A method for obtaining gravity values ​​of airborne disturbances

Abstract

The present invention provides a method for obtaining aviation disturbance gravity values, which first obtains information on the position and motion parameters of an aircraft carrier based on a precise single-point positioning method; then fuses the information on the position and motion parameters of the aircraft carrier with the measured data of an aviation gravimeter; then constructs a Kalman filter model, performs Kalman filtering and Kalman smoothing on the original value of the disturbance gravity, and outputs the final disturbance gravity value; finally, the output disturbance gravity value is subjected to accuracy evaluation to obtain a data processing result that meets the internal accuracy requirements. The present invention is reasonably conceived, does not require the deployment of ground reference stations, and can realize efficient solution and processing of aviation gravity measurement data in vast sea areas far away from the continent and in difficult areas where reference stations cannot be deployed. The aviation gravity solution has high internal accuracy and is suitable for promotion and application.

Description

Technical Field

[0001] The invention relates to the technical field of aviation gravity measurement, and in particular to a method for obtaining aviation disturbance gravity values. Background Art

[0002] Aerial gravity measurement is a geophysical survey method that uses aircraft and other aircraft as carriers, combined with inertial navigation platforms, airborne gravimeters, and global positioning systems (GNSS) to measure gravity field information in high-speed motion. At present, my country's offshore aerial gravity exploration has basically completed full coverage, providing important basic data for marine basic geological surveys and geoscience research. With the development of aerial gravity measurement, going deep blue has naturally become one of the missions of geophysicists. However, there are often no conditions for setting up base stations over the vast sea area, and the survey area is often hundreds of kilometers away from the base station. In this long baseline situation, the effect of eliminating correlation errors through differential methods is not ideal. The residual error usually increases with the increase of baseline length, which directly leads to the fact that the differential positioning mode may not be able to obtain reliable motion parameter information. On the other hand, in recent years, precise point positioning technology (Precise Point Positioning, PPP) has matured, and its positioning accuracy can reach the centimeter level, but the fusion processing of this technology and aerial gravity is difficult, and its practical application in aerial gravity measurement is rarely seen. In addition, the traditional free-space gravity anomaly needs to be calculated based on the geoid height, but the geoid height information may not be sufficient, so it is of great significance to introduce other rigorous gravity field parameters (i.e., disturbed gravity) for solution. Therefore, how to obtain high-precision disturbed gravity values ​​that meet the requirements from the original measurement data based on precise single-point positioning is a key technical problem that restricts the in-depth development of the field of airborne gravity exploration.

[0003] Therefore, it is necessary to study a method for obtaining aviation disturbance gravity values ​​to solve one or more of the above-mentioned technical problems. Summary of the invention

[0004] In view of the technical problems existing in the above-mentioned background technology, the present invention proposes a method for obtaining aviation disturbance gravity values. The method has a reasonable concept and does not require the deployment of ground reference stations. It can realize efficient solution and processing of aviation gravity measurement data in vast sea areas far away from the mainland and in difficult areas where reference stations cannot be deployed. The aviation gravity solution has high internal accuracy and is suitable for promotion and application.

[0005] In order to solve the above technical problems, the present invention provides a method for obtaining aviation disturbance gravity values, which first obtains the information of the position and motion parameters of the aircraft carrier based on the precise single-point positioning method; then fuses the information of the position and motion parameters of the aircraft carrier with the measured data of the aviation gravimeter; then constructs a Kalman filter model, performs Kalman filtering and Kalman smoothing on the original value of the disturbance gravity, and outputs the final disturbance gravity value; finally, the output disturbance gravity value is evaluated for accuracy, and a data processing result that meets the internal accuracy requirements is obtained.

[0006] The method for obtaining aviation disturbance gravity values, wherein the method for obtaining the position information of the aircraft carrier is: first constructing a pseudorange and carrier phase mathematical model for precise single-point positioning, using open source positioning software to obtain static precise single-point positioning results of the reference station and the mobile station, and then performing accuracy evaluation on the precise single-point positioning results to ensure that the positioning accuracy meets the requirements of aviation gravity measurement.

[0007] The method for obtaining aviation disturbance gravity values, wherein: when the precise single-point positioning result is obtained using open source positioning software, the precision of the precise ephemeris product used is required to be better than 2.5 centimeters, the precision of the precise clock error product used is required to be better than 75 picoseconds, and the ionosphere model uses data provided by the IGS Analysis Center.

[0008] The method for obtaining aviation disturbance gravity value, wherein: the mathematical model of pseudo-range and carrier phase of the precise single point positioning is as follows:

[0009]

[0010] In the above formula (1), r represents the station, s represents the satellite, and i represents the frequency (i = 1, 2). is the pseudorange observation value, is the carrier phase observation value; represents the geometric distance between stations and stars; c is the speed of light in vacuum; δt r and δt s Indicates the receiver clock error and satellite clock error; A / f i 2 The first-order ionospheric delay can be eliminated by the linear combination of the dual-frequency observations; f i represents the frequency of L1 and L2, λ i is the corresponding wavelength; N is the corresponding integer ambiguity; d r,i and represents the receiver pseudorange bias and satellite pseudorange bias caused by hardware delay on the ith frequency; b r,i and Indicates the receiver phase deviation and satellite phase deviation caused by hardware delay.

[0011] The method for obtaining the aviation disturbance gravity value, wherein the process of obtaining the static precise single-point positioning result of the reference station is: comparing the static positioning accuracy of the reference station, using base station data collected for more than 12 hours in a certain aviation survey area, and obtaining the static coordinates in the Earth-centered Earth-fixed coordinate system through precise single-point positioning.

[0012] The method for obtaining the aviation disturbance gravity value, wherein the process of obtaining the static precise single-point positioning result of the mobile station is: comparing the static positioning accuracy of the mobile station, using the 2-hour short baseline differential result collected in a certain aviation survey area as a benchmark, and comparing it with the result calculated by precise single-point positioning alone, to obtain the positioning accuracy in the three directions of XYZ.

[0013] The method for obtaining aviation disturbance gravity value, wherein the specific process of the fusion processing is:

[0014] First, the gravimeter and GNSS observations are used to obtain the disturbed gravity along the flight line. The basic equation of the disturbed gravity along the flight line is:

[0015]

[0016] Among them, in the above formula (2) is the second derivative of the earth's height h, indicating the vertical acceleration, obtained from the GNSS information processed by precise point positioning; δg is the disturbance gravity value; f Σ It is the total field after various gravity corrections of the vertical component acting on the gravimeter sensor;

[0017] Then, by establishing the Kalman filter state equation including the system state vector and system noise and the Kalman filter measurement equation including the observed quantity and observation noise, the state estimation value at the previous moment is used to estimate the state at the current moment, and then the observed value at the current moment is used to correct it; the equation is established based on the measurement error relationship, the disturbance gravity adopts the second-order approximate model, the disturbance gravity is described by the random statistical model, and the system state vector is taken as:

[0018]

[0019] Wherein, W in the above formula (3) is the vertical velocity; TF3 is the time delay of the gravimeter anti-aliasing filter, and the theoretical value is 2 seconds; KF3 is the gravimeter scale factor; KF1 and KF2 are the platform installation error angles; is the first derivative of the perturbed gravity;

[0020] The Kalman filter state equation is expressed as:

[0021]

[0022] The specific component form is as follows:

[0023]

[0024] In the above formula (5), f1, f2, and f3 are the measured values ​​of the two horizontal accelerations and the vertical acceleration of the gravimeter, respectively, and δf T is the low-frequency disturbance caused by the aircraft pitch and roll, q Σ is the overall impact of process noise; the derivatives of the four constants TF3 KF3 KF1 KF2 and the second-order derivative of the disturbance gravity δg are all represented by white noise;

[0025] The Kalman filter measurement equation is:

[0026] h(t)=H(t)X(t)+δh (6);

[0027] In the above formula (6), h(t) represents the height of the ellipsoid after eccentricity correction, H(t) is [1 0 0 0 0 0 0 0], and δh represents the measurement noise.

[0028] The method for obtaining aviation disturbance gravity value, wherein: the motion parameter information of the aircraft carrier is obtained by selecting aviation gravity data measured in a certain sortie measurement area and performing dynamic positioning accuracy comparison and analysis; the gravity correction mainly includes eccentricity correction, Eutworth correction, horizontal acceleration correction, zero drift correction, normal gravity and altitude correction; the Kalman filter processing is to use the constructed Kalman filter model, solve the equation according to the Kalman filter, and use Kalman smoothing processing to obtain the final disturbance gravity value.

[0029] The method for obtaining aviation disturbance gravity values, wherein the process of obtaining the disturbance gravity values ​​is: using precise single-point positioning to obtain the position and velocity information of the mobile station GNSS, and then combining the obtained position and velocity information of the mobile station GNSS with the gravimeter platform inertial navigation system for solution, obtaining the acceleration data, attitude data and platform data of the gravimeter, and finally integrating the obtained data information into the aforementioned Kalman filter model to solve and obtain the disturbance gravity value that meets the accuracy requirements.

[0030] The method for obtaining aviation disturbance gravity values, wherein the specific process of evaluating the accuracy of the disturbance gravity values ​​is as follows: first, for short baseline measurement data, the results of a self-compiled differential solution program and GTGRAV, which is a differential solution software provided by GT, are compared to verify the effectiveness of the self-compiled differential solution program; secondly, the gravity solution based on the precise single point positioning result and the GTGRAV result are compared again to measure the disturbance gravity solution effect based on the precise single point positioning; thirdly, the results based on the precise single point positioning result, the self-compiled differential solution program and the GTGRAV program are placed on a graph for comparison.

[0031] By adopting the above technical solution, the present invention has the following beneficial effects:

[0032] The method for obtaining aviation disturbance gravity values ​​of the present invention is reasonably conceived. Compared with the traditional dynamic differential GNSS technology, the present invention is mainly based on GNSS precise single-point positioning technology and adopts a single-station measurement mode. It does not require the deployment of ground reference stations and has broad application prospects in vast sea areas far away from the mainland and in difficult areas where reference stations cannot be deployed.

[0033] The present invention utilizes precise single-point positioning, thus avoiding the shortcoming of traditional differential positioning that it is difficult to ensure accuracy in the case of a long baseline; the present invention adopts a disturbed gravity formula for calculation, thus avoiding the shortcoming of the traditional method of using gravity anomalies that requires water level information; the present invention provides a mathematical model for extracting disturbed gravity, thus obtaining an ideal high-precision processing result, and having an excellent practical application effect.

[0034] The mathematical model of precise single-point positioning adopted in the present invention has been used to test its static and dynamic positioning accuracy, and the GT2A aerial gravity measured data of a certain sea area has been used for analysis. The test data analysis shows that the internal consistency accuracy of the aerial gravity solution of the precise single-point positioning mode and the short baseline differential mode is better than 0.41mGal, and the internal consistency accuracy of the GTGRAV program result is better than 0.50mGal, which meets the relevant needs of offshore aerial gravity measurement.

[0035] For a certain actual survey line data, the internal conformity accuracy obtained by traditional long baseline differential processing is 1.09mGal, while the internal conformity accuracy obtained by the processing of the present invention is 0.346mGal, and the improvement effect is obvious. The research results can provide a certain reference for the use of precise single-point positioning technology in aerial gravity measurement, and have good practical value, especially for gravity measurement in survey areas where it is difficult to establish a station. It has a good demonstration effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A flow chart of a method for obtaining aviation disturbance gravity values ​​according to the present invention;

[0038] Figure 2 A schematic diagram of the internal accuracy of the self-programmed differential mode and GT comparison involved in the method for obtaining aviation disturbance gravity values ​​of the present invention;

[0039] Figure 3 It is a schematic diagram of the internal accuracy of the PPP mode and GT comparison involved in the method for obtaining aviation disturbance gravity value of the present invention;

[0040] Figure 4 It is a schematic diagram of the internal accuracy of the PPP and differential mode and GT comparison involved in the method for obtaining aviation disturbance gravity value of the present invention;

[0041] Figure 5 This is a schematic diagram of the internal coincidence accuracy (traditional difference) of the GT processing of base stations at different distances on the same survey line involved in the method for obtaining aviation disturbance gravity values ​​of the present invention;

[0042] Figure 6 The present invention is a method for obtaining aviation disturbance gravity values ​​and a schematic diagram of the internal accuracy of short-distance base station differentials. DETAILED DESCRIPTION

[0043] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The present invention is further explained below in conjunction with specific implementation modes.

[0045] like Figure 1 As shown, the present embodiment provides a method for obtaining aviation disturbance gravity values, which is to first obtain information on the position and motion parameters of the aircraft carrier based on a precise single-point positioning method; then fuse the information on the position and motion parameters of the aircraft carrier with the measured data of the aviation gravimeter; then construct a Kalman filter model, perform Kalman filtering and Kalman smoothing on the original disturbance gravity value, and obtain the final disturbance gravity value; finally, perform accuracy evaluation on the output disturbance gravity value, and obtain a data processing result that meets the internal accuracy requirements.

[0046] The method for acquiring the position information of the above-mentioned aircraft carrier is: first construct a mathematical model of pseudorange and carrier phase for precise point positioning, use open source positioning software to obtain static precise point positioning results of the base station and the mobile station, and then evaluate the accuracy of the precise point positioning results to ensure that the positioning accuracy meets the requirements of aviation gravity measurement; and when the precise point positioning results are obtained using open source positioning software, the precision of the precise ephemeris product used is required to be better than 2.5 cm, the precision of the precise clock difference product used is required to be better than 75 picoseconds, and the ionosphere model uses data provided by the IGS Analysis Center.

[0047] The method for obtaining the aviation disturbance gravity value of the present invention has the following specific process:

[0048] S100, precise single point positioning

[0049] S101. Constructing mathematical models

[0050] The mathematical model of PPP pseudorange and carrier phase is as follows:

[0051]

[0052] In the above formula (1), r represents the station, s represents the satellite, and i represents the frequency (i = 1, 2). is the pseudorange observation value, is the carrier phase observation value; represents the geometric distance between stations and stars; c is the speed of light in vacuum; δt r and δt s Indicates the receiver clock error and satellite clock error; A / f i 2 First-order ionospheric delay; f i represents the frequency of L1 and L2, λ i is the corresponding wavelength; N is the corresponding integer ambiguity; d r,i and represents the receiver pseudorange bias and satellite pseudorange bias caused by hardware delay on the ith frequency; b r,i and Indicates the receiver phase deviation and satellite phase deviation caused by hardware delay.

[0053] In PPP technology, precise ephemeris is used to eliminate satellite orbit error terms, satellite clock error estimates are used to eliminate satellite clock error terms, and dual-frequency carrier observations are used to eliminate ionospheric effects. The difficulty of the calculation lies mainly in the determination of integer ambiguity. At present, mature PPP calculation software mainly includes GAMIT, RTKlib, PRIDE PPP-AR, GrafNav, etc., all of which can obtain centimeter-level precision products. Considering the convenience of program use, subsequent calculations and discussions are mainly based on the PPP program interface provided by Novatek's GrafNav software. Its precise ephemeris data (*.sp3) and precise clock error files (*.clk) are automatically downloaded from the IGS (International GNSS Service) website. The ionospheric model mainly uses data provided by the European Orbit Determination Center (CODE, Center for Orbit Determination in Europe, Bern, Switzerland).

[0054] Among them, statistical comparison of positioning accuracy after precise single-point processing, on the one hand, verifies whether the relevant products can achieve centimeter-level accuracy, and on the other hand, verifies whether the positioning accuracy meets the requirements of aerial gravity measurement, namely the "Technical Specifications for Aeronautical Gravity Measurement" (DZ / T 0381-2021).

[0055] S102, static positioning accuracy

[0056] First, the static positioning accuracy of the base station is compared. The base station data collected in a certain aerial survey area for more than 12 hours is used to obtain the static coordinates in the Earth-centered Earth-fixed coordinate system through PPP technology. The Geoprobe software of the Natural Resources Airborne Geophysical and Remote Sensing Center is used. After quality statistics, it is found that the positioning accuracy in the XYZ directions is 0.37cm, 0.39cm and 0.20cm respectively, and the three-dimensional space accuracy reaches 0.57cm, which meets the requirements and specifications of aerial gravity for base station positioning.

[0057] Secondly, by comparing the static positioning accuracy of the mobile station, the differential results of the 2-hour short baseline (within 20 km) collected in a certain aerial survey area were used as a benchmark and compared with the results calculated by PPP alone. The positioning accuracy in the XYZ directions was 3.14 cm, 3.45 cm, and 4.55 cm, respectively. The three-dimensional spatial accuracy was about 6.52 cm, and the maximum deviation was within 10 cm, which met the requirements of the measurement specifications.

[0058] Table 1: PPP static positioning accuracy statistics of base stations

[0059]

[0060] Table 2: Mobile station PPP static positioning accuracy statistics

[0061]

[0062] S103. Obtaining dynamic positioning accuracy

[0063] The aerial gravity data measured in a certain survey area were selected for relevant accuracy analysis and comparison. For the traditional differential positioning results, using the data of a close-range base station (within 100km), the differential positioning accuracy in the ENU coordinate system was 1.16cm, 1.00cm and 3.10cm respectively, and the three-dimensional spatial accuracy reached 3.45cm, which has a very high positioning accuracy, slightly better than the result calculated by PPP alone. However, when the base station distance exceeds 500km, taking the ProFlex800 receiver commonly used in aerial gravity measurement as an example, the ideal accuracy obtained by differential post-processing is: horizontal 10mm+1.0ppm, vertical 20mm+1.0ppm, and its positioning deviation is already higher than 50cm, which far exceeds the measurement specification requirements. However, because PPP technology uses non-differential positioning, it is not restricted by distance and the accuracy can be maintained within 10cm.

[0064] Therefore, the above data and analysis show that the application of precise single-point positioning technology can meet the positioning accuracy requirements of aviation gravity.

[0065] S200, Aviation Gravity Solution

[0066] S201, construct basic equations and Kalman filter processing

[0067] Airborne gravity measurement uses gravimeters and GNSS observations to obtain the disturbed gravity along the flight line; ideally, the basic equation for the disturbed gravity along the flight line (disturbed gravity refers to the difference between gravity and normal gravity at the same point in space) is:

[0068]

[0069] Among them, in the above formula (2) is the second derivative of the earth's height h, indicating the vertical acceleration, which is mainly obtained from the GNSS information processed by PPP technology; δg is the disturbance gravity value; f Σ It is the total field of the vertical component acting on the gravimeter sensor after various gravity corrections; δg is the disturbed gravity value; for platform-type aviation gravimeters, gravity corrections mainly include eccentricity correction, Euterworth correction, horizontal acceleration correction, zero drift correction, normal gravity and altitude correction, etc.

[0070] Then, by establishing the Kalman filter state equation including the system state vector and system noise and the Kalman filter measurement equation including the observed quantity and observation noise, the state estimation value at the previous moment is used to estimate the state at the current moment, and then the observed value at the current moment is used to correct it; considering the influence of error and noise, an equation is established based on the measurement error relationship, the disturbance gravity adopts a second-order approximate model, the disturbance gravity is described by a random statistical model, and the system state vector is taken as:

[0071]

[0072] Among them, in the above formula (3), W is the vertical velocity, TF3 is the time delay of the gravimeter anti-aliasing filter, and the theoretical value is 2 seconds; KF3 is the gravimeter scale factor; KF1 and KF2 are the platform installation error angles, which are generally unchanged in a single flight and are usually treated as constants; is the first derivative of the perturbed gravity;

[0073] The above Kalman filter state equation is expressed as:

[0074]

[0075] The specific component forms are as follows:

[0076]

[0077] In the above formula (5), f1, f2, and f3 are the measured values ​​of the two horizontal accelerations and the vertical acceleration of the gravimeter, respectively, and δf T is the low-frequency disturbance caused by the aircraft pitch and roll, q Σ is the overall impact of process noise; the derivatives of the four constants TF3 KF3 KF1 KF, and the second-order derivative of the disturbance gravity are all represented by white noise.

[0078] The above Kalman filter measurement equation is:

[0079] h(t)=H(t)X(t)+δh (6);

[0080] In the above formula (6), h(t) represents the ellipsoid height after eccentricity correction, which is the data obtained by GNSS measurement through PPP technology or differential processing. H(t) is [1 0 0 0 0 0 0 0], and δh represents the measurement noise.

[0081] After the relevant model is constructed, the equation is solved according to the Kalman filter, and the Kalman smoothing process is used to obtain the final disturbance gravity value.

[0082] S202. Data processing

[0083] The GT series three-axis stabilized platform aviation gravity measurement system produced by Russia's GT company (gravimetric technology) is one of the most accurate measurement systems in the world today. The gravity data processing software that comes with the system has excellent solution effect, but as a "black box", the processing details are not completely clear. Therefore, it can only use the measured repeated line data of a certain measurement area in the field to make indirect comparisons through the size of the internal coincidence accuracy.

[0084] The process of obtaining the disturbed gravity value is as follows: Figure 1 As shown in the figure, based on the mobile station data of the GNSS system, the position and velocity information of the mobile station GNSS are obtained by differential processing and PPP technology respectively, and then these data are combined with the gravimeter platform inertial navigation system to obtain the acceleration data, attitude data and platform data of the gravimeter, and finally the obtained information is integrated into the aforementioned Kalman model to solve the disturbed gravity value.

[0085] The specific process of evaluating the accuracy of the disturbed gravity value is as follows: First, the results of the self-compiled differential analysis program and GTGRAV, the differential analysis software provided by GT, are compared for the short baseline measurement data to verify the effectiveness of the self-compiled program. Figure 2 As shown, 10, 70 and 80 correspond to the line numbers of three repeated flights (the numbers after the underline of the line numbers correspond to different processing methods, the same below). After being processed by the differential decomposition program and GTGRAV respectively, the accuracy of the repeated lines after horizontal adjustment is 0.379mGal, which is better than the instrument accuracy of 0.5mGal. This shows that the self-compiled program is correct and effective, and is comparable to the accuracy of GTGRAV.

[0086] Secondly, the gravity solution based on PPP results is compared with the GTGRAV results to measure the effect of the perturbation gravity solution based on PPP. Figure 3 As shown, the accuracy of the internal repeated lines after horizontal adjustment obtained by the PPP-based solution program and GTGRAV processing is 0.395mGal, which is also better than the instrument accuracy of 0.5mGal. This shows that the results obtained based on PPP also have high accuracy and are comparable to the accuracy of the GTGRAV processing program.

[0087] Again, the PPP results, the self-written differential decomposition program and the GTGRAV program are compared on a graph, as shown in the figure below. Figure 4 As shown, the repeated line accuracy obtained by the three processing methods is 0.373mGal, and in comparison, the residuals of PPP and the self-compiled differential decomposition program are comparable (better than 0.41mGal), slightly better than the processing effect of GTGRAV (the residual is slightly greater than 0.4mGal).

[0088] Furthermore, the actual measurement data comparison of a long baseline (Base1, more than 500km) and a short baseline (Base2) is given. Two base stations Base1 and Base2 at different distances are used to solve the problem through the GTGRAV module. After the horizontal adjustment of the two, the internal coincidence accuracy is about 1.09mGal. Figure 5 As shown in the figure, from the curve shape, compared with Base2, the Base1 with an ultra-long baseline has some false abnormal deviations. The traditional differential processing method may be difficult to meet the needs of actual data processing.

[0089] The present invention recalculates the disturbance gravity of the survey line based on the PPP technology, and compares the results with those of Base2, and statistically complies with the accuracy, such as Figure 6 As shown in the figure, it is 0.346mGal. It can be seen that PPP technology is not constrained by distance and can maintain a relatively high solution accuracy in the case of a long baseline (over 500km). It can improve the deficiency of the traditional differential positioning mode that may lead to the inability to obtain reliable motion parameter information as the distance between base stations increases.

[0090] S203. Result Analysis

[0091] The present invention uses self-programming to solve the aviation disturbance gravity of PPP and differential positioning modes respectively, and verifies the effect of the relevant program by comparing with the GT results. From these results, it can be seen that the self-compiled solution program has high accuracy, the differential mode is in good agreement with PPP, and the GTGRAV results are consistent within the instrument accuracy range. In addition, in the case of short baselines, the residuals of PPP and the self-compiled differential solution program are comparable, slightly better than the processing effect of GTGRAV; in the case of long baselines, traditional differential positioning may have unpredictable deviations, while the results of PPP processing can still maintain high solution accuracy.

[0092] S300, draw conclusions

[0093] The processing based on actual aeronautical gravity data shows that the application of precise single-point positioning technology can meet the requirements of aeronautical gravity for positioning accuracy. In addition, the internal accuracy of aeronautical gravity solutions calculated by PPP and differential GNSS is better than 0.41mGal, and the internal accuracy of the combined results with GTGRAV is better than 0.50mGal, which shows that PPP technology can be used for aeronautical gravity measurement, and the results can meet the relevant specifications and actual field operation requirements. The relevant processing shows great superiority. While saving manpower and material resources, it can improve work efficiency and quality of results, and effectively improve the shortcomings of the long-distance differential positioning mode.

[0094] The invention has a reasonable concept and is based on the GNSS precise single-point positioning technology. It does not require the deployment of ground reference stations and can realize efficient solution and processing of aviation gravity data in vast sea areas far away from the mainland and in difficult areas where reference stations cannot be deployed. The aviation gravity solution has high internal accuracy and is suitable for promotion and application.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for obtaining aviation disturbance gravity value, characterized in that: First, based on the precise single-point positioning method, the position and motion parameter information of the aircraft carrier is obtained; then the position and motion parameter information of the aircraft carrier is integrated with the measured data of the aviation gravimeter; Then, the Kalman filter model is constructed, and the original value of the disturbed gravity is subjected to Kalman filtering and Kalman smoothing, and the final disturbed gravity value is output; finally, the output disturbed gravity value is subjected to accuracy evaluation to obtain a data processing result that meets the internal accuracy requirements; The method for acquiring the position information of the aircraft carrier is as follows: firstly constructing a pseudorange and carrier phase mathematical model of precise point positioning, using open source positioning software to obtain static precise point positioning results of the reference station and the mobile station, and then evaluating the accuracy of the precise point positioning results to ensure that the positioning accuracy meets the requirements of aviation gravity measurement; The specific process of the fusion processing is as follows: First, the gravimeter and GNSS observations are used to obtain the disturbed gravity along the flight line. The basic equation of the disturbed gravity along the flight line is: （2）； Among them, in the above formula (2) It is the second derivative of the earth's height h, indicating the vertical acceleration, obtained from the GNSS information processed by precise point positioning; is the disturbance gravity value; It is the total field after various gravity corrections of the vertical component acting on the gravimeter sensor; Then, by establishing the Kalman filter state equation including the system state vector and system noise and the Kalman filter measurement equation including the observed quantity and observation noise, the state estimation value at the previous moment is used to estimate the state at the current moment, and then the observed value at the current moment is used to correct it; the equation is established based on the measurement error relationship, the disturbance gravity adopts the second-order approximate model, the disturbance gravity is described by the random statistical model, and the system state vector is taken as: （3）； Wherein, W in the above formula (3) is the vertical velocity; The time delay of the gravimeter anti-aliasing filter is 2 seconds in theory; is the gravimeter scale factor; and is the platform installation error angle; is the first derivative of the perturbed gravity; The Kalman filter state equation is expressed as: （4）； The specific component form is as follows: (5)； In the above formula (5), are the measured values ​​of the two horizontal accelerations and vertical acceleration of the gravimeter, The low-frequency disturbance caused by the pitch and roll of the aircraft. is the overall impact of process noise; The derivatives of these four constants and the perturbation gravity The second-order derivatives of are all represented by white noise; The Kalman filter measurement equation is: (6)； In the above formula (6), represents the ellipsoid height after eccentricity correction, is [1 0 0 0 0 0 0 0], represents the measurement noise; The specific process of evaluating the accuracy of the disturbed gravity value is as follows: first, the results of the self-compiled differential decomposition program and GT's built-in differential decomposition software GTGRAV are compared for the short baseline measurement data to verify the effectiveness of the self-compiled differential decomposition program; secondly, the gravity solution based on the precise single-point positioning result and the GTGRAV result are compared again to measure the effect of the disturbed gravity solution based on precise single-point positioning; thirdly, the precise single-point positioning result, the self-compiled differential decomposition program and the GTGRAV program are placed on a graph for comparison.

2. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: When the precise single-point positioning results are obtained using open source positioning software, the precision of the precise ephemeris product used is required to be better than 2.5 cm, the precision of the precise clock error product used is required to be better than 75 picoseconds, and the ionosphere model uses data provided by the IGS Analysis Center.

3. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: The mathematical model of pseudorange and carrier phase of the precise point positioning is as follows: (1)； In the above formula (1), r represents the station, s represents the satellite, and i represents the frequency number. is the pseudorange observation value, is the carrier phase observation value; represents the geometric distance between stations and stars; c is the speed of light in vacuum; and Indicates the receiver clock error and satellite clock error; The first-order ionospheric delay can be eliminated by the linear combination of the dual-frequency observations; represents the frequencies of L1 and L2, is the corresponding wavelength; N represents the corresponding integer ambiguity; and represents the receiver pseudorange bias and satellite pseudorange bias caused by hardware delay on the i-th frequency; and Indicates the receiver phase deviation and satellite phase deviation caused by hardware delay.

4. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: The process of obtaining the static precise single-point positioning result of the reference station is as follows: comparing the static positioning accuracy of the reference station, using base station data collected for more than 12 hours in a certain aerial survey area, and obtaining static coordinates in the Earth-centered Earth-fixed coordinate system through precise single-point positioning.

5. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: The process of obtaining the static precise single-point positioning result of the mobile station is as follows: comparing the static positioning accuracy of the mobile station, using the 2-hour short baseline differential result collected in a certain aerial survey area as a benchmark, and comparing it with the result calculated by precise single-point positioning alone to obtain the positioning accuracy in the three directions of XYZ.

6. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: The motion parameter information of the aircraft carrier is obtained by selecting the aviation gravity data measured in a certain flight measurement area and performing dynamic positioning accuracy comparison and analysis; The gravity correction mainly includes eccentricity correction, Euterworth correction, horizontal acceleration correction, zero drift correction, normal gravity and altitude correction; The Kalman filter processing is to solve the equation of the constructed Kalman filter model according to the Kalman filter, and adopt the Kalman smoothing processing to obtain the final disturbance gravity value.

7. The method for obtaining aviation disturbance gravity value according to claim 1, characterized in that: The process of obtaining the disturbed gravity value is as follows: using precise single-point positioning to obtain the position and velocity information of the mobile station GNSS, then combining the obtained position and velocity information of the mobile station GNSS with the gravimeter platform inertial navigation system for solution, obtaining the acceleration data, attitude data and platform data of the gravimeter, and finally integrating the obtained data information into the aforementioned Kalman filter model to solve and obtain the disturbed gravity value that meets the accuracy requirements.

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