A satellite signal tracking method, apparatus, computer equipment, and storage medium

Abstract

This application discloses a satellite signal tracking method, apparatus, computer equipment, and storage medium. The method includes: acquiring the linear velocity of a target satellite; calculating the radial velocity of the target satellite relative to the ground terminal at the current moment based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment; acquiring a pre-constructed Doppler frequency shift expression; establishing a drift trend estimator based on the Doppler frequency shift expression; and constructing a frequency shift predictor based on the drift trend estimator; calculating the predicted frequency shift for the next moment based on the radial velocity and the frequency shift predictor; and scanning the target satellite signal based on the predicted frequency shift and a pre-set frequency scanning window. Applying the solution provided in this application can improve the stability of satellite signal tracking.

Description

Technical Field

[0001] This application relates to the field of satellite signal tracking technology, and more specifically, to a satellite signal tracking method, apparatus, computer equipment, and storage medium. Background Technology

[0002] With the rapid deployment of Low Earth Orbit (LEO) satellite constellations, such as Starlink and OneWeb, ground terminals need to stably track multiple high-speed moving satellite signals in a highly dynamic environment. Because LEO satellites operate at high speeds, averaging approximately 7.5 km / s, and have short dwell times within their field of view, tracking them is quite challenging.

[0003] Known satellite signal tracking methods primarily rely on phased array antenna beam pointing control. This approach requires real-time acquisition of satellite orbital parameters and prediction of motion models, resulting in high algorithm complexity and long computation time, leading to significant tracking lag and poor stability. Therefore, improving the stability of satellite signal tracking has become a pressing technical problem. Summary of the Invention

[0004] This application provides a satellite signal tracking method, apparatus, computer equipment, and storage medium to improve the stability of satellite signal tracking. The specific technical solution is as follows.

[0005] In a first aspect, embodiments of this application provide a satellite signal tracking method, the method being applied to a ground terminal, the method comprising: Obtain the linear velocity of the target satellite, and calculate the radial velocity of the target satellite relative to the ground terminal at the current moment based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. Obtain a pre-constructed Doppler frequency shift expression, establish a drift trend estimator based on the Doppler frequency shift expression, and construct a frequency shift predictor based on the drift trend estimator; The predicted frequency shift for the next moment is calculated based on the radial velocity and the frequency shift predictor. Based on the predicted frequency shift and the pre-set frequency scanning window, the target satellite is scanned for signals.

[0006] As one embodiment of this application, the step of establishing a drift trend estimator based on the Doppler frequency shift expression and constructing a frequency shift predictor based on the drift trend estimator includes: The drift trend estimator is obtained by performing a first-order difference on the Doppler frequency shift expression; A frequency shift predictor is constructed based on the Doppler frequency shift expression and the drift trend estimator.

[0007] As one embodiment of this application, the step of constructing a frequency shift predictor based on the Doppler frequency shift expression and the drift trend estimator includes: Construct the following frequency shift predictor: in, The Doppler shift at the current moment, For the drift trend estimator, the This is the predicted frequency shift for the next time step.

[0008] As one embodiment of this application, the method further includes: Acquire the signal parameters of the received signal; the signal parameters include at least the carrier-to-noise ratio, the phase change rate, and the cross-correlation peak value. Calculate the overall error factor of the received signal based on the signal parameters; When the comprehensive error factor is greater than or equal to a preset threshold, the frequency shift values ​​of the most recent preset number of time moments are counted, the frequency shift change value between every two adjacent time moments is calculated based on each frequency shift value, and a frequency shift trend prediction model is obtained by fitting. Based on the frequency shift change value and the frequency shift trend prediction model, the center value of the frequency scanning window is calculated, and based on the center value of the frequency scanning window and the frequency scanning window, the target satellite is scanned again.

[0009] As one embodiment of this application, the step of calculating the comprehensive error factor of the received signal based on the signal parameters includes: Calculate the comprehensive error factor using the following formula. : in, , , All of these are pre-set weighting coefficients; Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, This represents the ideal peak value.

[0010] As one embodiment of this application, the step of calculating the center value of the frequency scanning window based on the frequency shift change value and the frequency shift trend prediction model includes: Calculate the center value of the frequency scanning window using the following formula. : in, For the frequency shift trend prediction model, The average value of each frequency shift change is given. This is the preset feedback gain coefficient; in, , These are the fitting coefficients. t It is a time variable.

[0011] Secondly, embodiments of this application provide a satellite signal tracking device, which is applied to a ground terminal, and the device includes: The velocity acquisition module is used to acquire the linear velocity of the target satellite and, based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment, calculate the radial velocity of the target satellite relative to the ground terminal at the current moment. A predictor building module is used to obtain a pre-built Doppler frequency shift expression, build a drift trend estimator based on the Doppler frequency shift expression, and build a frequency shift predictor based on the drift trend estimator. A frequency shift prediction module is used to calculate the predicted frequency shift for the next moment based on the radial velocity and the frequency shift predictor. The signal tracking module is used to scan the target satellite for signals based on the predicted frequency shift and a pre-set frequency scanning window.

[0012] As one embodiment of this application, the predictor construction module is specifically used for: The drift trend estimator is obtained by performing a first-order difference on the Doppler frequency shift expression; A frequency shift predictor is constructed based on the Doppler frequency shift expression and the drift trend estimator.

[0013] As one embodiment of this application, the predictor construction module is specifically used to: construct the following frequency shift predictor: in, The Doppler shift at the current moment, For the drift trend estimator, the This is the predicted frequency shift for the next time step.

[0014] As one embodiment of this application, the apparatus further includes: The signal parameter acquisition module is used to acquire the signal parameters of the received signal; the signal parameters include at least the carrier-to-noise ratio, the phase change rate, and the cross-correlation peak value. The comprehensive error factor calculation module is used to calculate the comprehensive error factor of the received signal based on the signal parameters. The model fitting module is used to count the frequency shift values ​​of the most recent preset number of times when the comprehensive error factor is greater than or equal to a preset threshold, calculate the frequency shift change value between every two adjacent times based on each frequency shift value, and fit the frequency shift trend prediction model. The rescan module is used to calculate the center value of the frequency scan window based on the frequency shift change value and the frequency shift trend prediction model, and to scan the target satellite again based on the center value of the frequency scan window and the frequency scan window.

[0015] As one embodiment of this application, the comprehensive error factor calculation module is specifically used for: Calculate the comprehensive error factor using the following formula. : in, , , All of these are pre-set weighting coefficients; Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, This represents the ideal peak value.

[0016] As one embodiment of this application, the rescan module is specifically used for: Calculate the center value of the frequency scanning window using the following formula. : in, For the frequency shift trend prediction model, The average value of each frequency shift change is given. This is the preset feedback gain coefficient; in, , These are the fitting coefficients. t It is a time variable.

[0017] Thirdly, embodiments of this application provide a computer device, including: a memory and a processor, wherein the memory and the processor are coupled together; The memory is used to store one or more computer instructions; The processor is used to execute one or more computer instructions to implement the satellite signal tracking method as described in the first aspect.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium having stored thereon one or more computer instructions that are executed by a processor to implement the satellite signal tracking method as described in the first aspect above.

[0019] Fifthly, this application provides a computer program product, which includes a computer program that, when executed by a processor, implements the satellite signal tracking method described in the first aspect.

[0020] In this embodiment, after obtaining the target satellite's linear velocity, the radial velocity of the target satellite relative to the ground terminal at the current moment can be calculated based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. Then, a pre-constructed Doppler frequency shift expression is obtained, a drift trend estimator is established based on the Doppler frequency shift expression, and a frequency shift predictor is constructed based on the drift trend estimator. Finally, the predicted frequency shift for the next moment is calculated based on the radial velocity and the frequency shift predictor, and the target satellite signal is scanned based on the predicted frequency shift and a pre-set frequency scanning window. In other words, in this embodiment, the predicted frequency shift of the target satellite for the next moment can be calculated based on the constructed frequency shift predictor after only calculating the radial velocity of the target satellite. This algorithm is simple, time-saving, and has a small lag in satellite signal tracking, thereby improving the stability of satellite signal tracking. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0022] Figure 1 A schematic flowchart of a satellite signal tracking method provided in an embodiment of this application is shown; Figure 2 This paper shows a schematic diagram of the structure of a satellite signal tracking device provided in an embodiment of this application; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0024] It should be noted that the terms "comprising" and "having," and any variations thereof, in the embodiments and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0025] This application discloses a satellite signal tracking method, apparatus, computer equipment, and storage medium, which can improve the stability of satellite signal tracking. The embodiments of this application are described in detail below.

[0026] Low Earth Orbit (LEO) satellites, also known as low-Earth orbit satellites, generally refer to artificial satellites with an orbital altitude of 200-2000 kilometers. LEO satellites are primarily used for military target detection, as they easily obtain high-resolution images of targets. LEO satellites are also used for mobile phone communications; their low orbital altitude results in short transmission delays and minimal path loss.

[0027] In low-Earth orbit satellite communication, the frequency of the received signal changes significantly and rapidly due to the high speed of satellite movement, with Doppler shifts reaching hundreds of kHz. Therefore, accurately calculating and tracking the satellite frequency is a major challenge in accurately tracking satellite signals. Large errors in frequency calculation can lead to tracking failures; for example, incorrect frequency scanning or a frequency scanning window that does not cover the actual signal frequency can result in missed detections or misjudgments of signal non-existence.

[0028] Figure 1 The diagram illustrates a flow chart of a satellite signal tracking method provided in an embodiment of this application. This method can be applied to a ground terminal, and the process may include the following steps: S110: Obtain the linear velocity of the target satellite. Based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment, calculate the radial velocity of the target satellite relative to the ground terminal at the current moment.

[0029] In this embodiment, the ground terminal can track signals from multiple low-Earth orbit (LEO) satellites, and the signal tracking method is identical for each LEO satellite. Therefore, the satellite signal tracking method of this embodiment can be illustrated by taking the tracking of any LEO satellite (which can be referred to as the target satellite) by the ground terminal as an example.

[0030] When a low-Earth orbit satellite revolves around the Earth, its speed, or linear velocity, is not always directed toward the ground terminal. However, during signal tracking, only the radial component of the satellite relative to the ground terminal (LOS direction, Line of Sight) affects frequency shift prediction.

[0031] Therefore, in this embodiment, after obtaining the linear velocity of the target satellite, the radial velocity of the target satellite relative to the ground terminal at the current moment can be calculated based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. The angle between the target satellite and the ground terminal can be measured in real time. In one implementation, the radial velocity of the target satellite relative to the ground terminal at the current moment can be calculated using the following formula. : = in, This refers to the satellite's linear velocity. It is the angle between the satellite and the ground terminal receiver, which varies with time in the field of view; when the satellite rises above the horizon, θ≈90°. ∘ ,so θ≈0; when the satellite passes directly overhead, θ≈0 ∘ ,but ≈ .

[0032] LEO satellites typically operate at an altitude of 550 km, and their linear velocity during one orbit around the Earth is approximately: in, It is the gravitational constant; Earth mass; This is the Earth's radius (approximately 6371 km). The altitude is the satellite's altitude (e.g., 550 km).

[0033] S120: Obtain the pre-constructed Doppler frequency shift expression, build a drift trend estimator based on the Doppler frequency shift expression, and build a frequency shift predictor based on the drift trend estimator.

[0034] During target satellite signal tracking, stable tracking can be achieved if the frequency shift of the target satellite can be accurately determined. In this embodiment, the radial velocity of the LEO satellite relative to the ground terminal can be used as the tracking parameter. Based on this, the following Doppler frequency shift expression is constructed to estimate the Doppler frequency shift. : in, Radial velocity of the satellite relative to the ground terminal (unit: m / s); The speed of light (approximately 3 × 10⁻⁶) 8 m / s); The carrier frequency (e.g., approximately 14 GHz for the Ku band).

[0035] Furthermore, a drift trend estimator can be established based on the Doppler frequency shift expression, and a frequency shift predictor can be constructed based on the drift trend estimator. In one implementation, the Doppler frequency shift expression can be subjected to a first-order difference to obtain the drift trend estimator, and then the frequency shift predictor can be constructed based on the Doppler frequency shift expression and the drift trend estimator.

[0036] For example, it is possible to By performing first-order differencing, we obtain the drift trend estimator. : in, The Doppler shift at the current moment, This represents the Doppler frequency shift from the previous moment.

[0037] Further build the predictor: in, This is the predicted frequency shift for the next time step.

[0038] In other words, we can first determine the frequency shift change value of the target satellite, and then use the sum of the current frequency shift and the frequency shift change value as the predicted frequency shift for the next moment.

[0039] The Doppler shift at the current moment represents the offset of the current satellite signal frequency relative to its stationary state. This represents the frequency shift difference between the current time and the previous time, indicating the trend of frequency shift change. This is the predicted frequency shift for the next time step, i.e., the predicted value used to guide frequency tracking.

[0040] S130: Calculate the predicted frequency shift for the next moment based on the radial velocity and the frequency shift predictor.

[0041] As can be seen from the above expression, once the radial velocity of the target satellite relative to the ground terminal at the current moment is calculated, it can be substituted into the Doppler frequency shift expression to obtain the Doppler frequency shift of the target satellite at the current moment. Furthermore, the frequency shift change value can be calculated based on the drift trend estimator, and finally the predicted frequency shift at the next moment can be calculated based on the predictor.

[0042] S140: Based on the predicted frequency shift and the pre-set frequency scanning window, perform signal scanning on the target satellite.

[0043] After calculating the predicted frequency shift of the target satellite at the next moment, the signal of the target satellite can be scanned according to the predicted frequency shift and the pre-set frequency scanning window. For example, the signal can be scanned at the predicted frequency. Set a frequency search window (e.g., ±5 kHz) in the vicinity and perform a fast scan.

[0044] Furthermore, after scanning, the presence of a signal can be detected, for example, by using Fast Fourier Transform (FFT) and maximum likelihood detection to determine signal presence. If a match is found, it indicates the presence of the signal, and the system can enter lock mode; otherwise, a re-search is triggered. In satellite signal reception and tracking, "lock mode" refers to the working state where the receiving terminal successfully acquires and stably tracks the target signal.

[0045] In this embodiment, after obtaining the target satellite's linear velocity, the radial velocity of the target satellite relative to the ground terminal at the current moment can be calculated based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. Then, a pre-constructed Doppler frequency shift expression is obtained, a drift trend estimator is established based on the Doppler frequency shift expression, and a frequency shift predictor is constructed based on the drift trend estimator. Finally, the predicted frequency shift for the next moment is calculated based on the radial velocity and the frequency shift predictor, and the target satellite signal is scanned based on the predicted frequency shift and a pre-set frequency scanning window. In other words, in this embodiment, the predicted frequency shift of the target satellite for the next moment can be calculated based on the constructed frequency shift predictor after only calculating the radial velocity of the target satellite. This algorithm is simple, time-saving, and has a small lag in satellite signal tracking, thereby improving the stability of satellite signal tracking.

[0046] It is understandable that, due to the potential for sudden changes in the frequency of low-Earth orbit satellites, the signal tracking performance may vary, with some satellites performing well while others perform poorly.

[0047] In one embodiment of this application, in order to further improve the stability of satellite signal tracking, after scanning the target satellite signal, the received signal can also be detected. When the received signal is poor, the center value of the frequency scanning window can be adjusted, and the drift trend prediction model can be refitted.

[0048] In one implementation, the ground terminal first acquires the signal parameters of the received signal. These parameters include at least the carrier-to-noise ratio, phase change rate, and cross-correlation peak value. Based on these parameters, a comprehensive error factor for the received signal is calculated. Then, when the comprehensive error factor is greater than or equal to a preset threshold, the frequency shift values ​​at the most recent preset number of moments are statistically analyzed. The frequency shift change value between every two adjacent moments is calculated based on these frequency shift values, and a frequency shift trend prediction model is fitted. Finally, based on the frequency shift change value and the frequency shift trend prediction model, the center value of the frequency scanning window is calculated. Based on the center value of the frequency scanning window and the frequency scanning window itself, the target satellite signal is scanned again. The aforementioned signal parameters can be extracted in real-time by the ground terminal from the actually received satellite signals.

[0049] The overall error factor reflects the magnitude of the error between the actual received signal and the ideal signal. A larger overall error factor indicates a greater error between the actual received signal and the ideal signal, resulting in less effective signal tracking; conversely, a smaller overall error factor indicates a smaller error between the actual received signal and the ideal signal, resulting in better signal tracking.

[0050] For example, the comprehensive error factor can be calculated using the following formula. : in, , , All of these are pre-set weighting coefficients, which can be dynamically adjusted according to the application scenario. Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, The set ideal peak value.

[0051] Understandable. , , Three weighting coefficients are used to adjust the error factor. The importance of each indicator can usually be dynamically set according to the specific application scenario. Specifically, This is used to measure the deviation of the carrier-to-noise ratio C / N0. If the channel quality (such as multipath interference) changes drastically, this value can be appropriately increased. It reflects the impact of phase continuity and is applicable to coherent carrier tracking scenarios; The relevant peak value is used as an important basis for judging the existence of a signal, and is especially suitable for initial acquisition or when there is a risk of frequency jump.

[0052] In one implementation, the values ​​of the aforementioned weighting coefficients can be set through experimental simulation or online training. For example, a set of reasonable initial values ​​can be determined using the minimum mean square error criterion, such as the following values: =0.4, =0.3, =0.3.

[0053] As a reference carrier-to-noise ratio (C / N ratio), this value is an empirical benchmark under "good signal" conditions, and is typically set using the following methods: It is obtained from historical measurements and statistics; for example, if the average C / N0 when a ground terminal tracks signals in this frequency band is 38 dB-Hz, then... Set to 38 dB-Hz.

[0054] This is the set ideal peak value, which is usually the maximum value that the cross-correlation function should reach under ideal matching conditions, reflecting the signal lock-in state. Specifically, it can be set based on the maximum correlation peak value in the simulation when there is no frequency offset / phase error; or it can be estimated based on the average peak value among multiple successfully captured samples. For example, the average of multiple correlation peak values ​​during steady-state tracking can be taken. If the measured correlation peak value is stable around 1.0, then it can be set... =0.95.

[0055] When E(t) > ϵ, it indicates poor signal tracking performance. In this case, feedback correction can be triggered to update. The correction involves adjusting the center value of the frequency scan window and refitting the drift trend prediction model.

[0056] Specifically, frequency shift data points from the most recent N time moments can be collected as a time series of the frequency change rate; a linear model can then be fitted using the weighted least squares (WLS) method. ,in, , These are the fitting coefficients. The variable is time. This is a trend prediction method, which predicts the location of the frequency center over a future period based on the changing trends of historical frequency data. Furthermore, the weight of each sample point can be set to 1 / E(t), meaning that the better the signal quality (the smaller the overall error factor), the greater the impact of that point on the fit, thereby improving the robustness of the prediction model.

[0057] In one implementation, the center value of the frequency scanning window can be adjusted to... : in, For frequency shift trend prediction models, The average value of each frequency shift change is given. The preset feedback gain coefficient can be adaptively adjusted based on historical tracking offsets.

[0058] In this embodiment, after scanning the target satellite signal, the received signal can be detected. When the received signal is poor, the center value of the frequency scanning window can be adjusted, and the drift trend prediction model can be refitted, thereby further improving the stability of satellite signal tracking.

[0059] In one specific embodiment, during a ground station test, the target was a LEO satellite with an orbital altitude of approximately 550 km, a carrier frequency of 14.25 GHz, and a minimum elevation angle of 30°. According to orbital mechanics, the satellite's maximum radial velocity relative to the ground is approximately 7.5 km / s. Therefore, the maximum Doppler shift is: Using the method provided in the embodiments of this application for simulation, the average error of the prediction model is less than ±500 Hz, the tracking and holding rate is above 90%, and the first acquisition time is less than 1 second, which is far superior to the performance of traditional prediction methods (the holding rate is only about 72%, and the first acquisition time is about 2.3 seconds).

[0060] Furthermore, the method provided in this application embodiment was embedded into an FPGA+DSP hardware platform for verification. A 256-point FFT module was used, with an update period of 10 ms. The signal feature feedback processing module occupied approximately 5% of the logic resources. In actual testing, it can stably track more than 20 low-Earth orbit satellites in a real environment, with the average C / N0 remaining above 38 dB-Hz.

[0061] Furthermore, the method provided in this application is also applicable to different orbital inclination angles (0°–98°) and different communication frequency bands (such as Ku, Ka, etc.), by adjusting Δt, window width, and feedback coefficient α. i These parameters allow for quick adaptation to different constellation systems.

[0062] Figure 2 This illustration shows a schematic diagram of a satellite signal tracking device according to an embodiment of this application. The device is applied to a ground terminal and includes: The velocity acquisition module 210 is used to acquire the linear velocity of the target satellite and calculate the radial velocity of the target satellite relative to the ground terminal at the current moment based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. The predictor building module 220 is used to obtain a pre-built Doppler frequency shift expression, build a drift trend estimator based on the Doppler frequency shift expression, and build a frequency shift predictor based on the drift trend estimator. Frequency shift prediction module 230 is used to calculate the predicted frequency shift for the next moment based on the radial velocity and the frequency shift predictor. The signal tracking module 240 is used to scan the target satellite for signals based on the predicted frequency shift and a pre-set frequency scanning window.

[0063] As one embodiment of this application, the predictor construction module 220 is specifically used for: The drift trend estimator is obtained by performing a first-order difference on the Doppler frequency shift expression; A frequency shift predictor is constructed based on the Doppler frequency shift expression and the drift trend estimator.

[0064] As one embodiment of this application, the predictor construction module 220 is specifically used to: construct the following frequency shift predictor: in, The Doppler shift at the current moment, For the drift trend estimator, the This is the predicted frequency shift for the next time step.

[0065] As one embodiment of this application, the apparatus further includes: The signal parameter acquisition module is used to acquire the signal parameters of the received signal; the signal parameters include at least the carrier-to-noise ratio, the phase change rate, and the cross-correlation peak value. The comprehensive error factor calculation module is used to calculate the comprehensive error factor of the received signal based on the signal parameters. The model fitting module is used to count the frequency shift values ​​of the most recent preset number of times when the comprehensive error factor is greater than or equal to a preset threshold, calculate the frequency shift change value between every two adjacent times based on each frequency shift value, and fit the frequency shift trend prediction model. The rescan module is used to calculate the center value of the frequency scan window based on the frequency shift change value and the frequency shift trend prediction model, and to scan the target satellite again based on the center value of the frequency scan window and the frequency scan window.

[0066] As one embodiment of this application, the comprehensive error factor calculation module is specifically used for: Calculate the comprehensive error factor using the following formula. : in, , , All of these are pre-set weighting coefficients; Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, This represents the ideal peak value.

[0067] As one embodiment of this application, the rescan module is specifically used for: Calculate the center value of the frequency scanning window using the following formula. : in, For the frequency shift trend prediction model, The average value of each frequency shift change is given. This is the preset feedback gain coefficient; in, , These are the fitting coefficients. t It is a time variable.

[0068] In this embodiment, after obtaining the target satellite's linear velocity, the radial velocity of the target satellite relative to the ground terminal at the current moment can be calculated based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. Then, a pre-constructed Doppler frequency shift expression is obtained, a drift trend estimator is established based on the Doppler frequency shift expression, and a frequency shift predictor is constructed based on the drift trend estimator. Finally, the predicted frequency shift for the next moment is calculated based on the radial velocity and the frequency shift predictor, and the target satellite signal is scanned based on the predicted frequency shift and a pre-set frequency scanning window. In other words, in this embodiment, the predicted frequency shift of the target satellite for the next moment can be calculated based on the constructed frequency shift predictor after only calculating the radial velocity of the target satellite. This algorithm is simple, time-saving, and has a small lag in satellite signal tracking, thereby improving the stability of satellite signal tracking.

[0069] The following describes a computer device provided in an embodiment of this application. Please refer to [link / reference needed]. Figure 3 , Figure 3A schematic diagram of a computer device provided in an embodiment of this application, the computer device comprising: One or more processors 40; The processor 40 is coupled to a storage device 41, which is used to store one or more programs. When the one or more programs are executed by the one or more processors 40, the electronic device performs the following functions: Figure 1 The technical solution of the satellite signal tracking method is described above.

[0070] This application also provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement... Figure 1 The technical solution of the satellite signal tracking method is described above.

[0071] This application provides a computer program product, which includes a computer program that, when executed by a processor, implements the following: Figure 1 The technical solution of the satellite signal tracking method is described above.

[0072] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application.

[0073] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A satellite signal tracking method, characterized in that, The method is applied to a ground terminal, and the method includes: Obtain the linear velocity of the target satellite, and calculate the radial velocity of the target satellite relative to the ground terminal at the current moment based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment. Obtain a pre-constructed Doppler frequency shift expression, establish a drift trend estimator based on the Doppler frequency shift expression, and construct a frequency shift predictor based on the drift trend estimator; The predicted frequency shift for the next moment is calculated based on the radial velocity and the frequency shift predictor. Based on the predicted frequency shift and the pre-set frequency scanning window, the target satellite is scanned for signals. Acquire the signal parameters of the received signal; the signal parameters include at least the carrier-to-noise ratio, the phase change rate, and the cross-correlation peak value. Calculate the overall error factor of the received signal based on the signal parameters; When the comprehensive error factor is greater than or equal to a preset threshold, the frequency shift values ​​of the most recent preset number of time moments are counted, the frequency shift change value between every two adjacent time moments is calculated based on each frequency shift value, and a frequency shift trend prediction model is obtained by fitting. Based on the frequency shift change value and the frequency shift trend prediction model, the center value of the frequency scanning window is calculated, and based on the center value of the frequency scanning window and the frequency scanning window, the target satellite is scanned again. The step of calculating the comprehensive error factor of the received signal based on the signal parameters includes: Calculate the comprehensive error factor using the following formula. : in, , , All of these are pre-set weighting coefficients; Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, This represents the ideal peak value.

2. The method according to claim 1, characterized in that, The steps of establishing a drift trend estimator based on the Doppler frequency shift expression and constructing a frequency shift predictor based on the drift trend estimator include: The drift trend estimator is obtained by performing a first-order difference on the Doppler frequency shift expression; A frequency shift predictor is constructed based on the Doppler frequency shift expression and the drift trend estimator.

3. The method according to claim 2, characterized in that, The step of constructing a frequency shift predictor based on the Doppler frequency shift expression and the drift trend estimator includes: Construct the following frequency shift predictor: in, The Doppler shift at the current moment, For the drift trend estimator, the This is the predicted frequency shift for the next time step.

4. The method according to claim 1, characterized in that, The step of calculating the center value of the frequency scanning window based on the frequency shift change value and the frequency shift trend prediction model includes: Calculate the center value of the frequency scanning window using the following formula. : in, For the frequency shift trend prediction model, The average value of each frequency shift change is given. This is the preset feedback gain coefficient; in, , These are the fitting coefficients. t It is a time variable.

5. A satellite signal tracking device, characterized in that, The device is used in a ground terminal, and the device includes: The velocity acquisition module is used to acquire the linear velocity of the target satellite and, based on the linear velocity and the angle between the target satellite and the ground terminal at the current moment, calculate the radial velocity of the target satellite relative to the ground terminal at the current moment. A predictor building module is used to obtain a pre-built Doppler frequency shift expression, build a drift trend estimator based on the Doppler frequency shift expression, and build a frequency shift predictor based on the drift trend estimator. A frequency shift prediction module is used to calculate the predicted frequency shift for the next moment based on the radial velocity and the frequency shift predictor. The signal tracking module is used to scan the target satellite for signals based on the predicted frequency shift and a pre-set frequency scanning window; The signal parameter acquisition module is used to acquire the signal parameters of the received signal; the signal parameters include at least the carrier-to-noise ratio, the phase change rate, and the cross-correlation peak value. The comprehensive error factor calculation module is used to calculate the comprehensive error factor of the received signal based on the signal parameters. The model fitting module is used to count the frequency shift values ​​of the most recent preset number of times when the comprehensive error factor is greater than or equal to a preset threshold, calculate the frequency shift change value between every two adjacent times based on each frequency shift value, and fit the frequency shift trend prediction model. The rescan module is used to calculate the center value of the frequency scan window based on the frequency shift change value and the frequency shift trend prediction model, and to scan the target satellite again based on the center value of the frequency scan window and the frequency scan window. The comprehensive error factor calculation module is specifically used for: Calculate the comprehensive error factor using the following formula. : in, , , All of these are pre-set weighting coefficients; Carrier-to-noise ratio, For reference carrier-to-noise ratio, The phase change rate, For the peak value of cross-correlation, This represents the ideal peak value.

6. The apparatus according to claim 5, characterized in that, The predictor construction module is specifically used for: The drift trend estimator is obtained by performing a first-order difference on the Doppler frequency shift expression; A frequency shift predictor is constructed based on the Doppler frequency shift expression and the drift trend estimator.

7. A computer device, characterized in that, include: The memory and the processor are coupled; The memory is used to store one or more computer instructions; The processor is used to execute one or more computer instructions to implement the satellite signal tracking method as described in any one of claims 1 to 4.

8. A readable storage medium having one or more computer instructions stored thereon, characterized in that, The instruction is executed by the processor to implement the satellite signal tracking method as described in any one of claims 1 to 4.

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