A method of error compensation for an inertial navigation device

Abstract

The application relates to an inertial navigation device error compensation method, which comprises the following steps: S11, acquiring carrier navigation information corresponding to a calculation time; S12, calculating a speed change rate of the carrier navigation information and an angular velocity speed change rate, and acquiring a time difference corresponding to the calculation time; S13, determining carrier navigation information synchronized with data in a corresponding period according to the speed change rate, the angular velocity speed change rate and the time difference corresponding to the calculation time; S14, acquiring a moving path corresponding to the carrier navigation information synchronized with data according to the carrier navigation information synchronized with data; and S15, acquiring environment features corresponding to the moving path, including water depth, weather conditions and obstacle distribution, dividing the moving path into multiple grid units based on the collected environment features, and adjusting the moving path according to the evaluation results of the grid units. The application can improve the precision of ship body navigation and dynamically adjust the moving path of the ship.

Description

Technical Field

[0001] This invention relates to the field of inertial navigation technology, and in particular to an error compensation method for inertial navigation equipment. Background Technology

[0002] Inertial navigation products have advantages such as wide dynamic range, good linearity, stable performance, and all-weather navigation, making them irreplaceable in navigation fields such as ships and aircraft. Essentially, inertial navigation products utilize core sensing devices to collect angular motion and apparent acceleration information of the carrier. Through a specific mathematical model, they obtain the carrier's angular velocity and acceleration information relative to the local geographic coordinate system, and then use integration to calculate the carrier's attitude, velocity, and position information.

[0003] For example, Chinese Patent Publication No. CN112729290A discloses a method for compensating for the synchronization error of attitude data in an inertial navigation device. This method compensates for the vehicle's attitude information at the current navigation calculation time based on the vehicle's attitude angular rate during the most recent navigation calculation period and the time difference between the synchronization time and the current navigation calculation time. Specifically, it includes: calculating the vehicle's attitude angular rate during the most recent navigation calculation period; calculating the time difference between the synchronization time and the current navigation calculation time at the synchronization time; and calculating the vehicle's attitude information at the synchronization time based on the vehicle's attitude information at the current navigation calculation time, the vehicle's attitude angular rate during the most recent navigation calculation period, and the time difference between the synchronization time and the current navigation calculation time.

[0004] However, when a ship is traveling at high speed, the time difference in the output data of the navigation equipment can easily cause positional deviations during navigation. The ship needs to frequently adjust its route to adapt to environmental changes, resulting in poor error compensation of the navigation equipment and affecting the navigation of the ship. Summary of the Invention

[0005] This invention addresses the technical problems existing in the prior art by providing an error compensation method for inertial navigation devices.

[0006] The technical solution of this invention to solve the above-mentioned technical problems is as follows: An error compensation method for inertial navigation equipment, comprising:

[0007] S11, Obtain the carrier attitude information corresponding to the solution time;

[0008] S12, calculate the rate of change of the carrier's attitude information velocity and the rate of change of its angular velocity velocity, and obtain the corresponding time difference of the solution time;

[0009] S13. Based on the rate of change of velocity, the rate of change of angular velocity, and the corresponding time difference of the solution time, determine the carrier attitude information for data synchronization within the corresponding time period.

[0010] S14, Based on the carrier attitude information synchronized with the data, obtain the movement path corresponding to the carrier attitude information synchronized with the data;

[0011] S15: Obtain environmental features corresponding to the movement path, including water depth, weather conditions, and obstacle distribution. Based on the collected environmental features, divide the movement path into multiple grid cells and adjust the movement path according to the evaluation results of the grid cells.

[0012] The beneficial effects of this invention are that by taking into account various environmental characteristics and conducting dynamic evaluation, this scheme can significantly improve the adaptability and safety of ships under different environmental conditions.

[0013] This solution can assess changes in environmental characteristics in real time and respond quickly, adjusting the ship's movement path to enhance its dynamic response capabilities.

[0014] By comprehensively considering environmental characteristics, attitude information, and dynamic adjustment strategies, this solution can significantly improve the overall navigation performance of ships, including safety, efficiency, and reliability. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating steps S11-S15 of an inertial navigation device error compensation method according to the present invention.

[0016] Figure 2 This is a flowchart illustrating steps S21-S24 of an inertial navigation device error compensation method according to the present invention.

[0017] Figure 3 This is a flowchart illustrating steps S31-S33 of an inertial navigation device error compensation method according to the present invention.

[0018] Figure 4 This is a flowchart illustrating steps S41-S45 of an inertial navigation device error compensation method according to the present invention.

[0019] Figure 5 This is a flowchart illustrating steps S51-S54 of an inertial navigation device error compensation method according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0022] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0023] Example 1

[0024] This embodiment acquires the angular velocity and attitude of the ship during its movement to determine the required range of change in angular velocity and the attitude correction required when there are different positions and different position differences. In this way, when there is a time difference between the data generation time and the output time, the heading and position are adjusted in time to adjust the correction values ​​required by the navigation equipment after inertial movement, thereby improving the accuracy of navigation.

[0025] This application provides a method for error compensation in inertial navigation devices, such as... Figure 1 As shown, it includes:

[0026] S11, Obtain the carrier attitude information corresponding to the solution time;

[0027] S12, calculate the rate of change of the carrier's attitude information velocity and the rate of change of its angular velocity velocity, and obtain the corresponding time difference of the solution time;

[0028] S13. Based on the rate of change of velocity, the rate of change of angular velocity, and the corresponding time difference of the solution time, determine the carrier attitude information for data synchronization within the corresponding time period.

[0029] S14, Based on the carrier attitude information synchronized with the data, obtain the movement path corresponding to the carrier attitude information synchronized with the data;

[0030] S15: Obtain environmental features corresponding to the movement path, including key information such as water depth, weather conditions, and obstacle distribution. Based on the collected environmental features, divide the movement path into multiple grid cells and adjust the movement path according to the evaluation results of the grid cells.

[0031] The aforementioned carrier attitude information includes data such as the calculation cycle, speed, acceleration, apparent acceleration, trajectory, position, angular velocity, and carrier attitude during movement. The calculation time refers to the time point in the navigation system corresponding to the process of deriving the navigation information of the current moment from the navigation information of the previous moment. The calculation time difference represents the time difference between the previous moment and the current moment. The carrier attitude information obtained at this time is used to calculate the difference of the corresponding data when the system generates data but does not update it in time, in order to determine whether errors have occurred in the current angle, heading, etc.

[0032] The range of numerical changes obtained at this time is used to standardize the data, combine the currently obtained data into a more standard data form, and the output data can express the more precise attitude and position of the current carrier movement.

[0033] The carrier attitude information calculated in step S13 is sorted according to the rate of change of velocity, the rate of change of angular velocity, and the time point corresponding to the time difference of the calculation time. The data before and after synchronization are sorted and set in sequence to assist in the subsequent verification of the current angle.

[0034] The movement path generated in step S14 is a movement path generated by a neural network, which is used to predict the movement path of the hull at the solution time, so as to reduce the direction and position errors generated when the data is not updated.

[0035] The information obtained can be used to compensate for the current inertial navigation based on the current position and relative speed, in order to solve the problem that the position information will diverge after a period of movement using pure inertial calculation. At the same time, the calculation results of multiple velocities and accelerations are fused to solve the error of visual calculation when visibility and computing power are low during inertial movement.

[0036] Example 2

[0037] When a ship is traveling at high speed and the directions of the water flow on the surface intersect, the measured attitude information of the carrier will be inaccurate. That is, the current position of the ship will diverge, which makes the measured attitude information less effective in adjusting the current heading angle, and the corresponding adjustments cannot be made in time before the data is synchronized.

[0038] In this embodiment, a heading prediction method is adopted to predict the heading in advance based on the carrier's attitude information during normal driving in historical data and the carrier's attitude information at the time of calculation, so as to solve the error that occurs when the position diverges.

[0039] like Figure 2 As shown, the specific implementation method for path adjustment is as follows:

[0040] S21, determine the direction and velocity of the water flow on the water surface during the solution time, as well as the location of the water flow intersection;

[0041] S22, determine the percentage overlap between the current movement path of the ship and the direction of water flow;

[0042] S23, determine the rate of change of angular velocity, rate of change of velocity, and corresponding position point for each overlap percentage;

[0043] S24, when the position point is offset, obtain the position point with the largest change in angular velocity rate of change and velocity rate of change, and adjust the movement path according to the position point with the largest change.

[0044] In the above steps, the movement path of the hull is compared with the direction and speed of the water flow to identify the compensation method that needs to be adjusted when the hull moves on the cross current, so as to assist in adjusting the movement path and reduce movement error.

[0045] When selecting a location point, the process also includes: obtaining the predicted speed based on the output of the neural network prediction function; determining the difference between the predicted speed and the actual speed within the time difference of the solution time; comparing the magnitude of the difference between the predicted speed and the actual speed over time; and determining the location point and speed value where the error occurs when the difference between the predicted speed and the actual speed gradually changes.

[0046] This method is used to determine the location points to be selected. When a large difference is detected between the predicted and actual speeds, it indicates that the current navigation coefficients need to be compensated for the direction and position of the corresponding location. If the difference gradually increases over time or exhibits unstable behavior, it may mean that the navigation system has errors at certain locations. Once the location points with errors and their corresponding speed values ​​are identified, the system can take appropriate measures to compensate. For example, it can adjust the ship's course or speed to correct the error, or issue warnings to the crew for manual intervention. This timely feedback and compensation mechanism can greatly improve the overall performance and safety of the navigation system.

[0047] like Figure 3 As shown, the methods for obtaining grid cells include:

[0048] S31, Determine the search area, which includes the rectangular area of ​​the ship's current position and the surrounding waters;

[0049] S32 divides the search area into multiple grid cells according to latitude and longitude intervals. Each grid cell contains a location point. The size of the grid cell indicates the density of location points and the precision of the search.

[0050] S33. Take the point with the largest velocity error in each grid cell as the center point, and take the distance between the center point and the nearest point in the grid cell as the radius to construct a circle. The outer rectangle of the circle is the grid cell.

[0051] As mentioned above, the density of location points and the precision of the search usually mean smaller grid intervals and more detailed consideration of location points, which helps to determine the actual position of the hull or other objects, as well as more detailed velocity value changes, so that the adjustment values ​​of the current movement path can be determined in advance based on the obtained location points.

[0052] After obtaining the set grid cells, the center point of each grid cell is used as a grid point, and the movement path is adjusted according to the grid points, such as... Figure 4 As shown, the specific implementation methods include:

[0053] S41, determine the grid points of the grid cell and obtain the difference in velocity values ​​between adjacent grid points;

[0054] S42, obtain the cumulative time error of adjacent grid points over different time periods. The cumulative time error is used to determine the change of velocity value error over time by comparing the increase in the value of the velocity difference with the actual increase in the value.

[0055] S43, determine the location point with the largest cumulative time error within the current time period, and determine the change in velocity value. Mark the location points with the same change, and construct the first target region by combining the marked location points with the nearest grid point. The construction method of the first target region is the same as the construction method of the grid cell.

[0056] S44, construct the second target region from the grid point where the difference between the labeled location point and the velocity value is the largest; the construction method of the second target region is the same as that of the grid cell;

[0057] S45, take the regions in the overlapping part of the first target region and the second target region where the velocity values ​​corresponding to the currently marked positions show a gradually decreasing trend as the adjusted movement path.

[0058] Preferably, when acquiring the time cumulative error, after acquiring the first target region, the time cumulative error of the current grid cell is cleared to zero, and the time cumulative error in the adjacent grid cells of the first target region is recalculated.

[0059] By dividing the grid into cells and considering the velocity difference between adjacent grid points, this method can precisely identify key areas of velocity variation; this helps to achieve more detailed adjustments in scenarios that require precise control of the movement path.

[0060] By acquiring the cumulative time error over different time periods, this method can dynamically adapt to changes in speed values ​​over time; this makes the adjustment of the movement path more flexible and adaptable to real-time changing environmental conditions.

[0061] By identifying the location with the largest cumulative time error and the location with the same change in velocity value, this method can accurately identify key locations that require special attention. These locations may be areas with drastic velocity changes or areas where potential risks need to be avoided.

[0062] By constructing a first target region and a second target region, and considering their overlap, this method can further narrow down the scope of the adjustment path. This helps to more accurately identify the areas that need adjustment, improving the targeting and efficiency of path adjustment.

[0063] Within the overlapping sections, areas where the speed values ​​gradually decrease are selected as the adjusted movement path. This means that the path adjustment is based on the trend of speed changes. This adjustment method helps maintain stability and continuity during movement.

[0064] Example 3

[0065] After obtaining the adjusted movement path, in order to assist in the positioning, path planning and dynamic control of the auxiliary vessel, environmental characteristics such as the water depth value of the vessel's movement are obtained at this time, so as to help adjust the movement path in a timely manner and find the best matching point.

[0066] In this embodiment, the evaluation of the grid cells can also be achieved by adapting the obtained path with environmental parameters to determine how to adjust the movement path under different environmental conditions and find the best adaptation point on the current path so as to make adjustments to the current movement path in advance and reduce the impact of the environment during movement.

[0067] like Figure 5 As shown, the methods for adjusting the movement path based on environmental characteristics include:

[0068] S51, obtain the environmental characteristics of the grid cells, including water depth, weather, obstacles, etc.

[0069] S52, determine the first target area and the second target area corresponding to each environmental feature, use the carrier attitude information in the first target area and the second target area as the entropy value, and calculate the entropy of each first target area and the second target area.

[0070] When calculating the entropy values ​​of the first and second target regions, the features in the carrier's attitude information, such as the calculation cycle, speed, acceleration, apparent acceleration, trajectory, position, angular velocity, and carrier attitude during movement, should be able to reflect the carrier's motion state and environmental conditions in these regions.

[0071] For each extracted feature, its probability distribution in the first target region and the second target region is calculated. This can be achieved by statistically analyzing the frequency of each feature value. For example, for the speed feature, the probability of different speed values ​​appearing in these regions can be calculated.

[0072] The entropy value of each feature is calculated using the formula for information entropy. The general formula for information entropy is:

[0073]

[0074] Where H(X) represents the entropy value of feature X, p(x) i ) represents the eigenvalue x i The probability of occurrence.

[0075] Since there are multiple features, each with a corresponding entropy value, in order to obtain a comprehensive entropy value to describe the entire region, a weighted average is used to assign a weight to each feature. The entropy value of the corresponding region is the sum of the entropy values ​​of all features.

[0076] In this method, when obtaining the entropy value of the first target region, the features corresponding to the carrier's attitude information within the first target region are extracted, and a weight is assigned to each feature of the carrier's attitude information. The entropy values ​​of the features corresponding to all carrier attitude information are then weighted and averaged to obtain the entropy value of the first target region.

[0077] The entropy value of the second target region is calculated in the same way. When the entropy value of the overlapping part of the first and second target regions is greater than the entropy value of the second target region, the entropy value of the overlapping part of the first and second target regions is taken as the entropy value of the second target region.

[0078] S53, when the ship moves to any first target area and second target area, the area with the smallest entropy value around the ship is selected as the matching sub-region.

[0079] S54. Compare each element in the entropy sequence corresponding to the matching sub-region, calculate the grid point corresponding to the minimum entropy variance in the matching region, and when the grid point corresponding to the minimum entropy variance is less than the preset threshold, it is taken as the best matching point. Based on the path formed by the grid cells of the best matching point, output the final adjusted movement path.

[0080] Preferably, the matching sub-region contains at least two grid points. When there is no best matching point in the matching sub-region, the matching sub-region is expanded by two grid points.

[0081] Among them, the minimum entropy variance represents the minimum variance value corresponding to the current grid point, which is used to determine whether the value of the current feature exceeds the set value, so as to select a more stable region.

[0082] By acquiring environmental characteristics of the grid cells, such as water depth, weather, and obstacles, this method enables the movement path to adapt to different environmental conditions. This helps reduce the impact of the environment on movement, improving the safety and efficiency of the vessel.

[0083] By calculating the entropy values ​​of the first and second target regions, this method can dynamically assess the degree of disorder or uncertainty in these regions. When the ship moves to these regions, it can select the region with the smallest entropy value as the matching sub-region based on the magnitude of the entropy value, thereby achieving dynamic adjustment of the path.

[0084] By comparing each element in the entropy sequence corresponding to the matching sub-region and calculating the grid point corresponding to the minimum variance in the matching region, this method can accurately locate the best matching point, which makes path adjustment more precise and reliable.

[0085] When no optimal matching point exists in the matching sub-region, the method provides the option to expand the matching sub-region by two grid points. This flexibility allows the method to adapt to more complex environments and path requirements.

[0086] Here is a specific example:

[0087] Suppose a ship needs to adjust its course to adapt to changes in water depth during navigation. First, the method divides the navigation area into multiple grid cells based on environmental characteristics such as water depth and determines the environmental characteristics of each grid cell. Then, it calculates the entropy value of the ship's attitude information within each grid cell to assess the degree of disorder in that area.

[0088] When a ship moves to a grid cell, the method selects the region with the lowest entropy value from the surrounding area as the matching sub-region. Assume the matching sub-region contains three grid points A, B, and C, with corresponding entropy values ​​H(A), H(B), and H(C), respectively. Next, it compares these three entropy values ​​and calculates their variance.

[0089] If the entropy value H(B) corresponding to grid point B is the smallest and its variance is also less than a preset threshold, then point B will be considered the optimal matching point. Based on the optimal matching point B, the method will output an adjusted movement path, enabling the ship to successfully navigate around areas with shallow water.

[0090] If no optimal matching point exists within the matching sub-region, the method expands the matching sub-region by two grid points and repeats the process until the optimal matching point is found. This flexible adjustment strategy enables ships to navigate safely and efficiently in complex and ever-changing environments.

[0091] Preferably, in this invention, an inertial compensation algorithm is also used to adjust the current path, a single-axis multi-array IMU is used to compensate for the inertial navigation, and the current inertial navigation is verified based on data measured from multiple angles according to the placement of the multi-array IMU, so as to determine the navigation of the current ship hull under different layout and environmental scenarios, thereby reducing the errors generated during navigation.

[0092] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0093] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0094] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0097] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0098] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for error compensation in inertial navigation equipment, characterized in that, include: S11, Obtain the carrier attitude information corresponding to the solution time; S12, calculate the rate of change of the carrier's attitude and velocity and the rate of change of its angular velocity, and obtain the corresponding time difference of the solution time; S13. Based on the rate of change of velocity, the rate of change of angular velocity, and the corresponding time difference of the solution time, determine the carrier attitude information for data synchronization within the corresponding time period. S14, Based on the carrier attitude information synchronized with the data, obtain the movement path corresponding to the carrier attitude information synchronized with the data; S15: Obtain environmental features corresponding to the movement path, including water depth, weather conditions, and obstacle distribution. Based on the collected environmental features, divide the movement path into multiple grid cells. Adjust the movement path according to the evaluation results of the grid cells. The adjustment methods for the movement path include: S21, determining the direction and velocity of the water flow on the water surface during the solution time, as well as the location points where the water flows intersect; S22, determine the percentage overlap between the current movement path of the ship and the direction of water flow; S23, determine the rate of change of angular velocity, rate of change of velocity, and corresponding position point for each overlap percentage; S24, when the position point is offset, obtain the position point with the largest change in angular velocity rate of change and velocity rate of change, and adjust the movement path according to the position point with the largest change; The movement path is adjusted according to grid points. Specific implementation methods include: S41, determine the grid points of the grid cell and obtain the difference in velocity values ​​between adjacent grid points; S42, obtain the cumulative time error of adjacent grid points over different time periods; S43, determine the location point with the largest cumulative time error in the current time period, and determine the change in velocity value. Mark the location point with the same change, and construct the first target area by combining the marked location point with the nearest grid point. S44, construct the second target region by comparing the grid point with the marked location point and the velocity value with the grid point with the largest difference; S45, take the regions in the overlapping part of the first target region and the second target region where the velocity values ​​corresponding to the currently marked position points show a gradually decreasing trend as the adjusted movement path; The methods for adjusting movement paths based on environmental characteristics include: S51, Obtain the environmental characteristics of the grid cells, including water depth, weather, and obstacles; S52, determine the first target area and the second target area corresponding to each environmental feature, use the carrier attitude information within the first target area and the second target area as the entropy value, and calculate the entropy of each first target area and the second target area; S53, when the ship moves to any first target area and second target area, the area with the smallest entropy value around the ship is selected as the matching sub-region; S54. Compare each element in the entropy sequence corresponding to the matching sub-region, calculate the grid point corresponding to the minimum entropy variance in the matching region, and when the grid point corresponding to the minimum entropy variance is less than the preset threshold, it is taken as the best matching point. Based on the path formed by the grid cells of the best matching point, output the final adjusted movement path.

2. The inertial navigation device error compensation method according to claim 1, characterized in that, The methods for obtaining grid cells include: S31, Determine the search area, which includes the rectangular area of ​​the ship's current position and the surrounding waters; S32 divides the search area into multiple grid cells according to latitude and longitude intervals. Each grid cell contains a location point. The size of the grid cell indicates the density of location points and the precision of the search. S33. Take the point with the largest velocity error in each grid cell as the center point, and take the distance between the center point and the nearest point in the grid cell as the radius to construct a circle. The outer rectangle of the circle is the grid cell.

3. The inertial navigation device error compensation method according to claim 1, characterized in that, The carrier's attitude and attitude information includes the calculation cycle, velocity, acceleration, apparent acceleration, trajectory, position, angular velocity, and carrier attitude during movement.

4. The error compensation method for inertial navigation equipment according to claim 1, characterized in that, When selecting a location point, the process also includes: obtaining the predicted speed based on the output of the neural network prediction function; determining the difference between the predicted speed and the actual speed within the time difference of the solution time; comparing the magnitude of the difference between the predicted speed and the actual speed over time; and determining the location point and speed value where the error occurs when the difference between the predicted speed and the actual speed gradually changes.

5. The inertial navigation device error compensation method according to claim 1, characterized in that, The matching sub-region must contain at least two grid points. If there is no best matching point in the matching sub-region, the matching sub-region will be expanded by two grid points.

6. The inertial navigation device error compensation method according to claim 1, characterized in that, When acquiring the time cumulative error, after acquiring the first target area, the time cumulative error of the current grid cell is cleared to zero, and the time cumulative error in the adjacent grid cells of the first target area is recalculated.

7. The inertial navigation device error compensation method according to claim 1, characterized in that, When obtaining the entropy value of the first target region, the features corresponding to the carrier attitude information within the first target region are extracted, and a weight is assigned to each feature of the carrier attitude information. The entropy values ​​of the features corresponding to all carrier attitude information are weighted and averaged to obtain the entropy value of the first target region. When the entropy value of the overlapping part between the first target region and the second target region is greater than the entropy value of the second target region, the entropy value of the overlapping part between the first target region and the second target region is taken as the entropy value of the second target region.

Images