Multi-parameter joint tracking method and device for high-dynamic TT&C data transmission signal

Abstract

The application provides a high-dynamic TT&C data transmission signal multi-parameter joint tracking method and device, and belongs to the technical field of signal tracking. The method comprises the following steps: determining an optimal sampling time based on sampling time correction amounts corresponding to a plurality of continuous tracking periods, sampling and aligning an initial tracking input signal corresponding to a current tracking period to obtain a first tracking input signal; correcting the first tracking input signal based on a carrier frequency estimation initial value, a reference carrier frequency and a phase compensation signal to obtain a second tracking input signal; determining a phase compensation signal of a next tracking period based on the second tracking input signal; determining a current frame frequency observation value based on a current frame total phase offset and a current frame duration; and determining a carrier frequency estimation initial value of a next frame through inter-frame recursive filtering based on the current frame frequency observation value. The application can improve the tracking precision and real-time performance of high-dynamic TT&C data transmission signals.

Description

Technical Field

[0001] This application belongs to the field of signal tracking technology, and more specifically, relates to a method and device for multi-parameter joint tracking of high dynamic measurement and control data transmission signals. Background Technology

[0002] The onboard telemetry, tracking, and command (TT&C) transponder is a crucial component of the satellite TT&C and data transmission system, used to acquire, track, and demodulate signals from the satellite-to-ground link. During data transmission signal tracking, it is necessary to estimate and correct sampling time parameters, carrier frequency parameters, and carrier phase parameters in real time. The tracking accuracy of these three parameters directly affects demodulation performance and the system's bit error rate.

[0003] When a satellite is in orbit, factors such as relative motion between the satellite and the ground, Doppler variations, local oscillator instability, and channel noise cause the parameters of the transmitted data signal to be in a state of continuous change. The sampling time, carrier frequency, and carrier phase may drift, experience random disturbances, or even abrupt changes. If the tracking loop cannot update these parameters stably and in a timely manner, it can easily lead to the sampling point deviating from the optimal sampling position, the accumulation of carrier phase errors, and frequency tracking lag, thereby reducing the reliability of demodulation.

[0004] In existing telemetry and control data transmission receiving schemes, data transmission signal tracking typically employs methods such as sampling time adjustment based on correlation peak values, carrier phase tracking based on decision guidance, and frequency updates based on phase difference. These schemes usually design sampling time tracking, carrier phase tracking, and carrier frequency tracking separately, with each parameter loop being updated independently and iteratively.

[0005] However, in scenarios with high dynamics, low signal-to-noise ratio, or rapidly changing parameters, independent loops are prone to insufficient parameter adaptation. For example, sampling timing errors can affect symbol decision and phase error extraction, carrier frequency residuals can cause continuous phase rotation, and carrier phase errors can reduce the reliability of correlation detection and demodulation decisions. Therefore, if various parameters rely solely on their respective loops for independent updates, it can easily lead to an imbalance between tracking accuracy and noise suppression capability, parameter update lag, and decreased tracking stability, making it difficult to meet the continuous and reliable demodulation requirements of spaceborne telemetry and control transponders under complex operating conditions. Summary of the Invention

[0006] The purpose of this application is to provide a multi-parameter joint tracking method and device for high dynamic measurement and control data transmission signals, so as to solve the problems of imbalance between tracking accuracy and noise suppression capability and parameter update lag, and improve the tracking accuracy and real-time performance of high dynamic measurement and control data transmission signals.

[0007] A first aspect of this application provides a method for multi-parameter joint tracking of high dynamic measurement and control data transmission signals, comprising: Based on the preset sliding window length, select multiple consecutive tracking periods, determine the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, and sample and align the initial tracking input signal corresponding to the current tracking period based on the optimal sampling time to obtain the first tracking input signal; The process involves: acquiring the initial carrier frequency estimate and reference carrier frequency of the current frame; determining the Doppler frequency estimate of the current frame based on these values; compensating the first tracking input signal based on the Doppler frequency estimate to obtain a frequency offset correction signal; acquiring the phase compensation signal for the current tracking period; multiplying the phase compensation signal with the frequency offset correction signal to obtain the second tracking input signal; performing symbol decision based on the second tracking input signal to obtain a reference symbol; extracting the carrier phase error based on the second tracking input signal and the reference symbol; filtering the carrier phase error using a second-order loop filter to obtain the target carrier phase estimate; and generating the phase compensation signal for the next tracking period based on the target carrier phase estimate. Based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame, the total phase offset of the current frame is obtained. Based on the total phase offset of the current frame and the duration of the current frame, the frequency residual estimate of the current frame is obtained. Based on the frequency residual estimate of the current frame and the initial carrier frequency estimate of the current frame, the frequency observation value of the current frame is obtained. The current frame includes multiple consecutive tracking periods. Based on the frequency observation value of the current frame, the initial carrier frequency estimate of the next frame is determined by inter-frame recursive filtering.

[0008] A second aspect of this application provides a high-dynamic measurement and control data transmission signal multi-parameter joint tracking device, comprising: The sampling time tracking module is used to select multiple consecutive tracking periods based on a preset sliding window length, determine the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, and sample and align the initial tracking input signal corresponding to the current tracking period based on the optimal sampling time to obtain the first tracking input signal. The carrier phase tracking module is used to acquire the initial carrier frequency estimate and reference carrier frequency of the current frame; determine the Doppler frequency estimate of the current frame based on the initial carrier frequency estimate and reference carrier frequency; compensate the first tracking input signal based on the Doppler frequency estimate of the current frame to obtain a frequency offset correction signal; acquire the phase compensation signal of the current tracking period; multiply the phase compensation signal with the frequency offset correction signal to obtain the second tracking input signal; perform symbol decision based on the second tracking input signal to obtain a reference symbol; extract the carrier phase error based on the second tracking input signal and the reference symbol; filter the carrier phase error through a second-order loop filter to obtain the target carrier phase estimate; and generate the phase compensation signal for the next tracking period based on the target carrier phase estimate. The carrier frequency tracking module is used to obtain the total phase offset of the current frame based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame; to obtain the frequency residual estimate of the current frame based on the total phase offset and the duration of the current frame; to obtain the frequency observation value of the current frame based on the frequency residual estimate and the initial carrier frequency estimate of the current frame, wherein the current frame includes multiple consecutive tracking periods; and to determine the initial carrier frequency estimate of the next frame through inter-frame recursive filtering based on the frequency observation value of the current frame.

[0009] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above-described high dynamic measurement and control data transmission signal multi-parameter joint tracking method.

[0010] In a fourth aspect of this application, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the above-described high dynamic measurement and control data transmission signal multi-parameter joint tracking method.

[0011] The beneficial effects of the high dynamic measurement and control data transmission signal multi-parameter joint tracking method and device provided in this application are as follows: This application embodiment determines the optimal sampling time by jointly processing the sampling time correction amount of multiple consecutive tracking cycles, and performs sampling alignment on the initial tracking input signal corresponding to the current tracking cycle based on the optimal sampling time. This avoids frequent switching of sampling points caused by abnormal decisions in a single cycle, thereby suppressing the accumulation of sampling deviation caused by inconsistent sampling clocks and improving the stability and reliability of sampling time tracking.

[0012] Meanwhile, in this embodiment, the Doppler frequency estimate of the current frame is determined based on the initial carrier frequency estimate and the reference carrier frequency, and the first tracking input signal is compensated based on the Doppler frequency estimate to obtain a frequency offset correction signal; then the frequency offset correction signal is corrected by the phase compensation signal to obtain a second tracking input signal; and finally, the carrier phase error is extracted based on the second tracking input signal and the target carrier phase estimate is determined, which can reduce the impact of Doppler frequency shift and carrier phase error on demodulation performance and improve the stability and accuracy of carrier phase tracking.

[0013] Regarding the carrier frequency, this embodiment obtains the total phase offset of the current frame based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame, and obtains the frequency residual estimate of the current frame based on the total phase offset of the current frame, and further obtains the frequency observation value of the current frame; by determining the initial value of the carrier frequency estimate of the next frame through inter-frame recursive filtering, it can adapt to the frequency drift caused by the Doppler effect and local oscillator instability, and take into account both tracking response speed and noise suppression capability.

[0014] This application incorporates three types of parameters—sampling time, carrier phase, and carrier frequency—into a joint tracking mechanism. This ensures that the sampling time alignment provides reliable input for carrier phase tracking, the carrier phase tracking results provide observational basis for frame-level carrier frequency updates, and the frame-level carrier frequency update results provide initial values ​​for Doppler frequency compensation in the next frame. This improves the continuity and coordination of the multi-parameter tracking process. Even in high-dynamic, high-interference, and rapidly changing parameter scenarios, this application's embodiment can maintain stable tracking, reduce the bit error rate, and enhance the continuous operation capability and communication reliability of the satellite telemetry, tracking, and command (TT&C) data transmission system. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating a multi-parameter joint tracking method for high dynamic measurement and control data transmission signals provided in an embodiment of this application; Figure 2 This is a structural block diagram of a high dynamic measurement and control data transmission signal multi-parameter joint tracking device provided in an embodiment of this application; Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0019] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a high-dynamic-range telemetry and control data transmission signal multi-parameter joint tracking method according to an embodiment of this application. The method can be executed by an electronic device and includes: S101: Select multiple consecutive tracking cycles based on a preset sliding window length, determine the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking cycles, and sample and align the initial tracking input signal corresponding to the current tracking cycle based on the optimal sampling time to obtain the first tracking input signal.

[0020] In this embodiment, the sampling time correction for each tracking cycle is obtained as follows: For each tracking cycle, a set of candidate sampling points corresponding to that tracking cycle is determined, the set of candidate sampling points includes multiple candidate sampling points; for each candidate sampling point, a corresponding correlation window is constructed based on that candidate sampling point; according to the correlation window, a corresponding signal segment is extracted from the initial tracking input signal corresponding to that tracking cycle, and the extracted signal segment is used as the parallel candidate signal corresponding to that candidate sampling point; the correlation results between each parallel candidate signal and the local matching waveform are calculated, and the sampling time correction for that tracking cycle is determined based on the correlation results.

[0021] In this embodiment, for each tracking cycle, if the tracking cycle is the first tracking cycle, an initial tracking input signal is constructed based on the initial sampling time value output during the acquisition phase; if the tracking cycle is not the first tracking cycle, the historical sampling time estimate of the previous tracking cycle is obtained, and the sampling time error is determined based on the historical sampling time estimate, and the initial tracking input signal is constructed based on the sampling time error; wherein, the previous tracking cycle is the tracking cycle preceding and adjacent to the current tracking cycle. In this embodiment, the electronic device can refer to a telemetry and control transponder. The sliding window length refers to the number of consecutive tracking cycles participating in the joint update of the sampling time, for example, 16 tracking cycles. The sliding window length is a preset parameter used to balance the smoothness of the sampling time update with the response speed. The tracking cycle refers to the signal processing cycle corresponding to one baseband symbol; the duration of the tracking cycle can be determined by the system symbol rate, for example, 2 microseconds. Each tracking cycle can complete one sampling time correction and carrier phase parameter update.

[0022] In this embodiment, the sampling time correction refers to the value that needs to be adjusted in the sampling time within a single tracking cycle. For example, it can include -1, +1, and 0, where -1 represents shifting one sampling point to the left, +1 represents shifting one sampling point to the right, and 0 represents no adjustment is needed. The optimal sampling time refers to the target sampling time point determined after joint processing of multiple consecutive tracking cycles, corresponding to the optimal sampling position in the current tracking cycle. The sampling time of the first tracking cycle can be taken as the initial value of the sampling time output during the capture phase.

[0023] In this embodiment, the initial tracking input signal refers to the complex baseband signal to be processed before entering the current tracking cycle. This signal can be the baseband signal output during the acquisition phase and after coarse synchronization. The first tracking input signal refers to the baseband signal obtained by sampling and aligning the initial tracking input signal corresponding to the current tracking cycle based on the optimal sampling time, and is used for subsequent carrier phase tracking processing. The candidate sampling point set refers to the set of multiple sampling positions to be evaluated within the current tracking cycle. The correlation window refers to the sampling point window determined based on the candidate sampling points and used to extract signal segments from the initial tracking input signal. The parallel candidate signal refers to multiple candidate signals extracted from the initial tracking input signal according to different correlation windows. Each parallel candidate signal corresponds to one candidate sampling point. The local matching waveform refers to the symbol-shaped waveform generated by the telemetry and control transponder according to the known modulation format and symbol information, which is consistent with the transmitter. For example, it may include raised cosine shaped waveform, Nyquist shaped waveform, etc. The correlation result refers to the output result obtained by performing conjugate cross-correlation between the parallel candidate signal and the local matching waveform. It is used to characterize the degree of matching between the signal at the corresponding candidate sampling point and the local matching waveform. For example, it can include values ​​such as 0.8, 1.2 and 1.5.

[0024] In this embodiment, the sampling time error refers to the difference between the reference sampling time and the estimated historical sampling time from the previous tracking cycle. The reference sampling time refers to the nominal optimal sampling position determined by the system symbol rate and oversampling rate, used to measure the deviation of the actual sampling time from the preset sampling position. The estimated historical sampling time refers to the optimal sampling time value output in the previous tracking cycle.

[0025] For example, this embodiment can perform signal tracking initialization. For instance, the sliding window length is set to 8 tracking cycles, the number of candidate sampling points is 4, the delay step is 1 sampling cycle, and the continuous same-direction counting threshold is 5. This embodiment can obtain the current satellite operating mode; initially, the satellite is in a steady-state orbit operating mode by default. The delay step refers to the time interval between adjacent candidate sampling points. The sliding window set is initialized to empty, the maximum continuous same-direction count is initialized to 0, and the estimated historical sampling time value of the previous tracking cycle is initialized to the initial sampling time value output during the acquisition phase.

[0026] This embodiment can process the signal for each tracking cycle sequentially. Specifically, for the first tracking cycle, this embodiment can construct the initial tracking input signal using the initial sampling time value output from the acquisition phase. The initial tracking input signal for the first tracking cycle... Represented as: ; in, The amplitude coefficient of the received signal. The imaginary unit, The initial value at the sampling time output during the capture phase. For sampling point index, To track the residual frequency term in the input signal, S is the sampling period of the transponder. () represents the equivalent baseband symbol shaped waveform. This is the noise term corresponding to the first tracking cycle. The relevant length. In this embodiment, the sliding window refers to the number of consecutive tracking periods participating in the joint update, and the relevant length. This indicates the number of sampling points involved in the relevant calculations within a single tracking period.

[0027] For each subsequent tracking cycle, this embodiment can obtain the estimated historical sampling time value of the output from the previous tracking cycle, and determine the reference sampling time based on the system symbol rate and sampling period. The difference between the reference sampling time and the estimated historical sampling time value is used as the sampling time error. This embodiment can substitute the sampling time error into the time variable of the equivalent baseband symbol shaping waveform, and combine it with the received signal amplitude, residual frequency term, and noise term to construct the initial tracking input signal for the current tracking cycle. For example, the first... t Initial tracking input signal for each tracking cycle The construction formula is: ; in, t For tracking the index of the period, For the first t The sampling time error corresponding to each tracking cycle For the first t The noise term corresponding to each tracking cycle. The received signal refers to the complex baseband digital signal obtained after the data transmission signal transmitted by the satellite has been transmitted through the space channel, down-converted by the onboard transponder's radio frequency front-end, and converted from analog to digital.

[0028] This embodiment can determine the set of candidate sampling points based on the initial tracking input signal. Specifically, it can be based on a preset number of candidate sampling points. and delay step Determine the first t The set of candidate sampling points corresponding to each tracking period: ; in, For the first Within the tracking period, the first 1 candidate sampling point The two adjacent candidate sampling points satisfy the following condition: ,in This is the delay step size.

[0029] For each candidate sampling point in the candidate sampling point set, this embodiment can construct a corresponding correlation window based on that candidate sampling point. Within the tracking period, the first The correlation window corresponding to each candidate sampling point can be represented as: ; in, For the first The relevant window corresponding to each candidate sampling point For the relevant length.

[0030] According to the relevant window, this embodiment can be viewed from the first... The corresponding signal segment is extracted from the initial tracking input signal corresponding to each tracking cycle, and the extracted signal segment is used as the parallel candidate signal corresponding to the candidate sampling point. Within the tracking period, the first The parallel candidate signal can be represented as: ; in, For the first Within the tracking period, the first Parallel candidate signals.

[0031] This embodiment can calculate the correlation result between each parallel candidate signal and the local matched waveform. Specifically, this embodiment can first obtain demodulation information, which comes from the pilot symbols decoded during the signal acquisition stage or the reliable symbols obtained through symbol decision in the previous tracking cycle. This embodiment can map the demodulation information to baseband symbols according to the modulation method, perform raised cosine shaping filtering on the baseband symbols to obtain the baseband shaped waveform, and generate the local matched waveform based on the baseband shaped waveform. For example, the first... t The local matching waveform for each tracking cycle can be represented as: ; in, For the first Local matching waveform for each tracking cycle, For the first Each tracking cycle corresponds to a reconstruction from pilot symbols or reliable decision symbols, with a sampling period. The local baseband shaped waveform obtained by discrete sampling.

[0032] This embodiment can perform conjugate cross-correlation calculations between each parallel candidate signal and the local matched waveform to obtain the correlation results for each channel. t Within the tracking period, the first The correlation results for the parallel candidate signals are as follows: ; in, For the first t Within the tracking period, the first The correlation results corresponding to the parallel candidate signals. For the conjugate of the locally matched waveform, This represents the number of parallel candidate branches.

[0033] This embodiment can The path correlation results are fed into the maximum detector, which selects the candidate sampling point corresponding to the branch with the largest amplitude as the best candidate sampling point. If the best sampling point is the second one, the sampling time correction is not required; if the best sampling point is the first one, the sampling time correction is shifted to the left by 1 sampling point; if the best sampling point is the third one, the sampling time correction is shifted to the right by 1 sampling point.

[0034] In this embodiment, determining the optimal sampling time based on the sampling time correction amount corresponding to each of multiple consecutive tracking cycles includes: determining the adjustment direction corresponding to each sampling time correction amount, and determining the maximum consecutive same-direction count based on each adjustment direction; Obtain the continuous same-direction count threshold. If the maximum continuous same-direction count is greater than the continuous same-direction count threshold, then the sampling time update mode is determined to be the fast update mode. If the maximum consecutive same-direction count is not greater than the consecutive same-direction count threshold, then the sampling time update mode is determined to be the variable weight smooth update mode. The optimal sampling time is determined based on the sampling time correction amount corresponding to each of multiple consecutive tracking cycles, according to the sampling time update mode.

[0035] In this embodiment, the optimal sampling time is determined according to the sampling time update mode based on the sampling time correction amount corresponding to each of multiple consecutive tracking periods, including: If the sampling time update mode is fast update mode, then the nearest time is selected from multiple consecutive tracking periods. a Each tracking cycle, based on a The target correction amount is calculated based on the sampling time correction amount corresponding to each tracking period; the initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the initial sampling time is the estimated value of the historical sampling time output by the previous tracking period before the current tracking period is updated. If the sampling time update mode is the variable weight smooth update mode, then the current satellite operation mode is obtained, and weights are assigned to the correction amount of each sampling time according to the current satellite operation mode. The correction amount of each sampling time is weighted and summed based on the assigned weights to obtain the target correction amount. The initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time. The current satellite operation mode is the steady orbit operation mode, the orbit maintenance mode, or the rapid orbit change mode.

[0036] In this embodiment, weights are assigned to the sampling time correction amounts corresponding to each of the current satellite operation modes for multiple consecutive tracking cycles, including: If the current satellite operation mode is a steady orbit operation mode, the corresponding weight is determined based on the tracking period to which the correction amount belongs at each sampling time. The weight of the correction amount at each sampling time decreases exponentially as time goes by. If the current satellite operation mode is orbit maintenance mode, then the correction amount at each sampling time is assigned the same weight; If the current satellite operation mode is rapid orbit change mode, then the sampling time correction amount corresponding to the first period group and the sampling time correction amount corresponding to the second period group are assigned weights respectively, and the weight of the sampling time correction amount corresponding to the first period group is greater than the weight of the sampling time correction amount corresponding to the second period group. The first period group consists of the most recent period among multiple consecutive tracking periods. L The first tracking period is one tracking period, and the second tracking period is the tracking period other than the first tracking period in a series of tracking periods.

[0037] In this embodiment, the adjustment direction refers to the adjustment direction represented by the sampling time correction amount, which may include leftward shift, rightward shift, or unchanged direction. The adjustment direction is used to determine the number of consecutive same-direction adjustments. The maximum consecutive same-direction count refers to the maximum number of consecutive sampling time correction amounts with the same adjustment direction appearing within the sliding window. The maximum consecutive same-direction count is used to determine the severity of sampling time drift. The consecutive same-direction count threshold refers to the critical value of the number of consecutive same-direction adjustments that triggers the fast update mode, for example, it can be 5 times. The fast update mode refers to the update mode in which the sampling time parameters quickly follow the drift, used to cope with large-scale sampling time offsets. The variable-weight smooth update mode refers to the update mode in which the sampling time correction amount is weighted and averaged according to different weights, used to suppress noise interference. The satellite operation mode refers to the current orbital operation status of the satellite. The satellite operation mode is obtained from the onboard attitude control system. The onboard attitude control system is the core subsystem of the satellite, used to sense and control the satellite's spatial attitude and orbital motion status, and can monitor the satellite's current operation mode information in real time. The steady-state orbital operation mode refers to the state in which the satellite operates stably in a predetermined orbit, at which time the sampling time drift is relatively slow. The orbit maintenance mode refers to the satellite adjusting its orbit to maintain its predetermined orbit, in which case the sampling time drift rate is moderate. The rapid orbit change mode refers to the satellite performing a large orbital transfer, in which case the sampling time drift rate is relatively fast. The weight refers to the proportion of the sampling time correction amount in the joint calculation for different tracking periods, and may include, for example, 0.5, 0.3, and 0.2.

[0038] For example, this embodiment can maintain a sliding window set and count the maximum consecutive same-direction count. Specifically, this embodiment can add the sampling time correction amount of the current tracking period to the sliding window set. If the length of the sliding window set exceeds 8, the earliest added sampling time correction amount is removed. This embodiment can traverse the sliding window set, count the number of times the sampling time correction amount in the same direction appears consecutively, and record the maximum value as the maximum consecutive same-direction count.

[0039] This embodiment determines the sampling time update mode based on the relationship between the maximum consecutive same-direction count and the consecutive same-direction count threshold. If the maximum consecutive same-direction count is greater than 5, the sampling time update mode is determined to be a fast update mode. If the maximum consecutive same-direction count is not greater than 5, the sampling time update mode is determined to be a variable-weight smooth update mode.

[0040] If a fast update mode is used, this embodiment selects the two most recent tracking cycles from eight consecutive tracking cycles, averages the sampling time corrections of the two tracking cycles, and obtains the target correction. This embodiment also adds the historical sampling time estimate output from the previous tracking cycle before the current tracking cycle update to the target correction to obtain the optimal sampling time.

[0041] If a variable-weight smooth update mode is adopted, this embodiment obtains the current satellite operating mode from the onboard attitude control system. If the current satellite operating mode is a steady-state orbit operating mode, the weight of each sampling time correction decreases exponentially over time. The weight of the latest 8th tracking cycle is 0.3, the weight of the 7th tracking cycle is 0.2, the weight of the 6th tracking cycle is 0.15, the weight of the 5th tracking cycle is 0.12, the weight of the 4th tracking cycle is 0.1, the weight of the 3rd tracking cycle is 0.07, the weight of the 2nd tracking cycle is 0.04, and the weight of the 1st tracking cycle is 0.02. If the current satellite operating mode is an orbit maintenance mode, the sampling time corrections for the 8 tracking cycles are assigned the same weight, each weight being 0.125. If the current satellite operating mode is a rapid orbit change mode, the sampling time corrections corresponding to the two most recent tracking cycles are assigned weights of 0.4 and 0.3, and the sampling time corrections corresponding to the remaining 6 tracking cycles are assigned the same weight of 0.05.

[0042] This embodiment determines the optimal sampling time based on the sampling time correction amounts corresponding to each of multiple consecutive tracking periods. Specifically, this embodiment multiplies each sampling time correction amount by its corresponding weight and then sums them to obtain the smoothing update amount. This embodiment also adds the smoothing update amount to the historical sampling time estimate of the previous tracking period to obtain the optimal sampling time.

[0043] Based on the optimal sampling time, this embodiment can sample and align the initial tracking input signal corresponding to the current tracking period to obtain the first tracking input signal. The first tracking input signal It can be represented as: ; in, It is the first Within the tracking period, the first Effective baseband symbol components at each sampling time. This is the actual equivalent phase perturbation. For the first The equivalent noise term at each sampling time point.

[0044] This embodiment determines the optimal sampling time by using a sliding window combined with multi-cycle sampling time correction, effectively suppressing the sampling point jump problem caused by single-cycle abnormal decisions and weakening the impact of single-cycle abnormal decisions on the sampling time update results. This avoids frequent jumps in sampling time parameters due to outliers within adjacent tracking cycles, thereby improving the stability and robustness of sampling time parameter tracking. This embodiment introduces maximum continuous in-direction counting to achieve adaptive switching of the sampling time update mode, balancing tracking response speed in large drift scenarios with tracking stability in low-noise scenarios. This embodiment designs differentiated weight allocation strategies based on different satellite operating modes, adapting to the sampling time drift characteristics under different orbital states, further improving the robustness and accuracy of sampling time tracking, and providing a reliable signal foundation for subsequent carrier parameter tracking.

[0045] S102: Obtain the initial carrier frequency estimate and reference carrier frequency of the current frame; determine the Doppler frequency estimate of the current frame based on the initial carrier frequency estimate and reference carrier frequency; compensate the first tracking input signal based on the Doppler frequency estimate of the current frame to obtain the frequency offset correction signal; obtain the phase compensation signal of the current tracking period; multiply the phase compensation signal with the frequency offset correction signal to obtain the second tracking input signal; perform symbol decision based on the second tracking input signal to obtain the reference symbol; extract the carrier phase error based on the second tracking input signal and the reference symbol; filter the carrier phase error through a second-order loop filter to obtain the target carrier phase estimate; generate the phase compensation signal for the next tracking period based on the target carrier phase estimate.

[0046] In this embodiment, the initial carrier frequency estimate of the current frame refers to the carrier frequency estimate used when processing begins for the current frame, which can be determined from the carrier frequency estimate obtained from the previous frame through inter-frame recursive filtering. The reference carrier frequency refers to the frequency reference value used to calculate the Doppler frequency estimate, which can be the system-preset nominal center frequency of the carrier, the local carrier frequency, or the initial carrier frequency value output during the acquisition phase. The Doppler frequency estimate of the current frame is used to characterize the frequency offset of the initial carrier frequency estimate of the current frame relative to the reference carrier frequency.

[0047] Specifically, let the current frame be the th frame. Frame, number The initial value of the frame carrier frequency estimation is The reference carrier frequency is The Doppler frequency estimate of the current frame is... It can be represented as: ; in, For the first The Doppler frequency estimate for the frame. Since the carrier frequency is updated frame by frame, therefore, in the [frame number]... The Doppler frequency estimate can remain consistent across multiple tracking cycles within a frame.

[0048] In this embodiment, the Doppler frequency estimate of the current frame is determined based on the initial carrier frequency estimate and the reference carrier frequency. Based on the Doppler frequency estimate of the current frame, the first tracking input signal is compensated to obtain a frequency offset correction signal. This includes: determining the Doppler frequency estimate of the current frame based on the difference between the initial carrier frequency estimate and the reference carrier frequency; determining the frequency offset compensation signal based on the Doppler frequency estimate of the current frame; and compensating the first tracking input signal based on the frequency offset compensation signal to obtain the frequency offset correction signal.

[0049] In this embodiment, the first tracking input signal refers to the baseband signal obtained by sampling and aligning the initial tracking input signal corresponding to the current tracking period based on the optimal sampling time. The frequency offset correction signal refers to the intermediate signal obtained after Doppler frequency compensation of the first tracking input signal. Since the Doppler frequency offset accumulates over the sampling time to form a phase rotation, this embodiment can determine the frequency offset compensation signal based on the Doppler frequency estimate of the current frame and use this frequency offset compensation signal to compensate the first tracking input signal.

[0050] Specifically, in the first Intra-frame In the tracking period, the first The frequency offset compensation signal at each sampling point can be expressed as: ; in, For the first Intra-frame The first tracking period Frequency offset compensation signal at each sampling point The sampling period is For sampling point index, The imaginary unit is used. The frequency offset correction signal is obtained by compensating the first tracking input signal based on the frequency offset compensation signal. ; in, For the first The first tracking period Frequency offset correction signal at each sampling point For the first The first tracking period The first tracking input signal at each sampling point.

[0051] In this embodiment, the phase compensation signal refers to a complex exponential signal used to compensate for the carrier phase error in the current tracking period. The phase compensation signal can be generated by a numerically controlled oscillator based on the target carrier phase estimate output in the previous tracking period. Specifically, the first... The phase compensation signal for each tracking cycle can be expressed as: ; in, For the first The first tracking period Phase compensation signal at each sampling point For the first The target carrier phase estimate output for each tracking cycle.

[0052] Multiplying the phase compensation signal by the frequency offset correction signal yields the second tracking input signal: ; in, For the first The first tracking period The second tracking input signal at each sampling point is used for subsequent symbol decision and carrier phase error extraction.

[0053] In this embodiment, symbol decision is performed based on the second tracking input signal to obtain a reference symbol. Based on the second tracking input signal and the reference symbol, the carrier phase error is extracted, including: performing symbol decision by a decision unit based on the second tracking input signal to obtain a reference symbol; and extracting the phase error by a phase detector based on the second tracking input signal and the reference symbol to obtain the carrier phase error.

[0054] In this embodiment, a symbol decision is performed based on the second tracking input signal to obtain a reference symbol. Specifically, the reference symbol can be represented as: ; in, The symbolic decision operation of the decision controller. For the first The first tracking period The reference symbol is obtained from the decision of each sampling point. For example, when using binary phase shift keying modulation, the decision maker can make a decision based on the real part of the second tracking input signal; if the real part of the second tracking input signal is greater than 0, it is decided as a positive symbol; if the real part of the second tracking input signal is less than 0, it is decided as a negative symbol.

[0055] This embodiment can extract the carrier phase error using a phase detector based on the second tracking input signal and the reference symbol. Specifically, the carrier phase error can be expressed as: ; in, For the first The carrier phase error corresponding to each tracking period This indicates taking the imaginary part of a complex number. To take the real part of a complex number, For the first The first tracking period The conjugate of the reference symbols at each sampling point, The correlation length is given. Through the above processing, the carrier phase error of the second tracking input signal relative to the reference symbol can be extracted.

[0056] In this embodiment, the carrier phase error is filtered by a second-order loop filter to obtain the target carrier phase estimate. Specifically, the second-order loop filter can adopt a proportional-integral (PI) structure. Let... For the term of integration accumulation, we have: ; ; in, For the first The target carrier phase estimate output in each tracking cycle For the first The target carrier phase estimate output in each tracking cycle and These are the coefficients of the second-order loop filter.

[0057] The target carrier phase estimate output in the current tracking cycle can be used as the phase control input of a numerically controlled oscillator to generate the phase compensation signal for the next tracking cycle. Specifically, the next tracking cycle (the...) t Phase compensation signal (+1 tracking period) It can be represented as: ; Thus, the carrier phase forms a closed-loop recursion between adjacent tracking cycles. That is, the target carrier phase estimate output from the previous tracking cycle is used to generate the phase compensation signal for the current tracking cycle, and the target carrier phase estimate output from the current tracking cycle is used to generate the phase compensation signal for the next tracking cycle.

[0058] This embodiment compensates for the frequency offset of the first tracking input signal using the Doppler frequency estimate of the current frame, reducing the phase rotation effect caused by Doppler frequency shift. Then, it compensates for the phase offset correction signal using the phase compensation signal, further reducing the impact of the remaining carrier phase error on symbol decision and phase error extraction. Through decision-guided phase error extraction and second-order loop filtering, this embodiment smooths out noise-induced phase jitter, improving the stability and accuracy of carrier phase tracking, and providing reliable input for subsequent frame-level carrier frequency updates and data demodulation.

[0059] S103: Based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame, obtain the total phase offset of the current frame; based on the total phase offset of the current frame and the duration of the current frame, obtain the frequency residual estimate of the current frame; based on the frequency residual estimate of the current frame and the initial carrier frequency estimate of the current frame, obtain the frequency observation value of the current frame, where the current frame includes multiple consecutive tracking periods; based on the frequency observation value of the current frame, determine the initial carrier frequency estimate value of the next frame through inter-frame recursive filtering.

[0060] In this embodiment, the total phase offset of the current frame refers to the total change in carrier phase within the current frame, which can be, for example, 0.1 radians. The total phase offset of the current frame can be obtained by subtracting the target carrier phase estimate corresponding to the start tracking period of the current frame from the target carrier phase estimate corresponding to the end tracking period of the current frame. The frequency residual estimate of the current frame refers to the average frequency deviation calculated based on the total phase offset of the current frame, which can be, for example, 10 Hz. The frequency observation of the current frame refers to the carrier frequency measurement obtained in the current frame, used for inter-frame frequency recursive filtering. The initial carrier frequency estimate of the current frame refers to the carrier frequency estimate used when processing the current frame begins, which can be determined by the inter-frame recursive filtering result of the previous frame. The initial carrier frequency estimate of the next frame refers to the initial frequency value obtained after inter-frame recursive filtering using the frequency observation of the current frame, used for Doppler frequency estimation and frequency offset compensation in the next frame.

[0061] For example, in this embodiment, a single frame can be set to contain 256 tracking cycles, the duration of a single frame can be 256 microseconds, the process noise covariance of the inter-frame recursive filtering can be initialized to 0.01, the measurement noise covariance can be 0.1, the initial value of the carrier frequency estimation of the first frame can be initialized to the initial value of the carrier frequency output in the acquisition stage, and the state vector and error covariance matrix of the inter-frame recursive filtering can be initialized.

[0062] This embodiment can obtain the target carrier phase estimate at the start tracking period of the current frame and at the end tracking period of the current frame. Specifically, after each tracking period in the current frame completes sampling time tracking and carrier phase tracking in sequence, this embodiment can subtract the target carrier phase estimate corresponding to the start tracking period of the current frame from the target carrier phase estimate corresponding to the end tracking period of the current frame to obtain the total phase offset of the current frame. Let the current frame be the [number]th [frame name]. If the frame is a given frame, then the total phase offset of the current frame can be expressed as: ; in, For the first Total phase offset of the frame. For the first The target carrier phase estimate corresponding to the frame start tracking period. For the first The target carrier phase estimate corresponding to the frame termination tracking period.

[0063] This embodiment can obtain the frequency residual estimate of the current frame based on the total phase offset and the duration of the current frame. Specifically, the frequency residual estimate of the current frame can be expressed as: ; in, For the first Frame frequency residual estimate, For the first The duration of a frame.

[0064] Furthermore, in this embodiment, the observed frequency value of the current frame can be obtained based on the estimated residual value of the current frame frequency and the initial estimated carrier frequency value of the current frame. Specifically, the observed frequency value of the current frame can be expressed as: ; in, For the first Initial value for frame carrier frequency estimation. For the first The frequency observation of the frame. The current frame frequency observation can be used as the measurement input for inter-frame recursive filtering to smoothly update the carrier frequency.

[0065] For example, this embodiment can employ Kalman filtering to implement inter-frame recursive filtering, achieving a better balance between rapidly following Doppler frequency changes and suppressing noise jitter. Specifically, this embodiment can construct a discrete state-space model that includes the carrier frequency and the rate of frequency change. Let the... The frequency state vector of the frame is: ; in, Indicates the first The carrier frequency state of the frame. Indicates the first The rate of change of frame frequency. The current frame frequency observation is used as the measurement. ; Since the observation matrix is ​​used to observe the carrier frequency component in the frequency state vector, the observation matrix can be represented as: ; Based on the above definition, the discrete state-space model can be expressed as: ; ; in, For process noise, To measure noise. State transition matrix. It can be represented as: ; in, For the first The duration of a frame, also known as the frame period.

[0066] The above state model shows that the carrier frequency state of the current frame is jointly determined by the frequency state of the previous frame and the rate of frequency change, and the frequency observation value of the current frame is... Used to observe the carrier frequency component in the current frame frequency state.

[0067] In processing the first When processing frame data, this embodiment can use the frequency state estimate from the previous frame. Calculate the predicted frequency state value for the current frame: ; in, For the first Frame frequency state prediction value. When =1, the initial state prediction value is given by prior information.

[0068] Then, the prediction error covariance matrix is ​​updated synchronously: ; in, For the prediction error covariance matrix, This is the error covariance matrix after correction for the previous frame. This is the process noise covariance matrix, used to characterize the intensity of random changes in frequency state between adjacent frames. When As the value of increases, the prediction stage allows for faster frequency drift, thereby improving the tracking capability.

[0069] This embodiment can calculate the Kalman gain based on the prediction error covariance and the measurement noise covariance: ; in, For the first Kalman gain of the frame To measure noise covariance, used to characterize the measured quantity The statistical strength of measurement error. Because... The current frame frequency observation is in scalar form, therefore The measurement noise variance can be degenerated into a scalar form. When As the Kalman gain increases, the Kalman gain decreases, making the update more dependent on the predicted value to suppress jitter introduced by observation noise; when When the frequency is reduced, the Kalman gain increases, allowing the update to follow the frequency drift more quickly.

[0070] After obtaining the Kalman gain, this embodiment can use the current frame frequency observation value to correct the frequency state prediction value, and obtain the frequency state update value of the current frame: ; in, The residual is used to measure the deviation between the observed and predicted frequency values ​​of the current frame frequency.

[0071] At the same time, update the corrected error covariance matrix: ; in, This is the corrected error covariance matrix. It is an identity matrix.

[0072] This embodiment can determine the initial carrier frequency estimate for the next frame based on the frequency state update value of the current frame. In one implementation, the carrier frequency component can be extracted from the frequency state update value of the current frame and used as the initial carrier frequency estimate for the next frame. ; in, For the first Initial value for carrier frequency estimation of the frame.

[0073] This embodiment calculates the frequency residual through frame-level phase differential to achieve carrier frequency observation; combined with inter-frame recursive filtering, it can smooth frequency jitter caused by noise, and take into account both the tracking response speed in high dynamic scenarios and the tracking stability in low noise scenarios, providing a reliable frequency reference for Doppler frequency compensation and carrier phase tracking in the next frame.

[0074] Corresponding to the high dynamic measurement and control data transmission signal multi-parameter joint tracking method in the above embodiment, Figure 2 This is a structural block diagram of a high-dynamic measurement and control data transmission signal multi-parameter joint tracking device provided in one embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2 The high dynamic measurement and control data transmission signal multi-parameter joint tracking device 20 includes: sampling time tracking module 21, carrier phase tracking module 22 and carrier frequency tracking module 23.

[0075] Among them, the sampling time tracking module 21 is used to select multiple consecutive tracking cycles based on a preset sliding window length, determine the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking cycles, and sample and align the initial tracking input signal corresponding to the current tracking cycle based on the optimal sampling time to obtain the first tracking input signal. The carrier phase tracking module 22 is used to acquire the initial carrier frequency estimate and reference carrier frequency of the current frame, determine the Doppler frequency estimate of the current frame based on the initial carrier frequency estimate and reference carrier frequency, compensate the first tracking input signal based on the Doppler frequency estimate of the current frame to obtain a frequency offset correction signal, acquire the phase compensation signal of the current tracking period, multiply the phase compensation signal and the frequency offset correction signal to obtain the second tracking input signal, perform symbol decision based on the second tracking input signal to obtain a reference symbol, extract the carrier phase error based on the second tracking input signal and the reference symbol, filter the carrier phase error through a second-order loop filter to obtain the target carrier phase estimate, and generate the phase compensation signal for the next tracking period based on the target carrier phase estimate. The carrier frequency tracking module 23 is used to obtain the total phase offset of the current frame based on the target carrier phase estimation values ​​corresponding to the start and end tracking periods of the current frame; to obtain the frequency residual estimation value of the current frame based on the total phase offset of the current frame and the duration of the current frame; to obtain the frequency observation value of the current frame based on the frequency residual estimation value of the current frame and the initial carrier frequency estimation value of the current frame, wherein the current frame includes multiple consecutive tracking periods; and to determine the initial carrier frequency estimation value of the next frame through inter-frame recursive filtering based on the frequency observation value of the current frame. In one embodiment of this application, the sampling time tracking module 21 is specifically used for: Determine the adjustment direction corresponding to the correction amount at each sampling time, and determine the maximum consecutive same-direction count based on each adjustment direction; obtain the consecutive same-direction count threshold; if the maximum consecutive same-direction count is greater than the consecutive same-direction count threshold, the sampling time update mode is determined to be the fast update mode; if the maximum consecutive same-direction count is not greater than the consecutive same-direction count threshold, the sampling time update mode is determined to be the variable weight smooth update mode; based on the sampling time correction amount corresponding to each of multiple consecutive tracking periods, determine the optimal sampling time according to the sampling time update mode.

[0076] In one embodiment of this application, the sampling time tracking module 21 is further used for: If the sampling time update mode is fast update mode, then the nearest time is selected from multiple consecutive tracking periods. a Each tracking cycle, based on a The target correction amount is calculated based on the sampling time correction amount corresponding to each tracking cycle; the initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the initial sampling time is the estimated value of the historical sampling time output by the previous tracking cycle before the current tracking cycle is updated; if the sampling time update mode is the variable weight smooth update mode, the current satellite operation mode is obtained, and weights are assigned to each sampling time correction amount according to the current satellite operation mode. The weighted sum of each sampling time correction amount is performed based on the assigned weights to obtain the target correction amount; the initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the current satellite operation mode is the steady orbit operation mode, the orbit maintenance mode, or the rapid orbit change mode.

[0077] In one embodiment of this application, the sampling time tracking module 21 is further used for: If the current satellite operation mode is a steady-state orbit operation mode, the corresponding weight is determined based on the tracking period to which each sampling time correction belongs, and the weight of each sampling time correction decreases exponentially over time. If the current satellite operation mode is an orbit maintenance mode, the same weight is assigned to each sampling time correction. If the current satellite operation mode is a rapid orbit change mode, weights are assigned to the sampling time corrections corresponding to the first period group and the second period group respectively, with the weight of the sampling time corrections corresponding to the first period group being greater than the weight of the sampling time corrections corresponding to the second period group. The first period group is the most recent one among multiple consecutive tracking periods. L The first tracking period is one tracking period, and the second tracking period is the tracking period other than the first tracking period in a series of tracking periods.

[0078] In one embodiment of this application, the carrier phase tracking module 22 is specifically used to: determine the Doppler frequency estimate of the current frame based on the difference between the initial carrier frequency estimate of the current frame and the reference carrier frequency; determine the frequency offset compensation signal based on the Doppler frequency estimate of the current frame; and compensate the first tracking input signal based on the frequency offset compensation signal to obtain the frequency offset correction signal.

[0079] In one embodiment of this application, the carrier phase tracking module 22 is further configured to: perform symbol determination by a decision unit based on the second tracking input signal to obtain a reference symbol; and extract the phase error by a phase detector based on the second tracking input signal and the reference symbol to obtain the carrier phase error.

[0080] In one embodiment of this application, the high dynamic measurement and control data transmission signal multi-parameter joint tracking device 20 further includes: a sampling time correction calculation module, used for: determining a set of candidate sampling points corresponding to each tracking cycle, the set of candidate sampling points including multiple candidate sampling points; constructing a corresponding correlation window for each candidate sampling point, starting from the candidate sampling point; extracting a corresponding signal segment from the initial tracking input signal corresponding to the tracking cycle according to the correlation window, and using the extracted signal segment as the parallel candidate signal corresponding to the candidate sampling point; calculating the correlation results between each parallel candidate signal and the local matching waveform, and determining the sampling time correction amount corresponding to the tracking cycle based on the correlation results.

[0081] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of each module / unit in the above-described device embodiments, for example... Figure 2 The functions of the sampling time tracking module 21, carrier phase tracking module 22, and carrier frequency tracking module 23 are shown.

[0082] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0083] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display, a speaker, etc.

[0084] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store signal tracking initialization information.

[0085] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation method described in the high dynamic measurement and control data transmission signal multi-parameter joint tracking method provided in the embodiments of this application, or they can execute the implementation method of the electronic device described in the embodiments of this application, which will not be repeated here.

[0086] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to implement these processes. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0087] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., provided on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0088] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0089] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces or units, or they may be electrical, mechanical, or other forms of connection.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0092] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0093] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for joint tracking of multiple parameters in high-dynamic measurement and control data transmission signals, characterized in that, include: Multiple consecutive tracking cycles are selected based on a preset sliding window length. The optimal sampling time is determined based on the sampling time correction amount corresponding to each of the multiple consecutive tracking cycles. The initial tracking input signal corresponding to the current tracking cycle is sampled and aligned based on the optimal sampling time to obtain the first tracking input signal. The initial carrier frequency estimate and reference carrier frequency of the current frame are obtained. Based on the initial carrier frequency estimate and reference carrier frequency of the current frame, the Doppler frequency estimate of the current frame is determined. Based on the Doppler frequency estimate of the current frame, the first tracking input signal is compensated to obtain the frequency offset correction signal. Obtain the phase compensation signal for the current tracking period, and multiply the phase compensation signal with the frequency offset correction signal to obtain the second tracking input signal; Symbol decision is performed based on the second tracking input signal to obtain a reference symbol. Based on the second tracking input signal and the reference symbol, the carrier phase error is extracted. The carrier phase error is filtered through a second-order loop filter to obtain a target carrier phase estimate. A phase compensation signal for the next tracking cycle is generated based on the target carrier phase estimate. Based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame, the total phase offset of the current frame is obtained. Based on the total phase offset of the current frame and the duration of the current frame, the frequency residual estimate of the current frame is obtained. Based on the frequency residual estimate of the current frame and the initial carrier frequency estimate of the current frame, the frequency observation value of the current frame is obtained. The current frame includes multiple consecutive tracking periods. Based on the frequency observation value of the current frame, the initial carrier frequency estimate value of the next frame is determined by inter-frame recursive filtering.

2. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 1, characterized in that, The determination of the optimal sampling time based on the sampling time correction amount corresponding to each of the consecutive tracking cycles includes: Determine the adjustment direction corresponding to the correction amount at each sampling time, and determine the maximum consecutive same-direction count based on each adjustment direction; Obtain the continuous same-direction count threshold. If the maximum continuous same-direction count is greater than the continuous same-direction count threshold, then the sampling time update mode is determined to be the fast update mode. If the maximum consecutive same-direction count is not greater than the consecutive same-direction count threshold, then the sampling time update mode is determined to be the variable weight smooth update mode. Based on the sampling time correction amount corresponding to each of the multiple consecutive tracking cycles, the optimal sampling time is determined according to the sampling time update mode.

3. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 2, characterized in that, The step of determining the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, according to the sampling time update mode, includes: If the sampling time update mode is a fast update mode, then the nearest time is selected from the multiple consecutive tracking periods. a Each tracking cycle, based on the a The target correction amount is calculated based on the sampling time correction amount corresponding to each tracking period; the initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the initial sampling time is the estimated value of the historical sampling time output by the previous tracking period before the current tracking period is updated; If the sampling time update mode is a variable weight smooth update mode, then the current satellite operation mode is obtained, and weights are assigned to each of the sampling time corrections according to the current satellite operation mode. The sampling time corrections are then weighted and summed based on the assigned weights to obtain the target correction. The initial sampling time is corrected based on the target correction to obtain the optimal sampling time. The current satellite operation mode is a steady-state orbit operation mode, an orbit maintenance mode, or a rapid orbit change mode.

4. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 3, characterized in that, The step of assigning weights to the sampling time correction amounts corresponding to each of the multiple consecutive tracking cycles according to the current satellite operation mode includes: If the current satellite operation mode is a steady orbit operation mode, then the corresponding weight is determined based on the tracking period to which each of the sampling time corrections belongs, and the weight of each of the sampling time corrections decreases exponentially as time goes by. If the current satellite operation mode is orbit maintenance mode, then the same weight is assigned to each of the sampling time corrections; If the current satellite operation mode is rapid orbit change mode, then the sampling time correction amount corresponding to the first period group and the sampling time correction amount corresponding to the second period group are respectively assigned weights, and the weight of the sampling time correction amount corresponding to the first period group is greater than the weight of the sampling time correction amount corresponding to the second period group. The first period group is the most recent one among the multiple consecutive tracking periods. L The second set of tracking cycles refers to the tracking cycles other than the first set of tracking cycles in the series of tracking cycles.

5. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 1, characterized in that, The process of determining the Doppler frequency estimate of the current frame based on the initial carrier frequency estimate of the current frame and the reference carrier frequency, and compensating the first tracking input signal based on the Doppler frequency estimate of the current frame to obtain a frequency offset correction signal includes: Based on the difference between the initial carrier frequency estimate of the current frame and the reference carrier frequency, the Doppler frequency estimate of the current frame is determined. The frequency offset compensation signal is determined based on the Doppler frequency estimate of the current frame, and the first tracking input signal is compensated based on the frequency offset compensation signal to obtain the frequency offset correction signal.

6. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 1, characterized in that, The step of performing symbol decision based on the second tracking input signal to obtain a reference symbol, and extracting carrier phase error based on the second tracking input signal and the reference symbol, includes: Based on the second tracking input signal, a symbol decision is made by the decision-maker to obtain the reference symbol; Based on the second tracking input signal and the reference symbol, the phase error is extracted by a phase detector to obtain the carrier phase error.

7. The high dynamic measurement and control data transmission signal multi-parameter joint tracking method as described in claim 1, characterized in that, The correction amount for the sampling time in each tracking cycle is obtained in the following way: For each tracking period, a set of candidate sampling points is determined, and the set of candidate sampling points includes multiple candidate sampling points; For each candidate sampling point, construct a corresponding relevant window starting from that candidate sampling point; According to the relevant window, the corresponding signal segment is extracted from the initial tracking input signal corresponding to the tracking period, and the extracted signal segment is used as the parallel candidate signal corresponding to the candidate sampling point. Calculate the correlation results between each parallel candidate signal and the local matching waveform, and determine the sampling time correction amount corresponding to the tracking period based on the correlation results of each channel.

8. A high-dynamic measurement and control data transmission signal multi-parameter joint tracking device, characterized in that, include: The sampling time tracking module is used to select multiple consecutive tracking periods based on a preset sliding window length, determine the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, and perform sampling alignment on the initial tracking input signal corresponding to the current tracking period based on the optimal sampling time to obtain the first tracking input signal. The carrier phase tracking module is used to acquire the initial value of the carrier frequency estimate and the reference carrier frequency of the current frame, determine the Doppler frequency estimate of the current frame based on the initial value of the carrier frequency estimate and the reference carrier frequency, and compensate the first tracking input signal based on the Doppler frequency estimate of the current frame to obtain the frequency offset correction signal. Obtain the phase compensation signal for the current tracking period, and multiply the phase compensation signal with the frequency offset correction signal to obtain the second tracking input signal; Symbol decision is performed based on the second tracking input signal to obtain a reference symbol. Based on the second tracking input signal and the reference symbol, the carrier phase error is extracted. The carrier phase error is filtered through a second-order loop filter to obtain a target carrier phase estimate. A phase compensation signal for the next tracking cycle is generated based on the target carrier phase estimate. The carrier frequency tracking module is used to obtain the total phase offset of the current frame based on the target carrier phase estimates corresponding to the start and end tracking periods of the current frame; to obtain the frequency residual estimate of the current frame based on the total phase offset and the duration of the current frame; to obtain the frequency observation value of the current frame based on the frequency residual estimate and the initial carrier frequency estimate of the current frame, wherein the current frame includes multiple consecutive tracking periods; and to determine the initial carrier frequency estimate of the next frame through inter-frame recursive filtering based on the frequency observation value of the current frame.

9. The high dynamic measurement and control data transmission signal multi-parameter joint tracking device as described in claim 8, characterized in that, The sampling time tracking module, when determining the optimal sampling time based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, is specifically used for: Determine the adjustment direction corresponding to the correction amount at each sampling time, and determine the maximum consecutive same-direction count based on each adjustment direction; Obtain the continuous same-direction count threshold. If the maximum continuous same-direction count is greater than the continuous same-direction count threshold, then the sampling time update mode is determined to be the fast update mode. If the maximum consecutive same-direction count is not greater than the consecutive same-direction count threshold, then the sampling time update mode is determined to be the variable weight smooth update mode. Based on the sampling time correction amount corresponding to each of the multiple consecutive tracking cycles, the optimal sampling time is determined according to the sampling time update mode.

10. The high dynamic measurement and control data transmission signal multi-parameter joint tracking device as described in claim 9, characterized in that, The sampling time tracking module, when determining the optimal sampling time according to the sampling time update mode based on the sampling time correction amount corresponding to each of the multiple consecutive tracking periods, is specifically used for: If the sampling time update mode is a fast update mode, then the nearest time is selected from the multiple consecutive tracking periods. a Each tracking cycle, based on the a The target correction amount is calculated based on the correction amount corresponding to the sampling time of each tracking cycle; The initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the initial sampling time is the estimated value of the historical sampling time output by the previous tracking period before the current tracking period is updated. If the sampling time update mode is a variable weight smooth update mode, then the current satellite operation mode is obtained, and weights are assigned to each of the sampling time corrections according to the current satellite operation mode. The target correction is obtained by weighted summation of each of the sampling time corrections based on the assigned weights. The initial sampling time is corrected based on the target correction amount to obtain the optimal sampling time; the current satellite operation mode is a steady orbit operation mode, an orbit maintenance mode, or a rapid orbit change mode.

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