A data fusion method for thermospheric atmospheric density observation using multiple means on the same platform

Abstract

The invention discloses a data fusion method for thermospheric atmospheric density observation by multiple means on the same platform, comprising: obtaining POD measured data and pressure measured data observed on the same satellite; obtaining a first type of thermospheric atmospheric density based on the POD measured data by inversion, and obtaining a second type of thermospheric atmospheric density based on the pressure measured data by calculation; verifying the validity of the two types of density data, and continuing if the verification is passed; otherwise, ending; dividing all thermospheric atmospheric density data into orbital phases to obtain three types of orbital phases; obtaining applicable conditions of the two types of thermospheric atmospheric density data based on the three types of orbital phases and in combination with difference characteristics of the two types of thermospheric atmospheric density data; dynamically correcting the two types of thermospheric atmospheric density data through cross calibration according to the difference characteristics and the applicable conditions, and determining corresponding calibration factors; and completing the fusion of the two types of thermospheric atmospheric density data for the three types of orbital phases according to the calibration factors.

Description

Technical Field

[0001] The present invention belongs to the field of space physics research, relates to the technical field of application research of middle and high-level atmospheric detection, and specifically relates to a data fusion method for thermospheric atmospheric density observation by multiple means on the same platform. Background Art

[0002] Ionization gauges and accelerometers are the main instruments for in-situ detection of thermospheric atmospheric density. Among them, ionization gauges that calculate atmospheric density based on pressure observation data have been carried on early sounding rockets and satellites since the last century. They can realize in-situ observation of thermospheric atmospheric density and have gradually become the main atmospheric density detection instruments in China. Domestic space stations, APOD satellites, spherical satellites and Tianmu constellations are all equipped with OADs (Orbital Atmosphere Detector) containing ionization gauges to realize in-situ detection of orbital atmospheric density. Accelerometers that obtain atmospheric density based on drag inversion have been carried on CHAMP, GRACE satellites and SWARM constellations since the beginning of this century. They are currently the most widely used thermospheric atmospheric density detection instruments abroad. With the accumulation of precise orbital ephemeris information and the improvement of accuracy, non-conservative force acceleration can be obtained based on POD (Precise orbit determination) to invert atmospheric density data, becoming an important means of inverting atmospheric density based on drag in addition to accelerometers. Due to the similar inversion principles, using the atmospheric density inverted by POD to calibrate the atmospheric density data inverted by accelerometer can effectively reduce the systematic error of accelerometer observation data, thereby improving the inversion accuracy of atmospheric density.

[0003] However, there are few studies on the data comparison and calibration of the two methods of obtaining atmospheric density, POD inversion and pressure method, and there is basically no research on the fusion of density data of these two methods. For the fusion of multi-source data of thermospheric atmospheric density, the traditional data fusion method is to use the atmospheric density empirical model to obtain the empirical coefficients of the two data sources. This method not only ignores the characteristics of the data of the two methods, is not conducive to reflecting the true characteristics of atmospheric density, but also introduces systematic errors caused by the atmospheric density empirical model. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the prior art and propose a data fusion method for thermospheric atmospheric density observation by multiple means on the same platform. It provides a data fusion idea for thermospheric atmospheric density observation data by multiple means on the same platform (i.e., the same satellite), and realizes the efficient fusion of density data inverted by POD and density data obtained by pressure method.

[0005] In order to achieve the above object, the present invention proposes a data fusion method for thermospheric atmospheric density observation by multiple means on the same platform, comprising:

[0006] Step 1) Obtain the POD measured data and pressure measured data observed on the same star;

[0007] Step 2) The first type of thermosphere atmospheric density is obtained by inversion based on the POD measured data, and the second type of thermosphere atmospheric density is calculated based on the pressure measured data, thus obtaining thermosphere atmospheric density data of two methods;

[0008] Step 3) Verify the validity of the two types of thermosphere atmospheric density data in step 2). If the verification is successful, proceed to step 4); otherwise, end;

[0009] Step 4) All thermospheric atmospheric density data are divided into orbital phases to obtain three types of orbital phases;

[0010] Step 5) Based on the three types of orbital phases and the difference characteristics of the two types of thermospheric atmospheric density data, the applicable conditions of the two types of thermospheric atmospheric density data are obtained;

[0011] Step 6) According to the difference characteristics and applicable conditions, the two types of thermospheric atmospheric density data are dynamically corrected through cross-calibration to determine the corresponding calibration factors;

[0012] Step 7) Based on the calibration factors, the two types of thermospheric atmospheric density data are fused for the three types of orbital phases.

[0013] Preferably, the POD measured data in step 1) is calculated using GNSS measured data.

[0014] Preferably, the step 2) comprises:

[0015] Based on the drag formula, the POD measured data are inverted to obtain the first type of thermospheric atmospheric density; based on the Maxwell velocity distribution function, the second type of thermospheric atmospheric density is calculated in combination with the measured data of pressure and temperature.

[0016] Preferably, the step 4) comprises:

[0017] First, all the thermospheric atmospheric density data are divided into orbit ascending stage and orbit descending stage;

[0018] Separation of the northern hemisphere mid- and high-latitude regions from the orbit raising and orbit lowering phases As a transitional phase;

[0019] The orbit raising stage and orbit lowering stage are respectively divided into the descending stage and the ascending stage after removing the transition stage.

[0020] Preferably, the applicable condition criterion of the two types of thermosphere atmospheric density data in step 5) is: judging whether the relative error of the two types of thermosphere atmospheric density data meets a preset range value,

[0021] For the ascent phase, if the relative error between the two types of thermospheric atmospheric density data meets the preset range value, it is considered that the two types of thermospheric density data are basically consistent.

[0022] For the descent stage and the transition stage, if the relative error between the two types of thermospheric atmospheric density data exceeds the preset range value, it is considered that there is a difference between the two types of thermospheric atmospheric density data.

[0023] Preferably, the step 6) comprises:

[0024] During the ascent phase, the two types of thermospheric atmospheric density data are basically consistent and do not require correction;

[0025] In the descending stage, the second type of thermosphere atmospheric density data is overestimated. The first type of thermosphere atmospheric density data is used to linearly calibrate the second type of thermosphere atmospheric density data to obtain the corresponding calibration factor a.

[0026] In the transition stage, the first type of thermospheric atmospheric density data is insufficient. The second type of thermospheric atmospheric density data is used to linearly calibrate the first type of thermospheric atmospheric density data to obtain the corresponding calibration factor b.

[0027] Preferably, the step 7) comprises:

[0028] During the ascent phase, the data y after the fusion of the two types of thermospheric atmospheric density data is: y=(POD+OAD) / 2;

[0029] During the descent phase, the data y after the fusion of the two types of thermospheric atmospheric density data is: ;

[0030] In the transition stage, the data y after the fusion of the two types of thermospheric atmospheric density data is: ;

[0031] Among them, POD is the first type of thermospheric atmospheric density data, and OAD is the second type of thermospheric atmospheric density data.

[0032] Compared with the prior art, the advantages of the present invention are:

[0033] 1. Based on high-precision observation data, this invention proposes for the first time a fusion method for atmospheric density data obtained by POD inversion and pressure method on the same platform, which is an effective and universal data fusion method;

[0034] 2. The present invention analyzes the difference between the atmospheric density data obtained by the POD inversion and the pressure method to understand the characteristics of the two methods, creatively proposes three orbital stages, obtains the applicable conditions of each method by analyzing the difference characteristics of typical orbits, and dynamically corrects the density data of the two methods in the three orbital stages in a targeted manner, ultimately achieving long-term and effective fusion of the density data of the two methods, which can be applied to modeling and analysis of multi-method data. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flow chart of the data fusion method of the present invention for thermospheric atmospheric density observation by multiple means on the same platform. DETAILED DESCRIPTION

[0036] The present invention aims at the atmospheric density data obtained by the two methods of POD inversion and pressure method, and for the first time carries out the difference analysis and fusion research of the density data of the two methods, and proposes the data fusion method and ideas of multiple methods with the same satellite. In addition, with the development of detection technology, the accuracy and quality of the observation data of the two methods are also constantly improving, which is more conducive to the application and promotion of the scheme of the present invention. The main contents include: processing POD measured data and pressure measured data to obtain atmospheric density data; studying the response law of atmospheric density of the two methods to the space environment; starting from the principles of the two methods, understanding the data characteristics and influencing factors of the two methods through difference statistical analysis and detail feature analysis, summarizing the scope of application of the two methods (i.e., two types of thermosphere atmospheric density data), and proposing a "staged" dynamic data fusion method based on the analysis results. This method is highly targeted, can scientifically and effectively improve the accuracy and quality of the target data, and has strong applicability, and can be promoted and applied to the long-term fusion of data.

[0037] The "phased" dynamic data fusion method implementation scheme proposed in the present invention mainly includes 6 steps, as follows:

[0038] 1. Preprocessing of measured data: atmospheric density data is obtained by inverting POD measured data; atmospheric density data is obtained by calculating pressure measured data.

[0039] 2. Data verification: The validity of the thermospheric atmospheric density data obtained by POD inversion and pressure measurement is verified by the response law to the space environment.

[0040] 3. Orbital phase division: First, all density data are divided into two common orbital periods, namely the orbit raising phase and the orbit descending phase. Based on the difference in density data between the two methods, a special area of ​​50-90 degrees in the middle and high latitudes of the northern hemisphere is separated from the orbit raising and orbit descending periods. N is the third type of orbital period, and because it is at the junction of two consecutive orbits, it is named the "transition phase"; at this time, the orbit-ascending and orbit-descending phases in the middle and high latitudes of the Northern Hemisphere are removed as the first and second types of orbital periods, respectively. Since the atmospheric density in the orbit-ascending phase is basically decreasing, while the atmospheric density in the orbit-descending phase is basically increasing, in order to highlight the changes in atmospheric density, these two types of orbital periods are named "descending phase" and "ascending phase" respectively.

[0041] 4. Analysis of applicable conditions: Based on the three defined orbital phases: ascending phase, descending phase and transition phase, typical orbital analysis corresponding to the two methods are selected in turn to analyze the difference in atmospheric density characteristics, and the applicable conditions of the two methods are summarized.

[0042] 5. Dynamic correction of density data: Based on the difference characteristics and applicable scope of the above two methods, the density data inverted by POD and the density data obtained by pressure measurement method in each type of orbital stage are dynamically corrected through cross-calibration to obtain the corresponding calibration factors.

[0043] 6. Carry out data fusion in stages: Based on the above correction results, the atmospheric density data of the two methods in the three stages are fused respectively.

[0044] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0045] Example

[0046] like Figure 1 As shown, an embodiment of the present invention proposes a data fusion method for thermospheric atmospheric density observation by multiple means on the same platform, comprising the following steps:

[0047] 1. Based on the measured data of GNSS (Global Navigation Satellite System), POD data is obtained, and the atmospheric density data is inverted by combining the drag formula to obtain the first type of thermosphere atmospheric density data; based on the Maxwell velocity distribution function, the atmospheric density data is calculated in combination with the measured data of pressure and temperature, that is, the second type of thermosphere atmospheric density data.

[0048] The resistance formula is well known in the art and is as follows:

[0049]

[0050] in, is the drag acceleration, is the damping coefficient, is the satellite's area-to-mass ratio, is the relative speed of the satellite, is the inverted atmospheric density, that is, the first type of thermospheric atmospheric density data.

[0051] Satellite-based pressure measurements and measured temperature Calculate the atmospheric density:

[0052]

[0053]

[0054] in, is the atmospheric number density, is the Boltzmann constant, and are the satellite's velocity and angle of attack, is the average molecular mass of the indoor atmosphere, is the average molecular mass of the free atmosphere, is the calculated atmospheric mass density, i.e. the second type of thermospheric atmospheric density data.

[0055] 2. Compare and analyze the first type of thermospheric atmospheric density, namely POD density data, and the second type of thermospheric atmospheric density, namely OAD density data, and their relative errors with the long-term change trend of the space environment index, to determine whether the changes in the density of the two means meet the basic laws and the consistency of the long-term changes in the density data of the two means.

[0056] 3. According to the changes in the atmospheric density itself and the difference in the density data of the two means, the orbital period is divided into three stages: the ascending stage, the descending stage and the transition stage. Assuming that the true value of the atmospheric density can be expressed by the mean of the density data of the two means, that is, (POD+OAD) / 2, the relative error of the density data of the two means is expressed as (POD-OAD) / (POD+OAD). The present invention believes that the relative error distribution of the density data of the two means between [-0.05, 0.05] can be regarded as consistent, and if the absolute value of the error is greater than 0.05, it is considered that there is a difference between the two means of data. The statistical analysis results show that: in the ascending stage, the consistency of the density data of the two means is the best, and the relative error mean is 0.0171; in the descending stage, the OAD atmospheric density may be overestimated due to the influence of the detection airflow, and there is a difference in the density data of the two means, with a relative error mean of -0.1905; in the transition stage, the POD atmospheric density may be overestimated due to the influence of the neutral wind field, and the relative error mean is 0.1318.

[0057] 4. Based on the difference characteristics and applicable scope of the above two methods, the POD inversion density data and pressure measurement method under each type of orbital period are dynamically corrected through cross-calibration of the density data of the two methods. In the ascending stage, the two density data meet the consistency criterion and no correction is required; in the descending stage, the OAD density may be overestimated, and the POD density data is used to linearly calibrate the OAD to obtain the calibration factor a; in the transition stage, the POD density estimation is insufficient, and the OAD density data is used to calibrate it to obtain the calibration factor b.

[0058] 5. Based on the above correction results, the thermospheric atmospheric density data of the two methods in the three orbital stages are fused respectively, and the density fusion result is represented by y:

[0059] In the rising phase, y=(POD+OAD) / 2;

[0060] Descending stage, ;

[0061] Transition phase, .

[0062] Among them, POD is the first type of thermospheric atmospheric density data, and OAD is the second type of thermospheric atmospheric density data.

[0063] Need to explain:

[0064] 1. The "thermospheric atmospheric density", "atmospheric density", "orbital atmospheric density" and "density" mentioned in the present invention all refer to the total mass density of the thermospheric atmosphere.

[0065] 2. The phased dynamic fusion method for multi-means data on the same platform proposed in the present invention is mainly applicable to the detection and application research field of thermospheric atmospheric density.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention is described in detail with reference to the embodiments, it should be understood by those skilled in the art that any modification or equivalent replacement of the technical solutions of the present invention does not depart from the spirit and scope of the technical solutions of the present invention and should be included in the scope of the claims of the present invention.

Claims

1. A data fusion method for thermospheric atmospheric density observation using multiple means on the same platform, comprising: Step 1) Obtain the POD measured data and pressure measured data observed on the same star; Step 2) The first type of thermosphere atmospheric density is obtained by inversion based on the POD measured data, and the second type of thermosphere atmospheric density is calculated based on the pressure measured data; Step 3) Verify the validity of the two types of thermosphere atmospheric density data in step 2). If the verification is successful, proceed to step 4); otherwise, end; Step 4) Divide the verified thermospheric atmospheric density data into orbital phases to obtain three types of orbital phases; Step 5) Based on the three types of orbital phases and the difference characteristics of the two types of thermospheric atmospheric density data, the applicable conditions of the two types of thermospheric atmospheric density data are obtained; Step 6) According to the difference characteristics and applicable conditions, the two types of thermospheric atmospheric density data are dynamically corrected through cross-calibration to determine the corresponding calibration factors; Step 7) Based on the calibration factors, the two types of thermospheric atmospheric density data are fused for the three types of orbital phases; The step 4) comprises: First, all the thermospheric atmospheric density data are divided into orbit ascending stage and orbit descending stage; Separation of the northern hemisphere mid- and high-latitude regions from the orbit raising and orbit lowering phases As a transitional phase; The orbit raising stage and orbit lowering stage are respectively divided into the descending stage and the ascending stage after removing the transition stage.

2. The data fusion method for thermospheric atmospheric density observation by multiple means on the same platform according to claim 1 is characterized in that: The POD measured data in step 1) is calculated using GNSS measured data.

3. The data fusion method for thermospheric atmospheric density observation by multiple means on the same platform according to claim 1 is characterized in that: The step 2) comprises: Based on the drag formula, the POD measured data are inverted to obtain the first type of thermospheric atmospheric density; based on the Maxwell velocity distribution function, the second type of thermospheric atmospheric density is calculated in combination with the measured data of pressure and temperature.

4. The data fusion method for thermospheric atmospheric density observation by multiple means on the same platform according to claim 1 is characterized in that: The applicable condition criterion of the two types of thermosphere atmospheric density data in step 5) is: judging whether the relative error of the two types of thermosphere atmospheric density data meets the preset range value, For the ascent phase, if the relative error between the two types of thermospheric atmospheric density data meets the preset range value, it is considered that the two types of thermospheric density data are basically consistent. For the descent stage and the transition stage, if the relative error between the two types of thermospheric atmospheric density data exceeds the preset range value, it is considered that there is a difference between the two types of thermospheric atmospheric density data.

5. The data fusion method for thermospheric atmospheric density observation by multiple means on the same platform according to claim 4 is characterized in that: The step 6) comprises: During the ascent phase, the two types of thermospheric atmospheric density data are basically consistent and do not require correction; In the descending stage, the second type of thermosphere atmospheric density data is overestimated. The first type of thermosphere atmospheric density data is used to linearly calibrate the second type of thermosphere atmospheric density data to obtain the corresponding calibration factor a. In the transition stage, the first type of thermospheric atmospheric density data is insufficient. The second type of thermospheric atmospheric density data is used to linearly calibrate the first type of thermospheric atmospheric density data to obtain the corresponding calibration factor b.

6. The data fusion method for thermospheric atmospheric density observation by multiple means on the same platform according to claim 5 is characterized in that: The step 7) comprises: During the ascent phase, the data y after the fusion of the two types of thermospheric atmospheric density data is: y=(POD+OAD) / 2; During the descent phase, the data y after the fusion of the two types of thermospheric atmospheric density data is: ; In the transition stage, the data y after the fusion of the two types of thermospheric atmospheric density data is: ; Among them, POD is the first type of thermospheric atmospheric density data, and OAD is the second type of thermospheric atmospheric density data.

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