Long endurance gravity measurement method and device for enhancing relative gravity measurement precision based on absolute gravity information

Abstract

The invention discloses a long endurance gravity measurement method and device for enhancing relative gravity measurement precision based on absolute gravity information, and relates to the technical field of gravity measurement, and the method comprises the steps: obtaining an absolute gravimeter gravity data sequence and a relative gravimeter gravity data sequence; obtaining a relative gravimeter long-period error observation information sequence according to the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence; preprocessing the relative gravimeter long-period error observation information sequence, and obtaining a relative gravity information error constraint relation model based on the preprocessed relative gravimeter long-period error observation information sequence; and the relative gravity information error constraint relation model is adopted to predict the relative gravity information error in a period of time in the future, and error compensation is completed. According to the invention, the absolute gravimeter and the relative gravimeter are jointly used to realize advantage complementation, and the gravity information is measured at high precision in a long-endurance dynamic scene.

Description

Technical Field

[0001] This invention relates to the field of gravity measurement technology, and specifically to a long-endurance gravity measurement method and apparatus that enhances the accuracy of relative gravity measurement based on absolute gravity information. Background Technology

[0002] Gravity environment information, as a crucial component of multi-dimensional information sources, plays an important role in fields such as missile strikes, missile guidance, auxiliary navigation, and military surveying, and has become an important source of information for safeguarding operations. Relative gravimeters, as crucial instruments for acquiring gravity environment information, possess outstanding advantages in dynamic measurement performance. They can travel with the platform to measure relative gravity information, achieving an accuracy better than 0.6 mGal in actual measurements. However, relative gravimeters face zero-point drift and grid repeatability errors, and can only provide information on changes in the gravity environment, not directly provide absolute gravity information. In recent years, absolute gravimeters have been steadily developing, exhibiting significant advantages in long-term measurement stability. The dynamic measurement accuracy of absolute gravimeters on shipboard surfaces has reached 1 mGal, but their dynamic measurement performance verification is still insufficient and cannot meet the requirements for dynamic navigation and operation under all working conditions of offshore platforms.

[0003] As the working conditions of various vehicle-mounted, surface, and underwater platforms continue to expand, dynamic application scenarios are placing increasingly higher demands on gravity information, requiring measuring instruments to directly provide high-precision absolute gravity information that is unaffected by drift errors and meets the needs of ultra-long endurance use. Summary of the Invention

[0004] To address the gravity measurement needs of various platforms, this invention provides a long-endurance gravity measurement method and apparatus that enhances the accuracy of relative gravity measurement based on absolute gravity information. By combining an absolute gravimeter and a relative gravimeter, the advantages of both are complemented, enabling high-precision measurement of gravity information in dynamic long-endurance scenarios.

[0005] In a first aspect, the present invention provides a long-endurance gravity measurement method based on absolute gravity information to enhance the accuracy of relative gravity measurement, comprising: Obtain gravity data sequences from both absolute and relative gravimeters; The long-period error observation information sequence of the relative gravimeter is obtained from the gravity data sequence of the absolute gravimeter and the gravity data sequence of the relative gravimeter; The long-period error observation information sequence of the relative gravimeter is preprocessed, and a relative gravity information error constraint relationship model is obtained based on the preprocessed long-period error observation information sequence of the relative gravimeter. A relative gravity information error constraint relationship model is used to predict the relative gravity information error in the future period and complete the error compensation.

[0006] In some instances, the difference between the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence is used to obtain the long-period error observation information sequence of the relative gravimeter.

[0007] In some instances, the preprocessing of the long-period error observation information sequence of the relative gravimeter includes: The average data sequence is obtained by applying a sliding window processing method to the long-period error observation information sequence of the relative gravimeter.

[0008] In some instances, the relative gravity information error constraint relationship model obtained based on the preprocessed long-period error observation information sequence of the relative gravimeter includes: A linear fitting process is performed on the average data sequence to obtain a relative gravity information error constraint relationship model, where the slope of the relative gravity information drift error and the intercept are the relative gravity information grid value error.

[0009] In some instances, the method of using a relative gravity information error constraint relationship model to predict the relative gravity information error over a future period and to complete error compensation includes: The relative gravity information error is predicted over a future period by using the intercept of the slope in the relative gravity information error constraint relationship model, thus completing the error compensation.

[0010] Secondly, the present invention provides a long-endurance gravity measurement device that enhances the accuracy of relative gravity measurement based on absolute gravity information, comprising: The data acquisition module is used to acquire gravity data sequences from both the absolute gravimeter and the relative gravimeter. The observation error acquisition module is used to obtain the long-period error observation information sequence of the relative gravimeter from the gravity data sequence of the absolute gravimeter and the gravity data sequence of the relative gravimeter. The evaluation module is used to preprocess the long-period error observation information sequence of the relative gravimeter, and to obtain the relative gravity information error constraint relationship model based on the preprocessed long-period error observation information sequence of the relative gravimeter. The error compensation module is used to predict the relative gravity information error over a future period of time using a relative gravity information error constraint relationship model, and to complete the error compensation.

[0011] In some instances, the difference between the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence is used to obtain the long-period error observation information sequence of the relative gravimeter.

[0012] In some instances, the evaluation module is used to perform sliding window processing on the long-period error observation information sequence of the relative gravimeter to obtain an average data sequence.

[0013] In some instances, the evaluation module is used to perform linear fitting on the average data sequence to obtain a relative gravity information error constraint relationship model, wherein the slope of the relative gravity information drift error and the intercept are the relative gravity information grid value errors.

[0014] In some instances, the error compensation module is used to predict the relative gravity information error over a future period of time by using the intercept of the slope in the relative gravity information error constraint relationship model, thereby completing the error compensation.

[0015] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: This invention addresses the need for high-precision absolute gravity measurement information in long-endurance dynamic application scenarios. It tackles the problem that relative gravimeters cannot directly provide absolute gravity information due to zero-point drift errors and grid repeatability errors. Instead, it proposes a long-endurance gravity measurement method that enhances the accuracy of relative gravity measurements based on absolute gravity information. This method combines the dynamic measurement advantages of relative gravimeters with the long-term stable measurement advantages of absolute gravimeters, using absolute gravity information to correct long-period measurement errors contained in relative gravity information in real time, thus meeting the platform's demand for absolute gravity information under dynamic conditions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the following description, specific embodiments of the invention will be illustrated with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and computer execution as referred to herein includes operations by a computer processing unit representing electronic signals of data in a structured format. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise alter the operation of the computer in a manner well known to those skilled in the art. The data structure maintained by the data is the physical location of the memory, which has specific characteristics defined by the data format. However, the principles of the invention described above are not intended to be limiting, and those skilled in the art will understand that many of the following steps and operations can also be implemented in hardware.

[0020] The terms "module" or "unit" as used herein can be considered as software objects executing on the computing system. Different components, modules, engines, and services described herein can be considered as implementations on the computing system. The apparatus and methods described herein are preferably implemented in software, but can also be implemented in hardware, both of which are within the scope of this invention.

[0021] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0022] In the first embodiment of the present invention, a long-endurance gravity measurement method based on absolute gravity information to enhance the accuracy of relative gravity measurement is provided. The technical route is as follows: (1) Research the quality assessment method of absolute gravity information and construct the error constraint relationship model of relative gravity information to provide a basis for evaluating the data quality of relative gravimeters. (2) Research the method of combining absolute gravimeters with relative gravimeters to realize timely correction of relative gravimeter errors during the flight of the combat platform and provide high-precision absolute gravity information for long-endurance flight.

[0023] like Figure 1As shown, the combined use of absolute gravimeters and relative gravimeters improves the absolute gravity measurement performance of the platform under dynamic navigation conditions. Both types of gravimeters travel with the platform, receiving auxiliary navigation information provided by the platform and each performing gravity measurements. Simultaneously, the absolute and relative gravimeters exchange information, and based on the quality control of the dynamic measurement data from the absolute gravimeters, error correction for the relative gravimeters is completed, providing high-precision absolute gravity information for long-duration navigation in dynamic environments.

[0024] In this embodiment of the invention, the method of combining an absolute gravimeter with a relative gravimeter can be implemented in the following manner: Based on the error characteristics of relative gravimeters, this study investigates the applicable conditions for absolute gravimeter correction of relative gravimeters. Correction and compensation models are constructed under various navigation conditions of the platform. Quality control and confidence assessment of absolute gravimeter data are conducted based on navigation and motion data. Real-time correction of long-period errors of the relative gravimeter is achieved, eliminating grid repeatability errors while predicting relative gravimeter drift errors and correcting relative gravity data corresponding to historical tracks. This provides rich absolute gravity field information for gravity field background map construction and gravity-assisted navigation.

[0025] Absolute gravimeter gravity data sequence for: In the formula, For the first The gravity data from the absolute gravimeter at that moment. This represents the number of data points in the sequence.

[0026] Relative gravimeter gravity data sequence for: In the formula, For the first The relative gravity data from the gravimeter at that moment. This represents the number of data points in the sequence.

[0027] use and By subtracting the values, we obtain the long-period error observation information sequence of the relative gravimeter. : , The relative gravimeter and absolute gravimeter move with the platform, making them suitable for dynamic measurement scenarios.

[0028] In this embodiment of the invention, the method for assessing the quality of absolute gravity information can be implemented in the following manner: Given that gravity data is a low-frequency quantity, and that relative gravimeter drift error and grid error are also low-frequency quantities, digital filtering is used to remove... To mitigate the effects of mid-to-high frequency noise or disturbances, a sliding window process is applied to the data to obtain the average data. The sliding window typically spans 48 to 72 hours.

[0029]

[0030] As the sequence is continuously updated, while keeping the sliding window time span constant, multiple [sequences] are obtained. The sequence formed .

[0031]

[0032] For sequence By performing linear fitting, we obtain the relative gravity information error constraint relationship model:

[0033] In the formula, This is due to the drift error of relative gravity information. Relative gravity information grid error.

[0034] Since the error of a relative gravimeter is mainly a slowly varying error with a long period, it can be used... and Predicting relative gravity information errors over a future period and compensating for these errors, for example: Multiplying by time allows for the prediction of future drift in gravity measurements. b can directly compensate for constant errors in gravity measurements over future timeframes.

[0035] This embodiment, through the above-described technical solution, combines an absolute gravimeter and a relative gravimeter to provide high-precision absolute gravity information. The proposed method of combining absolute and relative gravimeter measurements is suitable for dynamic application scenarios. A scheme for correcting relative gravimeter data using absolute gravimeter data is presented, forming a loop of "compensation parameter update -- compensation parameter usage -- compensation parameter update".

[0036] This embodiment addresses the problem that relative gravimeters cannot directly provide absolute gravity information due to zero-point drift error and grid repeatability error. It proposes a long-endurance gravity measurement method based on absolute gravity information to enhance the accuracy of relative gravity measurements. This achieves high-precision, dynamic, long-endurance absolute gravity measurement, improving the platform's gravity measurement capabilities.

[0037] In a second embodiment of the present invention, to facilitate better implementation of the method provided in the embodiments of the present invention, an apparatus based on the above method is also provided. The meanings of the terms used are the same as in the methods described above, and specific implementation details can be found in the descriptions within the method embodiments.

[0038] Please see Figure 2 , Figure 2This is a schematic diagram of the structure of a device provided in an embodiment of the present invention, wherein the device may include a data acquisition module, an observation error acquisition module, an evaluation module, and an error compensation module, wherein: The data acquisition module is used to acquire gravity data sequences from both the absolute gravimeter and the relative gravimeter. The observation error acquisition module is used to obtain the long-period error observation information sequence of the relative gravimeter from the gravity data sequence of the absolute gravimeter and the gravity data sequence of the relative gravimeter. The evaluation module is used to preprocess the long-period error observation information sequence of the relative gravimeter, and to obtain the relative gravity information error constraint relationship model based on the preprocessed long-period error observation information sequence of the relative gravimeter. The error compensation module is used to predict the relative gravity information error over a future period of time using a relative gravity information error constraint relationship model, and to complete the error compensation.

[0039] In another specific example, the difference between the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence is used to obtain the long-period error observation information sequence of the relative gravimeter.

[0040] In another specific example, the aforementioned evaluation module is used to perform sliding window processing on the long-period error observation information sequence of the relative gravimeter to obtain an average data sequence.

[0041] In another specific example, the aforementioned evaluation module is used to perform linear fitting on the average data sequence to obtain a relative gravity information error constraint relationship model, wherein the slope in the relative gravity information error constraint relationship model is the relative gravity information drift error, and the intercept is the relative gravity information grid value error.

[0042] In another specific example, the aforementioned error compensation module is used to predict the relative gravity information error over a future period of time by using the intercept of the slope in the relative gravity information error constraint relationship model, thereby completing the error compensation.

[0043] The foregoing has provided a detailed description of a long-endurance gravity measurement method and apparatus based on absolute gravity information to enhance the accuracy of relative gravity measurement. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A long-endurance gravity measurement method based on absolute gravity information to enhance the accuracy of relative gravity measurement, characterized in that, include: Obtain gravity data sequences from both absolute and relative gravimeters; The long-period error observation information sequence of the relative gravimeter is obtained from the gravity data sequence of the absolute gravimeter and the gravity data sequence of the relative gravimeter; The long-period error observation information sequence of the relative gravimeter is preprocessed, and a relative gravity information error constraint relationship model is obtained based on the preprocessed long-period error observation information sequence of the relative gravimeter. A relative gravity information error constraint relationship model is used to predict the relative gravity information error in the future period and complete the error compensation.

2. The method according to claim 1, characterized in that, The difference between the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence is used to obtain the long-period error observation information sequence of the relative gravimeter.

3. The method according to claim 2, characterized in that, The preprocessing of the long-period error observation information sequence of the relative gravimeter includes: The average data sequence is obtained by applying a sliding window processing method to the long-period error observation information sequence of the relative gravimeter.

4. The method according to claim 3, characterized in that, The relative gravity information error constraint relationship model obtained based on the preprocessed long-period error observation information sequence of the relative gravimeter includes: A linear fitting process is performed on the average data sequence to obtain a relative gravity information error constraint relationship model, where the slope of the relative gravity information drift error and the intercept are the relative gravity information grid value error.

5. The method according to claim 4, characterized in that, The step of using a relative gravity information error constraint relationship model to predict the relative gravity information error over a future period and completing error compensation includes: The relative gravity information error is predicted over a future period by using the intercept of the slope in the relative gravity information error constraint relationship model, thus completing the error compensation.

6. A long-endurance gravity measurement device that enhances the accuracy of relative gravity measurement based on absolute gravity information, characterized in that, include: The data acquisition module is used to acquire gravity data sequences from both the absolute gravimeter and the relative gravimeter. The observation error acquisition module is used to obtain the long-period error observation information sequence of the relative gravimeter from the gravity data sequence of the absolute gravimeter and the gravity data sequence of the relative gravimeter. The evaluation module is used to preprocess the long-period error observation information sequence of the relative gravimeter, and to obtain the relative gravity information error constraint relationship model based on the preprocessed long-period error observation information sequence of the relative gravimeter. The error compensation module is used to predict the relative gravity information error over a future period of time using a relative gravity information error constraint relationship model, and to complete the error compensation.

7. The apparatus according to claim 6, characterized in that, The difference between the absolute gravimeter gravity data sequence and the relative gravimeter gravity data sequence is used to obtain the long-period error observation information sequence of the relative gravimeter.

8. The apparatus according to claim 7, characterized in that, The evaluation module is used to perform sliding window processing on the long-period error observation information sequence of the relative gravimeter to obtain the average data sequence.

9. The apparatus according to claim 8, characterized in that, The evaluation module is used to perform linear fitting on the average data sequence to obtain a relative gravity information error constraint relationship model, wherein the slope of the relative gravity information drift error and the intercept are the relative gravity information grid value error.

10. The apparatus according to claim 9, characterized in that, The error compensation module is used to predict the relative gravity information error over a future period of time by using the intercept of the slope in the relative gravity information error constraint relationship model, and to complete the error compensation.

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