Low-orbit paraboloid large-antenna gateway station self-learning tracking method

Abstract

The invention provides a self-learning tracking method for a low-orbit paraboloid large-antenna gateway station. The self-learning tracking method comprises the following steps: S1, acquiring ephemeris parameters and longitude and latitude parameters; s2, calculating to obtain a theoretical pitch angle and a theoretical azimuth angle; s3, controlling the target antenna to track the low earth orbit satellite for the first time and recording to obtain a first round of data set; s4, adding and subtracting the theoretical pitch angle to obtain a plurality of test pitch angles, controlling the target antenna to track the low-orbit satellite for the second time, and recording to obtain a second round of data set; s5, adding and subtracting the theoretical azimuth angle to obtain a plurality of test azimuth angles, controlling the target antenna to track the low earth orbit satellite for the third time, and recording to obtain a third round of data set; and step S6, extracting AGC maximum signal intensity, pitching azimuth rotation data, pitching azimuth coding data and inertial navigation data corresponding to different time points so as to control the target antenna to be aligned with the low-orbit satellite. The method has the beneficial effects that the data sampling error can be reduced, and the satellite alignment precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of antenna tracking and alignment, and in particular to a self-learning tracking method for a low-orbit parabolic large antenna gateway station. Background Art

[0002] The existing satellite data receiving system mainly includes antenna feed subsystem, antenna mount subsystem and tracking receiving subsystem. Among them, the antenna feed subsystem mainly includes parabolic antenna and antenna feed; the antenna mount subsystem mainly includes antenna mount, antenna control unit and antenna driving unit; the tracking receiving subsystem mainly includes combiner signal amplifier, difference signal amplifier, channel synthesis network, down converter and tracking receiver.

[0003] The parabolic antenna reflects the electromagnetic wave signals transmitted by the satellite and converges them to the focus of the parabola. The antenna feed is set at the focus of the parabola to collect all the signal energy converged to the focus of the parabola.

[0004] The combining channel of the feed source generates a combining signal, and its difference channel generates a difference signal. The combining signal contains data information, and the signal is sent to the combining signal amplifier for amplification. The difference signal contains information that the antenna deviates from the receiving direction (that is, when the antenna is facing the receiving direction, the difference signal is zero), and the signal is sent to the difference signal amplifier for amplification. Afterwards, the amplified combining signal and the difference signal are combined into one signal in the channel synthesis network, and the signal is sent to the down converter for frequency conversion and converted into an intermediate frequency signal. The frequency-converted signal is sent to the tracking receiver, which is demodulated by the tracking receiver to restore the error signal. The error signal is sent to the antenna control unit, and the antenna control unit generates an angle deviation instruction based on the error signal. The angle deviation instruction is sent to the antenna drive unit, and the antenna drive unit adjusts the rotation of the antenna mount based on the instruction so that the antenna is aligned with the receiving direction, thereby realizing the automatic tracking of the satellite and data reception by the antenna.

[0005] The tracking performance of the satellite data receiving system determines whether the system can track satellites without blind spots and obtain satellite data. Therefore, before using the satellite data receiving system to receive satellite data, its tracking performance needs to be tested.

[0006] With the development of the domestic low-orbit satellite industry, the current domestic low-orbit parabolic large antenna gateway stations all use single-pulse tracking. The disadvantage of single-pulse tracking is that it requires good RF phase stability, at least two-channel related receivers, and the feed system is large and complex, and the equipment is expensive. The use of the four-speaker method requires microwave structural parts for high-frequency sum and difference network design, which greatly increases the technical complexity and processing difficulty, making the equipment cost expensive.

[0007] In addition, due to the existence of time sampling errors and antenna assembly errors, the elevation data and azimuth data used by the antenna during actual satellite alignment have accuracy problems, which reduces the accuracy of satellite alignment. Summary of the invention

[0008] The technical problem to be solved by the present invention is to reduce data sampling errors and improve satellite tracking accuracy. In order to overcome the defects of the above-mentioned prior art (or related technology), the present invention provides a self-learning tracking method for a low-orbit parabolic large antenna gateway station.

[0009] The present invention provides a low-orbit parabolic large antenna gateway station self-learning tracking method, comprising the following steps: Step S1, for a target antenna in a low-orbit parabolic large antenna gateway station, obtaining the ephemeris parameters of the low-orbit satellite to be docked and the latitude and longitude parameters of the target antenna at time t; Step S2, obtaining a theoretical elevation angle and a theoretical azimuth angle of the target antenna when aligned with the satellite at time t according to the ephemeris parameters and the latitude and longitude parameters; Step S3, based on the theoretical pitch angle and the theoretical azimuth angle, controlling the target antenna to track the low-orbit satellite for the first time, and acquiring and recording the pitch azimuth rotation data, pitch azimuth coding data, inertial navigation data and AGC signal strength data of the target antenna at each time point during the tracking process to obtain a first round of data sets; Step S4, performing addition and subtraction processing of different unit angles on the theoretical pitch angle to obtain a plurality of test pitch angles, for each of the test pitch angles, controlling the target antenna to track the low-orbit satellite for a second time based on the test pitch angle, and acquiring and recording the pitch azimuth rotation data, the pitch azimuth coding data, the inertial navigation data and the AGC signal strength data of the target antenna at each time point during the tracking process to obtain a second round of data sets; Step S5, performing addition and subtraction processing of different unit angles on the theoretical azimuth to obtain a plurality of test azimuths, for each of the test azimuths, controlling the target antenna to track the low-orbit satellite for a third time based on the test azimuth, and acquiring and recording the pitch azimuth rotation data, the pitch azimuth coding data, the inertial navigation data and the AGC signal strength data of the target antenna at each time point during the tracking process to obtain a third round of data sets; Step S6, extracting the AGC maximum signal strength corresponding to different time points and the corresponding pitch-azimuth rotation data, the pitch-azimuth coding data and the inertial navigation data from the first round of data sets, the second round of data sets and the third round of data sets to control the target antenna to align with the low-orbit satellite.

[0010] Compared with the prior art, the low-orbit parabolic large antenna gateway station self-learning tracking method of the present invention has the following advantages: In the present invention, the ephemeris parameters and the longitude and latitude parameters are collected and acquired through step S1, the theoretical pitch angle and the theoretical azimuth angle are calculated through step S2, the first tracking and the first round of data set collection and acquisition are performed through step S3, the theoretical pitch angle is adjusted, the second tracking and the second round of data set collection and acquisition are performed through step S4, the theoretical azimuth angle is adjusted, the third tracking and the third round of data set collection and acquisition are performed through step S5, data extraction and satellite alignment control are performed through step S6, and a large-scale data set is acquired through multiple rounds of adjustment of the theoretical pitch angle and the theoretical azimuth angle, so that high-precision maximum AGC signal strength and corresponding pitch azimuth rotation data, pitch azimuth coding data and inertial navigation data can be extracted from the multiple rounds of data sets, thereby reducing data sampling errors and improving the accuracy of subsequent satellite alignment.

[0011] In a possible implementation, the ephemeris parameters include the semi-major axis, eccentricity, orbital inclination, periapsis argument, ascending node longitude, true anomaly and time parameters of the orbit of the low-orbit satellite, and the longitude and latitude parameters include the current longitude, current latitude and current orbital altitude of the target antenna. In step S2, the theoretical pitch angle and the theoretical azimuth are obtained according to the semi-major axis, the eccentricity, the orbital inclination, the periapsis argument, the ascending node longitude, the true anomaly, the time parameters, the current longitude, the current latitude and the current orbital altitude.

[0012] In a possible implementation manner, in step S2, the theoretical elevation angle and the theoretical azimuth angle of the target antenna when aligned with the satellite at time t are obtained by the following calculation formula: ; in, t represents the time t; EL represents the theoretical pitch angle; AZ represents the theoretical azimuth; a represents the semi-major axis; e represents the eccentricity; i represents the orbital inclination; Ω represents the longitude of the ascending node; ω represents the argument of pericenter; θ represents the true anomaly angle; t0 represents the time parameter; B represents the current longitude; L represents the current latitude; H represents the current ellipsoid height.

[0013] In a possible implementation manner, in step S3, step S4 and step S5, the time interval between adjacent time points is 15 milliseconds.

[0014] In a possible implementation, in step S3, the second round data set is obtained by the following calculation formula: ; in, t-0, t-1, t-2, ..., tn represent the respective time points; EL-0, EL-1, EL-2, ..., EL-n represent the theoretical pitch angles corresponding to the respective time points; AZ-0, AZ-1, AZ-2, ..., AZ-n represent the theoretical azimuths corresponding to the respective time points; EL-M-0, EL-M-1, EL-M-2, ..., EL-Mn represent the pitch rotation angles corresponding to the respective time points; AZ-M-0, AZ-M-1, AZ-M-2, ..., AZ-Mn represent the azimuth rotation angles corresponding to the respective time points; EL-encode-0, EL-encode-1, EL-encode-2, ..., EL-encode-n represent the absolute elevation coding angles corresponding to the respective time points; AZ-encode-0, AZ-encode-1, AZ-encode-2, ..., AZ-encode-n represent the absolute azimuth encoding angles corresponding to the respective time points; EL-INS-0, EL-INS-1, EL-INS-2, ..., EL-INS-n represent the inertial navigation pitch angles corresponding to the respective time points; AZ-INS-0, AZ-INS-1, AZ-INS-2, ..., AZ-INS-n represent the inertial navigation azimuth angles corresponding to the respective time points; AGC-0, AGC-1, AGC-2, ..., AGC-n represent the signal strength values ​​corresponding to the respective time points.

[0015] In a possible implementation, in step S4, the unit angle is set to 0.03 degrees, and the theoretical pitch angle is added or subtracted by a single time, twice, and three times the unit angle to obtain the test pitch angles.

[0016] In a possible implementation, in step S5, the unit angle is set to 0.03 degrees, and the theoretical azimuth is added or subtracted by a single time, twice, and three times the unit angle to obtain each test azimuth.

[0017] In a possible implementation, in step S6, the AGC maximum signal strength corresponding to different time points and the corresponding pitch azimuth rotation data, the pitch azimuth encoding data and the inertial navigation data are obtained by the following calculation formula: ; in, t-0, t-1, t-2, ..., tn represent the respective time points; EL-M-max1 represents the pitch rotation angle corresponding to the maximum signal strength of the AGC at each time point; AZ-M-max1 represents the azimuth rotation angle corresponding to the maximum signal strength of the AGC at each time point; EL-encode-maxl represents the absolute elevation encoding angle corresponding to the maximum signal strength of the AGC at each time point; AZ-encode-maxl represents the absolute azimuth encoding angle corresponding to each time point when the AGC signal strength is maximum; EL-INS-maxl represents the inertial navigation pitch angle corresponding to the maximum signal strength of the AGC at each time point; AZ-INS-maxl represents the inertial navigation azimuth angle corresponding to the maximum signal strength of the AGC at each time point; AGC1 represents the maximum signal intensity of the AGC corresponding to each time point. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0019] First, those skilled in the art should understand that these implementations are only used to explain the technical principles of the embodiments of the present invention, and are not intended to limit the protection scope of the embodiments of the present invention. Those skilled in the art can make adjustments to them as needed to adapt to specific application scenarios.

[0020] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] See also Figure 1The embodiment of the present invention discloses a self-learning tracking method for a low-orbit parabolic large antenna gateway station. From the overall solution, the microwave structure returns to the traditional solution to solve the disadvantage of the high cost of the four-horn method. On the other hand, the tracking accuracy problem is solved from the software algorithm. In terms of tracking performance, the same effect as the single pulse tracking method is achieved; specifically, in terms of microwave structure, the traditional single-horn antenna system is used, and its hardware core components include a high-performance processor, a large-capacity storage unit, a high-precision inertial navigation, a navigation unit, a high-precision encoder, a satellite signal receiver, an azimuth transmission component, a pitch transmission component, an azimuth limit switch, and a pitch limit switch. The software self-learning tracking algorithm includes: 1. Establish an ideal model: Based on the precise ephemeris parameters of the low-orbit satellite and the geographical location of the gateway station (provided by the navigation unit), the theoretical pitch angle and theoretical azimuth angle required by the current target antenna to the satellite can be calculated in real time. At the same time, the target antenna obtains the current pitch value and azimuth value based on the high-precision inertial navigation. Further, the antenna rotates the azimuth and pitch to align it with the satellite in real time; 2. The software self-learning function is mainly used to self-learn various errors to achieve high-precision tracking. Since it is based on an ideal model, the following errors will actually exist: time sampling error and antenna assembly error.

[0022] Continue to see Figure 1 , the definitions involved in the present invention are explained accordingly: (1) EL and AZ: represent the theoretical elevation angle and theoretical azimuth angle; (2) BLH: longitude and latitude height parameter, measured by the navigation unit, indicating the current longitude, latitude and ellipsoid height of the target antenna; (3) EL-INS and AZ-INS: measured by high-precision inertial navigation, indicating the inertial navigation pitch angle and inertial navigation azimuth angle; (4) EL-M and AZ-M: The processor actively drives the pitch and azimuth transmission, and counts the pitch rotation angle and azimuth rotation angle; (5) EL-encode and AZ-encode: encoder readout, indicating the absolute elevation encoding angle and absolute azimuth encoding angle; (6) AGC: signal strength value given by the satellite signal receiver; Ephemeris parameters: provided by the satellite company, and finally imported into the large-capacity storage, representing a: semi-major axis, e: eccentricity, i: orbit inclination, Ω: ascending node longitude, ω: perigee argument, θ: true anomaly, t0: time parameter; t, time parameter, is the time reference provided by the navigation unit.

[0023] Continue to see Figure 1The tracking accuracy requirement of the target antenna of the method of the present invention is 0.03 degrees (taking a 1.8-meter Q / V band antenna as an example, 3 dB is 0.3 degrees, and 1 / 10 is 0.03 degrees); the tracking speed requirement is 3 degrees / second (according to the low-orbit satellite speed, the antenna tracking speed requirement is calculated accordingly); the entire tracking angle requirement is to start tracking from a pitch of 15 degrees, with a total range of 150 degrees.

[0024] Continue to see Figure 1 The specific steps of the method of the present invention are as follows: Step S1, for the target antenna in the low-orbit parabolic large antenna gateway station, obtain the ephemeris parameters of the low-orbit satellite to be docked and the latitude and longitude parameters of the target antenna at time t; Step S2, obtaining the theoretical elevation angle and theoretical azimuth angle of the target antenna when it is aligned with the satellite at time t according to the ephemeris parameters and the longitude and latitude parameters; Step S3, based on the theoretical pitch angle and the theoretical azimuth angle, the target antenna is controlled to track the low-orbit satellite for the first time, and during the tracking process, the pitch azimuth rotation data, the pitch azimuth coding data, the inertial navigation data and the AGC signal strength data of the target antenna are acquired and recorded at each time point to obtain the first round of data sets; Step S4, performing addition and subtraction processing of different unit angles on the theoretical pitch angle to obtain multiple test pitch angles, for each test pitch angle, controlling the target antenna to track the low-orbit satellite for the second time based on the test pitch angle, and acquiring and recording the pitch azimuth rotation data, pitch azimuth coding data, inertial navigation data and AGC signal strength data of the target antenna at each time point during the tracking process to obtain a second round of data sets; Step S5, performing addition and subtraction processing of different unit angles on the theoretical azimuth to obtain multiple test azimuths, for each test azimuth, controlling the target antenna to track the low-orbit satellite for the third time based on the test azimuth, and acquiring and recording the pitch azimuth rotation data, pitch azimuth coding data, inertial navigation data and AGC signal strength data of the target antenna at each time point during the tracking process to obtain a third round of data sets; Step S6, extracting the AGC maximum signal strength corresponding to different time points and the corresponding pitch azimuth rotation data, pitch azimuth coding data and inertial navigation data from the first round data set, the second round data set and the third round data set to control the target antenna to align with the low-orbit satellite.

[0025] Continue to see Figure 1In order to solve the time sampling error in the present invention, based on the tracking speed of 3 degrees / second, the accuracy needs to be controlled at 0.03 degrees, and the longest sampling time is 30 milliseconds / 2, that is, the azimuth and pitch are corrected at least once every 15 milliseconds; at the same time, for the antenna assembly error, considering that there will be certain errors when the antenna is assembled due to the tolerance of the components, that is, the high-precision inertial navigation and navigation devices installed on the antenna have tolerances, but once the assembly is completed, the tolerance value will be fixed, thereby solving the problems of time sampling error and antenna assembly error.

[0026] Continue to see Figure 1 , the implementation process of the method of the present invention includes: 1. Theoretical calculation: {t, EL, AZ} = f(ephemeris parameters, latitude and longitude parameters) = f(a, e, i, Ω, ω ,θ, t0,B,L,H); {t, EL, AZ} means: the theoretical elevation angle EL and the theoretical azimuth angle AZ that need to be adjusted for the antenna to the satellite at time point t; 2. Self-learning tracking algorithm: The first round used the theoretical tracking model: ; Note: In the first round of tracking, EL-M = EL, AZ-M = AZ, that is, when the antenna elevation and azimuth angles rotate, they are consistent with the theoretical calculated values ​​at each time point. At the same time, the elevation and azimuth coding data, inertial navigation data and AGC signal strength data are recorded. The time interval between each time point is 15 milliseconds and saved in a large-capacity memory. In the second round, the theoretical pitch angle EL is added or subtracted by a single unit angle Δel (0.03 degrees), and then the data is tracked and saved. Then, the double unit angle and triple unit angle are added or subtracted, and the tracking and data are saved. The data volume of the second round is 6 times that of the first round. In the third round, the theoretical azimuth angle AZ is added or subtracted by a single unit angle Δaz (0.03 degrees), and then the data is tracked and saved. Then, the double unit angle and triple unit angle are added or subtracted, and the tracking and data are saved. The data volume of the third round is 6 times that of the first round. After multiple rounds of data collection, data extraction is performed: the pitch angle and azimuth angle at the maximum AGC at time t-0 are found, and the corresponding coded data and inertial navigation data are found. Similarly, the data at time tn is found, as follows: ; Among them, XXX-XX-maxl is the data corresponding to the maximum channel strength of AGC in multiple rounds, and AGC1 is the maximum signal strength in each round; Finally, the maximum AGC signal strength can be found at every time from t-0 to tn, and the three sets of data are used as backup for each other: ; When one set of data goes wrong, it can be replaced by the other two sets of data.

[0027] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "in the present embodiment", "specific example", or "some examples" etc. means that the specific features, mechanisms, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, mechanisms, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0028] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A self-learning tracking method for a low-orbit parabolic large antenna gateway station, characterized in that: The following steps are involved: Step S1, for a target antenna in a low-orbit parabolic large antenna gateway station, obtaining ephemeris parameters of a low-orbit satellite to be docked and latitude and longitude parameters of the target antenna; Step S2, obtaining a theoretical elevation angle and a theoretical azimuth angle of the target antenna when aligned with the satellite at time t according to the ephemeris parameters and the latitude and longitude parameters; Step S3, based on the theoretical pitch angle and the theoretical azimuth angle, controlling the target antenna to track the low-orbit satellite for the first time, and acquiring and recording the pitch azimuth rotation data, pitch azimuth coding data, inertial navigation data and AGC signal strength data of the target antenna at each time point during the tracking process to obtain a first round of data sets; Step S4, performing addition and subtraction processing of different unit angles on the theoretical pitch angle to obtain a plurality of test pitch angles, for each of the test pitch angles, controlling the target antenna to track the low-orbit satellite for a second time based on the test pitch angle, and acquiring and recording the pitch azimuth rotation data, the pitch azimuth coding data, the inertial navigation data and the AGC signal strength data of the target antenna at each time point during the tracking process to obtain a second round of data sets; Step S5, performing addition and subtraction processing of different unit angles on the theoretical azimuth to obtain a plurality of test azimuths, for each of the test azimuths, controlling the target antenna to track the low-orbit satellite for a third time based on the test azimuth, and acquiring and recording the pitch azimuth rotation data, the pitch azimuth coding data, the inertial navigation data and the AGC signal strength data of the target antenna at each time point during the tracking process to obtain a third round of data sets; Step S6, extracting the AGC maximum signal strength corresponding to different time points and the corresponding pitch-azimuth rotation data, the pitch-azimuth coding data and the inertial navigation data from the first round of data sets, the second round of data sets and the third round of data sets to control the target antenna to align with the low-orbit satellite.

2. The self-learning tracking method for a low-orbit parabolic large antenna gateway station according to claim 1, characterized in that: The ephemeris parameters include the semi-major axis, eccentricity, orbital inclination, pericenter argument, ascending node longitude, true anomaly and time parameters of the orbit of the low-orbit satellite, and the longitude and latitude parameters include the current longitude, current latitude and current orbital altitude of the target antenna. In step S2, the theoretical pitch angle and the theoretical azimuth are obtained according to the semi-major axis, the eccentricity, the orbital inclination, the pericenter argument, the ascending node longitude, the true anomaly, the time parameters, the current longitude, the current latitude and the current orbital altitude.

3. The self-learning tracking method for a low-orbit parabolic large antenna gateway according to claim 2, characterized in that: In step S2, the theoretical elevation angle and the theoretical azimuth angle of the target antenna when aligned with the satellite at time t are obtained by the following calculation formula: ； in, t represents the time t; EL represents the theoretical pitch angle; AZ represents the theoretical azimuth; a represents the semi-major axis; e represents the eccentricity; i represents the orbital inclination; Ω represents the longitude of the ascending node; ω represents the argument of pericenter; θ represents the true anomaly angle; t0 represents the time parameter; B represents the current longitude; L represents the current latitude; H represents the current ellipsoid height.

4. The self-learning tracking method for a low-orbit parabolic large antenna gateway station according to claim 1, characterized in that: In step S3, step S4 and step S5, the time interval between adjacent time points is 15 milliseconds.

5. The self-learning tracking method for a low-orbit parabolic large antenna gateway station according to claim 1, characterized in that: In step S3, the second round data set is obtained by the following calculation formula: ； in, t-0, t-1, t-2, ..., tn represent the respective time points; EL-0, EL-1, EL-2, ..., EL-n represent the theoretical pitch angles corresponding to the respective time points; AZ-0, AZ-1, AZ-2, ..., AZ-n represent the theoretical azimuths corresponding to the respective time points; EL-M-0, EL-M-1, EL-M-2, ..., EL-Mn represent the pitch rotation angles corresponding to the respective time points; AZ-M-0, AZ-M-1, AZ-M-2, ..., AZ-Mn represent the azimuth rotation angles corresponding to the respective time points; EL-encode-0, EL-encode-1, EL-encode-2, ..., EL-encode-n represent the absolute elevation coding angles corresponding to the respective time points; AZ-encode-0, AZ-encode-1, AZ-encode-2, ..., AZ-encode-n represent the absolute azimuth encoding angles corresponding to the respective time points; EL-INS-0, EL-INS-1, EL-INS-2, ..., EL-INS-n represent the inertial navigation pitch angles corresponding to the respective time points; AZ-INS-0, AZ-INS-1, AZ-INS-2, ..., AZ-INS-n represent the inertial navigation azimuth angles corresponding to the respective time points; AGC-0, AGC-1, AGC-2, ..., AGC-n represent the signal strength values ​​corresponding to the respective time points.

6. The self-learning tracking method for a low-orbit parabolic large antenna gateway station according to claim 1, characterized in that: In the step S4, the unit angle is set to 0.03 degrees, and the theoretical pitch angle is added or subtracted by a single time, twice, and three times the unit angle to obtain the test pitch angles.

7. The self-learning tracking method for a low-orbit parabolic large antenna gateway according to claim 1, characterized in that: In step S5, the unit angle is set to 0.03 degrees, and the theoretical azimuth is added or subtracted by a single time, twice, and three times the unit angle to obtain each test azimuth.

8. The self-learning tracking method for a low-orbit parabolic large antenna gateway according to claim 1, characterized in that: In step S6, the AGC maximum signal strength corresponding to different time points and the corresponding pitch azimuth rotation data, the pitch azimuth encoding data and the inertial navigation data are obtained by the following calculation formula: ； in, t-0, t-1, t-2, ..., tn represent the respective time points; EL-M-max1 represents the pitch rotation angle corresponding to the maximum signal strength of the AGC at each time point; AZ-M-max1 represents the azimuth rotation angle corresponding to the maximum signal strength of the AGC at each time point; EL-encode-maxl represents the absolute elevation encoding angle corresponding to the maximum signal strength of the AGC at each time point; AZ-encode-maxl represents the absolute azimuth encoding angle corresponding to each time point when the AGC signal strength is maximum; EL-INS-maxl represents the inertial navigation pitch angle corresponding to the maximum signal strength of the AGC at each time point; AZ-INS-maxl represents the inertial navigation azimuth angle corresponding to the maximum signal strength of the AGC at each time point; AGC1 represents the maximum signal intensity of the AGC corresponding to each time point.

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