensuring positioning accuracy.

[0029] 8. In the preferred embodiment of the present invention, a second-level weight based on time continuity is introduced, which realizes the dual-dimensional fusion of spatial distance weight and time consistency weight, which can effectively identify and suppress instantaneous coordinate jumps, while enhancing the contribution of stable coordinate data to the positioning results.

[0030] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0031] Figure 1 This is a flowchart of an embodiment of an iterative optimization method based on satellite communication positioning coordinates according to the present invention.

[0032] Figure 2 This is a flowchart illustrating the effective coordinate calculation steps in an embodiment of an iterative optimization method based on satellite communication positioning coordinates according to the present invention.

[0033] Figure 3 This is a flowchart illustrating the iterative optimization steps in an embodiment of an iterative optimization method based on satellite communication positioning coordinates according to the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0035] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0036] An embodiment of an iterative optimization method based on satellite communication positioning coordinates See Figure 1 This embodiment provides an iterative optimization method based on satellite communication positioning coordinates, including the following steps: Valid coordinate calculation steps - S1: Obtain N sets of satellite positioning latitude and longitude coordinate data, calculate the mean of the N sets of latitude and longitude coordinate data to obtain the center point coordinates; calculate the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates; use the derivative of the semi-spherical distance as the weight value to perform a weighted average calculation on the N sets of satellite positioning latitude and longitude coordinates to obtain the current valid latitude and longitude coordinate values; Iterative optimization step - S2: Repeat the effective coordinate calculation step to obtain the 1st to nth effective latitude and longitude coordinate values ​​in sequence; calculate the center point coordinates of the 1st to nth effective latitude and longitude coordinate values; calculate the semi-spherical distance between each effective latitude and longitude coordinate value and the center point coordinates; use the derivative of the semi-spherical distance as the weight value to calculate the weighted average of the 1st to nth effective latitude and longitude coordinate values ​​to obtain the iteratively optimized satellite positioning latitude and longitude coordinate values.

[0037] In this embodiment, before acquiring N sets of satellite positioning latitude and longitude coordinate data, a data validity pre-screening step is also included: Obtain M sets of raw satellite positioning latitude and longitude coordinate data continuously output by the ground satellite positioning hardware, where M > N; perform validity determination on each of the M sets of raw satellite positioning latitude and longitude coordinate data: determine whether the longitude and latitude values ​​in each set of raw satellite positioning latitude and longitude coordinate data simultaneously meet the conditions that the longitude value is greater than 0 and less than 180 and the latitude value is greater than 0 and less than 90; mark the raw satellite positioning latitude and longitude coordinate data that do not meet the above conditions as invalid data and discard them; retain the raw satellite positioning latitude and longitude coordinate data that meet the above conditions as valid data, until N sets of valid satellite positioning latitude and longitude coordinate data are accumulated for subsequent calculations.

[0038] In the effective coordinate calculation step, the mean of N sets of latitude and longitude coordinate data is calculated to obtain the center point coordinates, including: Calculate the arithmetic mean of all longitude values ​​in the N sets of satellite positioning latitude and longitude coordinate data as the longitude value of the center point, and the arithmetic mean of all latitude values ​​as the latitude value of the center point; The formula for calculating the longitude value of the center point is:

[0039] The formula for calculating the latitude value of the center point is:

[0040] Where N is the total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation.X i For the longitude value in the i-th group of satellite positioning coordinate data, Y i represents the latitude value in the i-th group of satellite positioning coordinate data.

[0041] In the effective coordinate calculation step, the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates is calculated, including: Based on the longitude and latitude values ​​of the center point, and the longitude value in the i-th set of satellite positioning coordinate data. and latitude value Calculate the spherical distance d between the i-th satellite positioning coordinate point and the center point according to the following semi-versus formula. i :

[0042] Where R is the Earth's radius. The coordinates of the center point, Let be the longitude and latitude values ​​in the i-th group of satellite positioning coordinate data.

[0043] In the effective coordinate calculation step, the semi-spherical distance d between the i-th satellite positioning coordinate point and the center point is used. i The weight value of the i-th coordinate point is determined as follows: w i :

[0044] in, f For the spherical distance d in the semi-sine direction i The monotonically decreasing function makes the semi-sine spherical distance d i The larger the value, the higher the corresponding weight value. w i The smaller; Based on weight values w i Calculate the comprehensive weight value of the i-th coordinate point ; Based on the weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average using the following formula. Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates: in, N The total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation. X iFor the longitude value in the i-th group of satellite positioning coordinate data, Y i The latitude value is from the i-th set of satellite positioning coordinate data. This represents the comprehensive weight value corresponding to the i-th set of coordinate data.

[0045] In the iterative optimization step, each iteration is based on all the currently accumulated valid satellite positioning latitude and longitude coordinate data. The current valid latitude and longitude coordinate value is calculated according to the valid coordinate calculation steps. The weighted average of all valid latitude and longitude coordinate values ​​obtained by continuous iteration is calculated to continuously approximate the actual latitude and longitude coordinate values.

[0046] In the effective coordinate calculation step, the effective latitude and longitude coordinate values ​​output within the M consecutive historical calculation cycles prior to the current calculation cycle are taken to construct a historical coordinate sequence. Based on the time position of the i-th satellite positioning coordinate point in the historical coordinate sequence and the coordinate change between the i-th coordinate point and its adjacent historical coordinate points, the temporal continuity evaluation value of the coordinate point is calculated. t i ; Based on time continuity assessment value t i Determine the second-level weight adjustment coefficient for the i-th coordinate point. g ( t i ),in g For the evaluation value of time continuity t i The monotonic function makes the second-level weight adjustment coefficient larger when the time continuity evaluation value is higher; Based on the first-level weight value w i Adjustment coefficient for the second level weight g ( t i The product of ) is used to calculate the comprehensive weight value of the i-th coordinate point. :

[0047] Based on the comprehensive weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates.

[0048] In the iterative optimization step, after calculating the current valid latitude and longitude coordinates in each iteration, an iterative convergence determination step is also included: Obtain the valid latitude and longitude coordinates obtained from the previous iteration.P k 1=( X k 1, Y k 1) and the effective latitude and longitude coordinates obtained from the current iteration. P k =( X k , Y k ); Calculate the current valid latitude and longitude coordinates. P k Compared with the previous valid latitude and longitude coordinates P k The coordinate change Δ between 1 k ; The coordinate change Δ k With preset convergence threshold ε Comparison: When Δ k < ε When the iteration is considered to have converged, the current valid latitude and longitude coordinates are determined. P k This serves as the final localization result output, stopping subsequent iterations of the calculation. When Δ k ≥ ε If the iteration has not yet converged, proceed to the next iteration. Among them, the coordinate change Δ k It represents the difference between latitude and longitude coordinates or the semi-sine spherical distance.

[0049] In this embodiment, when the satellite positioning hardware is equipped with inertial sensors (such as accelerometers and gyroscopes), inertial data can be used to assist in verifying the validity of the satellite positioning latitude and longitude coordinates: if the satellite positioning latitude and longitude coordinates change but the inertial sensor data shows that the hardware has not moved, then the satellite positioning latitude and longitude coordinates are determined to be invalid data and are discarded; conversely, if the inertial data shows that the hardware has moved, then the iteration strategy can be adjusted accordingly.

[0050] In this embodiment, an alarm is automatically triggered when the following abnormal states are detected: The iterations failed to converge after multiple consecutive iterations. The coordinate values ​​output by the iteration exceed the preset geofence range; The percentage of valid data remains below the preset threshold. The deviation between the iteration results and the historical true values ​​continues to increase.

[0051] In the effective coordinate calculation step, such as Figure 2 As shown, 30 sets of satellite positioning latitude and longitude data are continuously acquired through ground satellite positioning hardware. Valid positioning coordinates are obtained by calculating the center point coordinates, the semi-sine spherical distance, and the weighted center point coordinates. 1. The ground satellite positioning hardware continuously acquires 30 sets of satellite positioning coordinates latitude and longitude. All 30 sets of positioning coordinates latitude and longitude are valid data, and there are no latitude and longitude values ​​that are 0 or negative. Calculate the mean of 30 sets of latitude and longitude values ​​to obtain the location latitude and longitude coordinates of the center point; location latitude and longitude values:

[0052] Calculate the semi-spherical distance between each point in the 30 sets of latitude and longitude coordinates and the center point:

[0053] Among them, R 6371km.

[0054] The derivative of the semi-sine spherical distance is used as the weighting value for each positioning point, reducing the weight of points farther from the center point and minimizing the impact of points farther from the center point on the overall result. The weighted average of 30 sets of satellite positioning coordinates is calculated based on the weight value of each latitude and longitude, thus obtaining the final coordinate value as the latitude and longitude coordinates of the satellite positioning at this moment: ,

[0055] By continuously obtaining latitude and longitude values ​​from satellite positioning, the final coordinates are calculated using the effective coordinate calculation module, with 30 sets of effective latitude and longitude values ​​as units.

[0056] The process involves sequentially stacking the first, second, third, and so on, up to the nth final latitude and longitude coordinates. For each final latitude and longitude coordinate, the center point coordinates are calculated, and the semi-spherical distance from each final latitude and longitude coordinate to the center point coordinates is calculated. The derivative of this semi-spherical distance is used as a weight value to calculate the weighted average of each final latitude and longitude coordinate, yielding the current satellite positioning latitude and longitude coordinates. This iterative calculation of the center point coordinates is then performed.

[0057] Specifically, such as Figure 3 As shown, 30 sets of valid satellite positioning coordinate values ​​are taken, and the final latitude and longitude coordinate values ​​of the first point are calculated through the valid coordinate calculation module; Take 30 sets of valid satellite positioning coordinate values, and calculate the temporary latitude and longitude coordinate values ​​of the second point through the valid coordinate calculation module; Calculate the center point of the first and second points where latitude and longitude coordinates are obtained; Calculate the semi-sine spherical distance from each coordinate point to the center point, and use the derivative of this distance as the weight value for that coordinate point; The weighted average of the first and second latitude and longitude coordinates is used to calculate the final latitude and longitude coordinates of the satellite positioning at this moment. In the nth calculation, 30 sets of valid satellite positioning coordinates are taken, and the temporary latitude and longitude coordinates of the nth point are calculated by the valid coordinate calculation module. Calculate the center point of the first n latitude and longitude coordinates; Calculate the semi-sine spherical distance from each coordinate point to the center point, and use the derivative of this distance as the weight value for that coordinate point; The weighted average of the first n latitude and longitude coordinates is used to calculate the final latitude and longitude coordinates of the satellite positioning at this moment.

[0058] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0059] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. An iterative optimization method based on satellite communication positioning coordinates, characterized in that, Includes the following steps: Valid coordinate calculation steps: Obtain N sets of satellite positioning latitude and longitude coordinate data, calculate the mean of the N sets of latitude and longitude coordinate data to obtain the center point coordinates; calculate the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates; use the derivative of the semi-spherical distance as a weight value to calculate the weighted average of the N sets of satellite positioning latitude and longitude coordinates to obtain the current valid latitude and longitude coordinate values; Iterative optimization steps: Repeat the effective coordinate calculation steps to obtain the 1st to nth effective latitude and longitude coordinate values ​​in sequence; Calculate the center point coordinates of the 1st to nth valid latitude and longitude coordinates; calculate the semi-spherical distance between each valid latitude and longitude coordinate value and the center point coordinates; Using the derivative of the semi-sine spherical distance as the weight value, the first to nth valid latitude and longitude coordinates are weighted and averaged to obtain the satellite positioning latitude and longitude coordinates after iterative optimization.

2. The method according to claim 1, characterized in that, Before obtaining N sets of satellite positioning latitude and longitude coordinate data, a data validity pre-screening step is also included: Obtain M sets of raw satellite positioning latitude and longitude coordinate data continuously output by the ground satellite positioning hardware, where M > N; The validity of each of the M sets of original satellite positioning latitude and longitude coordinate data is determined: whether the longitude and latitude values ​​in each set of original satellite positioning latitude and longitude coordinate data simultaneously meet the conditions that the longitude value is greater than 0 and less than 180 and the latitude value is greater than 0 and less than 90; the original satellite positioning latitude and longitude coordinate data that do not meet the above conditions are marked as invalid data and removed; the original satellite positioning latitude and longitude coordinate data that meet the above conditions are retained as valid data, until N sets of valid satellite positioning latitude and longitude coordinate data are accumulated.

3. The method according to claim 1, characterized in that, Calculate the mean of N sets of latitude and longitude coordinate data to obtain the coordinates of the center point, including: Calculate the arithmetic mean of all longitude values ​​in the N sets of satellite positioning latitude and longitude coordinate data as the longitude value of the center point, and the arithmetic mean of all latitude values ​​as the latitude value of the center point; The formula for calculating the longitude value of the center point is: The formula for calculating the latitude value of the center point is: Where N is the total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation. X i For the longitude value in the i-th group of satellite positioning coordinate data, Y i represents the latitude value in the i-th group of satellite positioning coordinate data.

4. The method according to claim 1, characterized in that, Calculate the semi-spherical distance between each satellite positioning latitude and longitude coordinate point and the center point coordinates, including: Based on the longitude and latitude values ​​of the center point, and the longitude value in the i-th set of satellite positioning coordinate data. X i and latitude value Y i Calculate the spherical distance d between the i-th satellite positioning coordinate point and the center point according to the following semi-versus formula. i : Where R is the Earth's radius. The coordinates of the center point, Let be the longitude and latitude values ​​in the i-th group of satellite positioning coordinate data.

5. The method according to claim 4, characterized in that: In the effective coordinate calculation step, the semi-spherical distance d between the i-th satellite positioning coordinate point and the center point is used. i The weight value of the i-th coordinate point is determined as follows: w i : in, f For the spherical distance d in the semi-sine direction i The monotonically decreasing function makes the semi-sine spherical distance d i The larger the value, the higher the corresponding weight value. w i The smaller; Based on weight values w i Calculate the comprehensive weight value of the i-th coordinate point ; Based on the weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average using the following formula. Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates: in, N The total number of sets of satellite positioning latitude and longitude coordinate data used in the calculation. X i For the longitude value in the i-th group of satellite positioning coordinate data, Y i The latitude value is from the i-th set of satellite positioning coordinate data. This represents the comprehensive weight value corresponding to the i-th set of coordinate data.

6. The method according to claim 1, characterized in that: In the iterative optimization step, each iteration is based on all the currently accumulated valid satellite positioning latitude and longitude coordinate data. The current valid latitude and longitude coordinate value is calculated according to the valid coordinate calculation steps. The weighted average of all valid latitude and longitude coordinate values ​​obtained by continuous iteration is calculated to continuously approximate the actual latitude and longitude coordinate values.

7. The method according to claim 5, characterized in that: In the effective coordinate calculation step, the effective latitude and longitude coordinate values ​​output within the M consecutive historical calculation cycles prior to the current calculation cycle are taken to construct a historical coordinate sequence. Based on the time position of the i-th satellite positioning coordinate point in the historical coordinate sequence and the coordinate change between the i-th coordinate point and its adjacent historical coordinate points, the temporal continuity evaluation value of the coordinate point is calculated. t i ; Based on time continuity assessment value t i Determine the second-level weight adjustment coefficient for the i-th coordinate point. g ( t i ),in g For the evaluation value of time continuity t i The monotonic function makes the second-level weight adjustment coefficient larger when the time continuity evaluation value is higher; Based on the first-level weight value w i Adjustment coefficient for the second level of weights g ( t i The product of ) is used to calculate the comprehensive weight value of the i-th coordinate point. : Based on the comprehensive weight values ​​of each of the N sets of satellite positioning latitude and longitude coordinate data Calculate the longitude-weighted average Xf inal Latitude-weighted average Y final This yields the current valid latitude and longitude coordinates.

8. The method according to any one of claims 1 to 7, characterized in that, After each iteration calculates the current valid latitude and longitude coordinates, an iteration convergence determination step is also included: Obtain the valid latitude and longitude coordinates obtained from the previous iteration. P k 1=( X k 1, Y k 1) and the effective latitude and longitude coordinates obtained from the current iteration. P k =( X k , Y k ); Calculate the current valid latitude and longitude coordinates. P k Compared with the previous valid latitude and longitude coordinates P k The coordinate change Δ between 1 k ; The coordinate change Δ k With preset convergence threshold ε Comparison: When Δ k < ε When the iteration is considered to have converged, the current valid latitude and longitude coordinates are determined. P k This serves as the final localization result output, stopping subsequent iterations of the calculation. When Δ k ≥ ε If the iteration has not yet converged, proceed to the next iteration. Among them, the coordinate change Δ k It represents the difference between latitude and longitude coordinates or the semi-sine spherical distance.

9. The method according to any one of claims 1 to 7, characterized in that: When satellite positioning hardware is equipped with an inertial sensor, inertial data can be used to help verify the validity of satellite positioning latitude and longitude coordinates: if the satellite positioning latitude and longitude coordinates change but the inertial sensor data shows that the hardware has not moved, then the satellite positioning latitude and longitude coordinates are determined to be invalid data and discarded; conversely, if the inertial data shows that the hardware has moved, the iteration strategy can be adjusted accordingly.

10. The method according to any one of claims 1 to 7, characterized in that: An alarm will be automatically triggered when the following abnormal states are detected: The iterations failed to converge after multiple iterations. The coordinate values ​​output by the iteration exceed the preset geofence range; The percentage of valid data remains below the preset threshold. The deviation between the iteration results and the historical true values ​​continues to increase.

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