Monopulse phase comparison tracking signal processing method based on digital beacon receiver

Abstract

The invention discloses a monopulse phase comparison tracking signal processing method based on a digital beacon receiver, and relates to the technical field of radio orientation, and the method comprises the steps: carrying out the antenna pointing deviation analysis of a shipborne communication-in-motion antenna according to the predicted ship attitude information in a preset time window, and obtaining a predicted pointing deviation angle sequence; carrying out feature extraction to obtain a directional deviation trend feature, and determining the resolving complexity of four paths of radio frequency signals of the shipborne communication-in-motion antenna; dynamically configuring the phase comparison algorithm processing precision, the filtering processing mode and the signal compensation mechanism of the digital beacon receiver, and generating an adaptive signal resolving process; and according to an adaptive signal resolving process, resolving the continuous wave satellite downlink beacon signal in the preset time window through a digital beacon receiver to obtain a monopulse phase comparison tracking signal, and regulating and controlling the orientation and pitching of the shipborne communication-in-motion antenna in real time. According to the invention, the technical problem of poor radio orientation effect in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of radio direction finding technology, and more specifically to a method for processing single-pulse phase tracking signals based on a digital beacon receiver. Background Technology

[0002] In the field of satellite communications, ensuring the establishment and maintenance of a stable, high-gain communication link between shipborne terminals and geostationary orbit satellites is crucial. Shipborne "on-the-move communication" systems are the core equipment for achieving this goal. They ensure continuous communication by precisely aligning the antenna beam with the target satellite in real time on a moving vessel, compensating for pointing deviations caused by the ship's rolling motion. When a ship is navigating at sea, its motion is highly nonlinear and time-varying due to sea conditions. Especially in severe sea conditions, the high-frequency, large-amplitude rolling of the ship can cause severe and rapid dynamic deviations in antenna pointing, thus degrading antenna tracking performance and subsequent signal processing effectiveness. Summary of the Invention

[0003] This application provides a single-pulse phase-tracking signal processing method based on a digital beacon receiver, which is used to address the technical problem of poor radio direction finding in the prior art.

[0004] In view of the above problems, this application provides a single-pulse phase tracking signal processing method based on a digital beacon receiver, the method comprising: Based on the predicted ship attitude information within a preset time window, the pointing deviation of the shipborne mobile communication antenna is analyzed to obtain the predicted pointing deviation angle sequence. Feature extraction is performed on the predicted pointing deviation angle sequence to obtain pointing deviation trend features, and the computational complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined based on the pointing deviation trend features. Based on the aforementioned computational complexity, the phase comparison algorithm processing accuracy, filtering processing method, and signal compensation mechanism of the digital beacon receiver are dynamically configured to generate an adapted signal computation process. According to the adaptation signal calculation process, the digital beacon receiver processes the continuous wave satellite downlink beacon signal within the preset time window to obtain a single-pulse phase tracking signal, and then adjusts the azimuth and elevation of the shipborne mobile communication antenna in real time.

[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application proposes a single-pulse phase-comparison tracking signal processing method based on a digital beacon receiver. By proactively analyzing ship attitude disturbance trends and dynamically configuring the optimal signal processing flow accordingly, it significantly improves the tracking accuracy, response speed, and overall robustness of the shipborne mobile communication antenna in highly dynamic sea conditions. Compared to traditional methods, the technical solution provided in this application significantly overcomes the biases of fixed signal processing flows when facing time-varying and nonlinear ship motions, achieving the technical effect of improving the stability of satellite link maintenance and the accuracy of signal processing in complex and ever-changing marine environments. Attached Figure Description

[0006] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0007] Figure 1 This is a flowchart illustrating the single-pulse phase tracking signal processing method based on a digital beacon receiver provided in an embodiment of this application.

[0008] Figure 2 This is a schematic diagram illustrating the process of constructing an antenna pointing deviation prediction channel in the single-pulse phase tracking signal processing method based on a digital beacon receiver provided in the embodiments of this application. Detailed Implementation

[0009] This application provides a single-pulse phase tracking signal processing method based on a digital beacon receiver to address the technical problem of poor radio direction finding in the prior art.

[0010] 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.

[0011] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0012] Examples, such as Figure 1As shown, this application provides a single-pulse phase tracking signal processing method based on a digital beacon receiver, wherein the method includes: S10: Analyze the pointing deviation of the shipborne mobile communication antenna based on the predicted ship attitude information within the preset time window, and obtain the predicted pointing deviation angle sequence.

[0013] In the single-pulse tracking process of traditional shipborne mobile communication systems, the perception and processing of antenna pointing deviation is usually based on the hysteresis feedback of real-time measurement signals. That is, the control system only begins to perform correction calculations after the ship's attitude change has actually caused pointing deviation and is reflected in the received signal.

[0014] Step S10 in the method provided in this application embodiment includes: The ship's attitude is predicted in a short time by using a shipborne high-precision inertial navigation system. The predicted sequence of ship motion states within a preset time window is obtained as the predicted ship attitude information. The ship motion states include at least the roll angle, pitch angle, bow angle and their corresponding angular velocity and angular acceleration. Based on the historical operation logs of similar shipborne mobile communication antennas, a sample dataset was collected to train a long short-term memory network and construct an antenna pointing deviation prediction channel. Among them, based on the historical operation logs of similar shipborne mobile communication antennas, a sample dataset was collected to train a long short-term memory network, and an antenna pointing deviation prediction channel was constructed, such as... Figure 2 As shown, it includes: Using ship attribute information and shipborne mobile antenna attribute information as equipment constraints, and the time span of the preset time window as a condition constraint, the historical operation logs of similar shipborne mobile antennas are retrieved, a sample ship attitude information set is collected, and the historical antenna pointing deviation angle sequence corresponding to different sample ship attitude information is obtained as a sample pointing deviation angle sequence, and a sample pointing deviation angle sequence set is obtained. The sample ship attitude information set and the sample pointing deviation angle sequence set are used as training data, and K-fold cross-partitioning is performed to obtain K sample training sets, where K is an integer greater than or equal to 10; Using the sample ship attitude information as input and the sample pointing deviation angle sequence as label, the long short-term memory network is trained to convergence using the K sample training sets, generating K antenna pointing deviation prediction branches. The K antenna pointing deviation prediction branches are integrated according to the mean fusion strategy to construct the antenna pointing deviation prediction channel. Based on the predicted ship attitude information, the ship operation fluctuation state is assessed to determine the ship operation fluctuation coefficient. The antenna pointing deviation prediction channel is activated according to the ship operation fluctuation coefficient. Based on the predicted ship attitude information, the predicted pointing deviation angle sequence within the preset time window is obtained. The process includes assessing the ship's operational fluctuation state based on the predicted ship attitude information to determine the ship's operational fluctuation coefficient, and activating the antenna pointing deviation prediction channel according to the ship's operational fluctuation coefficient, including: The coefficients of variation of multiple predicted state index sequences in the predicted ship attitude information are calculated respectively, and the ship operation fluctuation coefficient is obtained by weighted summation of multiple index coefficients. The optimal number of branches J is obtained by multiplying the ratio of the ship operation fluctuation coefficient to the maximum historical ship operation fluctuation coefficient recorded in the historical time period by K and rounding down, where J is greater than or equal to 2 and less than or equal to K. J antenna pointing deviation prediction branches are randomly selected from the K antenna pointing deviation prediction branches in the antenna pointing deviation prediction channel for antenna pointing deviation analysis.

[0015] In this embodiment of the application, the pointing deviation of the shipborne mobile communication antenna is analyzed based on the predicted ship attitude information within a preset time window to obtain the predicted pointing deviation angle sequence.

[0016] Specifically, firstly, a short-term attitude prediction of the ship is performed using an onboard high-precision inertial navigation system. This obtains a predicted sequence of ship motion states within a preset time window as the predicted ship attitude information. The ship motion states include at least the roll angle, pitch angle, and bow angle, along with their corresponding angular velocities and angular accelerations. For example, the onboard high-precision inertial navigation system receives the ship's attitude and motion parameters at the current moment. Using a built-in motion model and filtering extrapolation algorithm, it calculates a sequence of ship attitude changes over a preset time period (e.g., within the next 5 seconds). This process continuously outputs predicted values ​​at multiple time points. Each predicted value includes the roll angle, pitch angle, and bow angle, along with their corresponding angular velocities and angular accelerations.

[0017] Furthermore, based on the historical operation logs of similar shipborne mobile communication antennas, a sample dataset was collected to train a long short-term memory network and construct an antenna pointing deviation prediction channel.

[0018] Specifically, firstly, using ship attribute information and shipborne mobile communication antenna attribute information as equipment constraints, and the time span of the preset time window as a condition constraint, historical operation logs of similar shipborne mobile communication antennas are retrieved to collect sample ship attitude information sets. The historical antenna pointing deviation angle sequences corresponding to different sample ship attitude information are then obtained as sample pointing deviation angle sequences, resulting in a sample pointing deviation angle sequence set. Data records matching the equipment attributes and preset time window with the current task are filtered from the historical log database. For example, for each selected historical navigation segment, the actual ship attitude information within that time period is extracted as a sample ship attitude information set, and the pointing deviation angle sequence actually measured by the antenna within that time period is simultaneously extracted to obtain a sample pointing deviation angle sequence set.

[0019] Furthermore, the sample ship attitude information set and the sample pointing deviation angle sequence set are used as training data, and K-fold cross-partitioning is performed to obtain K sample training sets, where K is an integer greater than or equal to 10. For example, the training data is divided into 10 equal parts to obtain 10 sample training sets.

[0020] Furthermore, a Long Short-Term Memory (LSTM) network is used as the core model. For example, a two-layer LSTM network structure is constructed, with the first LSTM layer having 64 memory units and the second LSTM layer having 32 memory units. Finally, a fully connected layer is connected to output a predicted sequence with the same length as the preset time window.

[0021] Further, using the sample ship attitude information as input and the sample pointing deviation angle sequence as labels, the Long Short-Term Memory (LSTM) network is trained to convergence using the K sample training sets, generating K antenna pointing deviation prediction branches. For example, the total dataset is divided into 10 equal parts, with 9 parts merged as the training set and the remaining part used as the validation set. This is trained 10 times, resulting in 10 LSTM model branches with identical structures but slightly different training data. During training, the sample ship attitude information set is used as input, and the sample antenna pointing deviation angle sequence is used as the training objective. Mean squared error is used as the loss function to measure prediction quality, and the Adam optimization algorithm is used to continuously adjust the model's internal parameters until the prediction error on the validation set no longer decreases significantly.

[0022] Furthermore, the K antenna pointing deviation prediction branches are integrated using a mean fusion strategy to construct an antenna pointing deviation prediction channel. For example, for a new prediction task, each of the K branch models makes a prediction, and then the arithmetic mean of their output K prediction sequences at the corresponding time points is taken as the final output of the antenna pointing deviation prediction channel.

[0023] Furthermore, based on the predicted ship attitude information, the ship operation fluctuation state is assessed to determine the ship operation fluctuation coefficient. The antenna pointing deviation prediction channel is activated according to the ship operation fluctuation coefficient. Based on the predicted ship attitude information, the predicted pointing deviation angle sequence within the preset time window is obtained.

[0024] Specifically, firstly, the coefficients of variation of multiple predicted state index sequences in the predicted ship attitude information are calculated, and the weighted sum of these coefficients yields the ship's operational fluctuation coefficient. From the predicted ship attitude information, predicted value sequences of nine indicators are extracted: roll angle, pitch angle, bow angle, and their respective angular velocities and angular accelerations. The coefficients of variation of these nine sequences are calculated separately to measure the degree of dispersion of each indicator's fluctuation. For example, the roll angle coefficient of variation = |roll angle standard deviation / roll angle mean|. Further, weights are assigned to these nine coefficients of variation, where the weights can be set empirically; for example, if the angular acceleration of the roll angle is considered to have a greater impact, it is given a higher weight. The weighted sum of the nine coefficients of variation yields the final ship operational fluctuation coefficient, which reflects the overall fluctuation status.

[0025] Further, the ratio of the ship operation fluctuation coefficient to the maximum historical ship operation fluctuation coefficient recorded within the historical time period is multiplied by K and rounded down to obtain the optimal number of branches J, where J is greater than or equal to 2 and less than or equal to K. The historical database is queried to find the maximum ship operation fluctuation coefficient recorded within a relatively long period, such as one year. The currently calculated ship operation fluctuation coefficient is divided by the maximum ship operation fluctuation coefficient to obtain a ratio. This ratio is multiplied by the total number of branches K in the prediction channel, and the product is then rounded to the nearest integer, resulting in the optimal number of branches J. J = Ship operation fluctuation coefficient / Maximum ship operation fluctuation coefficient × K. For example, if J = 3.7, it is rounded down to 3; if J = 0.8, it is rounded down to 2 to ensure that at least two branches are used for prediction.

[0026] Furthermore, J antenna pointing deviation prediction branches are randomly selected from the K antenna pointing deviation prediction branches in the antenna pointing deviation prediction channel for antenna pointing deviation analysis. The current predicted ship attitude information is simultaneously input into these J selected branch models, and each branch outputs a predicted pointing deviation angle sequence. Finally, these J prediction results are averaged and fused to obtain the predicted pointing deviation angle sequence.

[0027] By introducing short-time attitude prediction information based on high-precision inertial navigation and mapping it to a sequence of antenna pointing deviation angles within a specific future time window, the limitations of traditional methods in responding with lag are effectively addressed. The method provided in this application no longer passively compensates based solely on the error signal at the current moment, but instead predicts in advance how the antenna pointing will change over a short period in the future, including the magnitude and trend of the deviation. This allows signal processing and servo control to shift from passive response to active planning.

[0028] S20: Perform feature extraction on the predicted pointing deviation angle sequence to obtain pointing deviation trend features, and determine the computational complexity of the four radio frequency signals of the shipborne mobile communication antenna based on the pointing deviation trend features.

[0029] If we only have the raw deviation angle sequence data, but cannot extract the essential features that characterize the intensity and dynamics of the motion, it will be difficult to accurately distinguish the signal processing requirements under different sea states.

[0030] Step S20 in the method provided in this application embodiment includes: The maximum deviation amplitude, average angular velocity, and extreme values ​​of angular acceleration within the preset time window of the predicted pointing deviation angle sequence are extracted as pointing deviation trend features. Based on the historical operation logs of similar shipborne mobile communication antennas, a deviation trend feature-solution complexity mapping table is configured. The deviation trend feature-solution complexity mapping table contains several mapping relationships, and each mapping relationship includes the maximum deviation amplitude threshold, the average angular velocity threshold, the extreme value threshold of the angular acceleration, and the corresponding sample solution complexity. Using the deviation trend feature-computation complexity mapping table, the computation complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined according to the pointing deviation trend feature.

[0031] In this embodiment of the application, feature extraction is performed on the predicted pointing deviation angle sequence to obtain pointing deviation trend features, and the computational complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined based on the pointing deviation trend features.

[0032] Specifically, firstly, the maximum deviation amplitude, average angular velocity, and extreme value of angular acceleration within the preset time window of the predicted pointing deviation angle sequence are extracted as pointing deviation trend features. For example, the predicted deviation angle values ​​at all time points in the sequence are traversed, and the angle value with the largest absolute value is found. For instance, if the angle values ​​in a sequence are 0.1 degrees, -0.3 degrees, 0.8 degrees, and -0.05 degrees, then its maximum deviation amplitude is 0.8 degrees. Further, the average angular velocity of the sequence is calculated, and the value with the largest absolute value of angular acceleration is extracted as the extreme value of angular acceleration.

[0033] Furthermore, based on the historical operation logs of similar shipborne mobile communication antennas, a deviation trend feature-solution complexity mapping table is configured. This table contains several mapping relationships, each including a maximum deviation amplitude threshold, a sample average angular velocity threshold, a sample angular acceleration extreme value threshold, and the corresponding sample solution complexity. For example, based on historical data, the typical characteristic value range of antenna pointing deviation under different sea states and ship motion states is analyzed, along with the optimal signal processing strategies actually needed or verified to maintain stable tracking under these states. These experiences are summarized and organized into a structured mapping table. This table contains multiple rows of mapping relationships, each representing a typical dynamic scenario. For instance, one row might indicate that when the maximum deviation amplitude is very small (e.g., less than 0.5 degrees), the average angular velocity is very low (e.g., less than 1 degree / second), and the angular acceleration extreme value is also small (e.g., less than 5 degrees / square second), the signal processing challenge is relatively small, thus adapting to a more stable solution complexity, i.e., a stable mode. The corresponding processing strategy for this mode is to enable the simplest algorithm and strong noise suppression filtering to save resources and power consumption. The mapping table also includes several other modes, corresponding to general dynamic, severe dynamic, and extreme dynamic scenarios, as well as a dedicated mode for initial signal acquisition or reacquisition.

[0034] Furthermore, using the aforementioned deviation trend feature-computation complexity mapping table, the computational complexity of the four radio frequency signals of the shipborne mobile antenna is determined based on the pointing deviation trend features. For example, the extracted feature values ​​are: maximum deviation amplitude = 1.2 degrees, average angular velocity = 2.5 degrees / second, and extreme angular acceleration = 10 degrees / square second. Looking up the mapping table, it is found that these values ​​simultaneously meet the threshold range defined by the standard mode; therefore, the computational complexity of the four radio frequency signals of the shipborne mobile antenna is in the standard mode.

[0035] By extracting features from the predicted pointing deviation angle sequence, continuous time-series data is condensed into key pointing deviation trend features such as maximum deviation amplitude, average angular velocity, and extreme values ​​of angular acceleration. These features quantify the intensity, speed, and acceleration of antenna pointing changes over a future period, directly reflecting the potential impact of environmental dynamics on signal stability and solution accuracy. Based on these features, the solution complexity is determined, enabling an objective and forward-looking assessment of the signal processing task's difficulty.

[0036] S30: Dynamically configure the phase comparison algorithm processing accuracy, filtering processing method and signal compensation mechanism of the digital beacon receiver according to the solution complexity, and generate an adapted signal solution process.

[0037] Traditional digital beacon receivers often employ static presets or only a few fixed modes for signal processing, making it impossible to precisely match the continuously changing ship motion states and corresponding signal processing complexity. When the processing complexity is low, using high-precision complex algorithms and strong filtering may lead to slow response and wasted resources; when the processing complexity is high, if simple algorithms and weak filtering are still used, the calculated error voltage signal will contain a large amount of noise and distortion, severely degrading the quality of the tracking control signal.

[0038] Step S30 in the method provided in this application embodiment includes: A computational complexity-operating parameter comparison table for a digital beacon receiver is constructed, wherein the operating parameters include the phase comparison algorithm processing accuracy, filtering processing method, and signal compensation mechanism; The phase comparison algorithm processing accuracy includes multiple processing algorithms with different processing accuracy, wherein the processing algorithm includes at least complex baseband and difference phase comparison processing, phase difference demodulation, zero-crossing phase detection and amplitude ratio; The filtering process includes several filtering schemes, each of which includes a filter type, filter order, cutoff bandwidth, and filtering strategy. The signal compensation mechanism includes temperature compensation, frequency response compensation, and nonlinearity compensation. The frequency response compensation includes center frequency point frequency response compensation, multi-point frequency response compensation, and full-band frequency response compensation. Using the aforementioned solution complexity-running parameter lookup table, appropriate running parameters are obtained based on the solution complexity as an appropriate signal solution process.

[0039] In this embodiment of the application, the phase comparison algorithm processing accuracy, filtering processing method and signal compensation mechanism of the digital beacon receiver are dynamically configured according to the solution complexity to generate an adapted signal solution process.

[0040] Specifically, firstly, a computational complexity-operating parameter comparison table for a digital beacon receiver is constructed, wherein the operating parameters include the phase comparison algorithm processing accuracy, filtering processing method, and signal compensation mechanism.

[0041] Specifically, the performance requirements of the shipborne mobile communication system under various typical sea states and ship motion conditions are analyzed, and several discrete computational complexity levels, from low to high, are defined, for example, named L0 to L4. For each level, a set of optimized operating parameters is configured based on hardware processing capabilities and algorithm performance. These parameters cover three core aspects: the accuracy of the phase comparison algorithm, the filtering method, and the signal compensation mechanism. For example, for the stable mode, the configuration uses a computationally simple phase comparison algorithm, a narrowband low-order filter, and a basic signal compensation strategy; while for the severe sea state mode, the configuration uses a high-precision complex algorithm, a wideband high-order filter, and a comprehensive real-time compensation strategy.

[0042] The phase comparison algorithm includes multiple processing algorithms with varying degrees of precision. These algorithms at least include complex baseband sum-difference phase comparison processing, phase difference demodulation, zero-crossing phase detection, and amplitude ratio. The phase comparison algorithm is a digital signal processing method that calculates the angular deviation between the antenna pointing direction and the target line of sight by precisely measuring and comparing the phase difference of the same beacon signal from different subarrays (or sum and difference channels) of the antenna. It can process the pre-processed sum and difference channel baseband signals into a single-pulse phase comparison tracking signal (i.e., azimuth / elevation error voltage). The amplitude ratio algorithm estimates the error by calculating the ratio of the difference channel signal amplitude to the sum channel signal amplitude; it is the simplest to calculate but has limited accuracy. The zero-crossing phase detection algorithm calculates the phase difference by detecting the time difference between the zero-crossing points of the two signals; its computational load is moderate. The phase difference demodulation algorithm uses a phase-locked loop to extract the instantaneous phase of the signal and performs difference calculations; its computational load is large but its accuracy is high. Complex baseband and differential phase comparison processing perform correlation and normalization operations on the complex representations of the two signals. This method is the most computationally complex but offers the best linearity and anti-interference capabilities. For example, when the computational complexity is determined to be in standard mode, the phase difference demodulation algorithm will be automatically selected as the current phase comparison algorithm's processing accuracy configuration.

[0043] The filtering process includes several filtering schemes, each comprising a filter type, filter order, cutoff bandwidth, and filtering strategy. For example, each filtering scheme is clearly defined by four elements: filter type (FIR or IIR), filter order (multiple orders from 1st to 8th), cutoff bandwidth (multiple bandwidths from a few hertz to tens of hertz), and filtering strategy (single-stage or cascaded). In low-computational-complexity modes, such as stable modes, IIR-type, low-order, narrow-cutoff-bandwidth schemes are preferred to ensure signal smoothness and low computational overhead. In high-complexity modes, such as severe sea state modes, FIR-type, high-order, wide-cutoff-bandwidth schemes are preferred to suppress noise while preserving the true dynamic changes of the error signal as much as possible.

[0044] The signal compensation mechanism includes temperature compensation, frequency response compensation, and nonlinearity compensation. Frequency response compensation includes center frequency response compensation, multi-point frequency response compensation, and full-band frequency response compensation. Specifically, temperature compensation corrects gain and phase changes based on real-time data from the internal temperature sensor by consulting a compensation table or applying compensation coefficients. Its accuracy modes include high-precision real-time compensation, low-precision gradual compensation, or off. Frequency response compensation corrects amplitude and phase inconsistencies between RF channels. Options include fixed-value compensation only for the center operating frequency, compensation for multiple discrete frequency points, or continuous compensation across the entire operating band. Nonlinearity compensation is generally enabled under extreme conditions to counteract nonlinear distortion from components such as power amplifiers. For example, in standard mode, real-time temperature compensation and center frequency response compensation are enabled simultaneously; while in severe sea state mode, full-function real-time temperature compensation, full-band frequency response compensation, and nonlinearity compensation are enabled.

[0045] Furthermore, using the aforementioned solution complexity-operation parameter lookup table, suitable operation parameters are obtained based on the solution complexity to form an adapted signal solution process. Using the solution complexity level as an index, a precise search is performed in the lookup table to read all the specific configuration details of the corresponding phase comparison algorithm processing precision, filtering processing method, and signal compensation mechanism, thus constructing an adapted signal solution process for the current scenario.

[0046] Based on the aforementioned determined real-time computation complexity, the core processing stages of the digital beacon receiver are dynamically and adaptively configured, including the processing accuracy of the phase comparison algorithm, the type and parameters of the filters, and the specific strategies of the signal compensation mechanism. This generates a signal computation flow that is best suited to the current and anticipated dynamic environment. During stable periods, a simple, efficient, and low-latency flow can be automatically selected to ensure rapid response; during turbulent periods, it intelligently switches to a robust flow with high precision, strong noise immunity, and compensation to ensure the accuracy and reliability of the error signal.

[0047] S40: According to the adaptation signal calculation process, the digital beacon receiver processes the continuous wave satellite downlink beacon signal within the preset time window to obtain a single pulse phase tracking signal, and then adjusts the azimuth and elevation of the shipborne mobile communication antenna in real time.

[0048] In traditional methods, signal processing and servo control are two relatively independent processes. The calculated error voltage signal may have quality fluctuations due to mismatch between the processing flow and the environment. Directly using such a signal for control may lead to unstable servo system operation, oscillation, or decreased tracking accuracy.

[0049] Step S40 in the method provided in this application embodiment includes: According to the adaptive signal calculation process, the digital beacon receiver processes the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne mobile communication antenna within the preset time window, and generates azimuth error voltage and elevation error voltage in real time. Within the preset time window, based on the azimuth error voltage and pitch error voltage, servo drive control is performed on the azimuth and pitch axes of the shipborne mobile communication antenna.

[0050] In this embodiment of the application, according to the adaptation signal calculation process, the digital beacon receiver calculates and processes the continuous wave satellite downlink beacon signal within the preset time window to obtain a single pulse phase tracking signal, and then adjusts the azimuth and elevation of the shipborne mobile communication antenna in real time.

[0051] Specifically, firstly, following the adaptation signal processing flow, the digital beacon receiver processes the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne mobile antenna within the preset time window, generating azimuth error voltage and elevation error voltage in real time. Secondly, the digital beacon receiver processes the acquired adaptation signal processing flow for the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne mobile antenna within the preset time window, generating azimuth error voltage and elevation error voltage in real time. The magnitude and polarity of the azimuth error voltage represent the distance and direction of the antenna beam center's deviation from the satellite in the horizontal direction, while the magnitude and polarity of the elevation error voltage represent the deviation in the vertical direction. These two voltage signals together constitute a high-quality single-pulse phase tracking signal.

[0052] Furthermore, within the preset time window, servo drive control is performed on the azimuth and pitch axes of the shipborne mobile antenna based on the azimuth error voltage and pitch error voltage. For example, a continuously positive azimuth error voltage will cause the controller to command the azimuth axis motor to rotate in the direction that reduces the error; the larger the error voltage, the greater the speed command for the motor rotation. Similarly, the pitch error voltage independently controls the movement of the pitch axis motor until the error voltage approaches zero, indicating that the antenna has been accurately re-aligned with the satellite, effectively counteracting the pointing disturbance caused by the ship's rolling motion.

[0053] Following the dynamically optimized adaptive signal processing flow, the received continuous wave satellite beacon signals are processed to generate azimuth and elevation error voltages in real time. Because this processing flow is specifically mapped to address the anticipated dynamic environment within the current time window, the calculated single-pulse phase tracking signal achieves an optimal balance in terms of accuracy, real-time performance, and anti-interference capability under this environment.

[0054] In summary, the embodiments of this application have at least the following technical effects: This application proposes a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver. By proactively analyzing the ship's attitude disturbance trend and dynamically configuring the optimal signal processing flow accordingly, it significantly improves the tracking accuracy, response speed, and overall robustness of the shipborne mobile antenna in highly dynamic sea conditions. Specifically, by integrating short-time attitude prediction data from a high-precision inertial navigation system, the dynamic trend characteristics of antenna pointing deviation, such as maximum amplitude, average rate of change, and acceleration, can be quantitatively assessed within a future time window, thus predicting the level of challenges the tracking system will face in advance. Based on this prediction, the deviation trend is quantified into signal processing complexity, and the most suitable phase comparison algorithm processing accuracy, filtering strategy, and signal compensation mechanism are dynamically matched accordingly. This allows for an efficient and concise processing flow to reduce system load and delay during smooth ship motion, while automatically activating a higher-precision processing flow with stronger anti-interference and compensation capabilities during severe swaying to ensure the accuracy and stability of error extraction. This closed-loop prediction-configuration mechanism enables the antenna servo control system to always obtain a high-quality single-pulse phase comparison tracking signal that best matches its current and near-term dynamic environment, thereby driving the actuator to make more precise and timely adjustments. This effectively avoids problems such as tracking lag and excessive error signal noise that may be caused by mismatch between the processing flow and the dynamic environment. Compared with traditional methods, the technical solution provided in this application significantly overcomes the deviation of fixed signal processing procedures when facing time-varying and nonlinear ship motion, and achieves the technical effect of improving the stability of satellite link maintenance and the accuracy of signal processing of shipborne mobile communication systems in the face of complex and ever-changing marine environments.

[0055] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0056] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0057] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for processing single-pulse phase-tracking signals based on a digital beacon receiver, characterized in that, The methods include: Based on the predicted ship attitude information within a preset time window, the pointing deviation of the shipborne mobile communication antenna is analyzed to obtain the predicted pointing deviation angle sequence. Feature extraction is performed on the predicted pointing deviation angle sequence to obtain pointing deviation trend features, and the computational complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined based on the pointing deviation trend features. Based on the aforementioned computational complexity, the phase comparison algorithm processing accuracy, filtering processing method, and signal compensation mechanism of the digital beacon receiver are dynamically configured to generate an adapted signal computation process. According to the adaptation signal calculation process, the digital beacon receiver processes the continuous wave satellite downlink beacon signal within the preset time window to obtain a single-pulse phase tracking signal, and then adjusts the azimuth and elevation of the shipborne mobile communication antenna in real time.

2. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 1, characterized in that, The ship's attitude is predicted in a short time by using a shipborne high-precision inertial navigation system. The predicted sequence of ship motion states within a preset time window is used as the predicted ship attitude information. The ship motion states include at least the roll angle, pitch angle, bow angle and their corresponding angular velocity and angular acceleration.

3. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 1, characterized in that, Based on the predicted ship attitude information within a preset time window, the pointing deviation of the shipborne mobile communication antenna is analyzed to obtain the predicted pointing deviation angle sequence, including: Based on the historical operation logs of similar shipborne mobile communication antennas, a sample dataset was collected to train a long short-term memory network and construct an antenna pointing deviation prediction channel. Based on the predicted ship attitude information, the ship operation fluctuation state is assessed to determine the ship operation fluctuation coefficient. The antenna pointing deviation prediction channel is activated according to the ship operation fluctuation coefficient. Based on the predicted ship attitude information, the predicted pointing deviation angle sequence within the preset time window is obtained.

4. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 3, characterized in that, Based on historical operation logs of similar shipborne mobile communication antennas, a sample dataset was collected to train a long short-term memory network, constructing an antenna pointing deviation prediction channel, including: Using ship attribute information and shipborne mobile antenna attribute information as equipment constraints, and the time span of the preset time window as a condition constraint, the historical operation logs of similar shipborne mobile antennas are retrieved, a sample ship attitude information set is collected, and the historical antenna pointing deviation angle sequence corresponding to different sample ship attitude information is obtained as a sample pointing deviation angle sequence, and a sample pointing deviation angle sequence set is obtained. The sample ship attitude information set and the sample pointing deviation angle sequence set are used as training data, and K-fold cross-partitioning is performed to obtain K sample training sets, where K is an integer greater than or equal to 10; Using the sample ship attitude information as input and the sample pointing deviation angle sequence as label, the long short-term memory network is trained to convergence using the K sample training sets, generating K antenna pointing deviation prediction branches. The K antenna pointing deviation prediction branches are integrated using a mean fusion strategy to construct an antenna pointing deviation prediction channel.

5. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 4, characterized in that, Based on the predicted ship attitude information, the ship's operational fluctuation state is assessed to determine the ship's operational fluctuation coefficient. The antenna pointing deviation prediction channel is then activated according to the predicted ship operational fluctuation coefficient, including: The coefficients of variation of multiple predicted state index sequences in the predicted ship attitude information are calculated respectively, and the ship operation fluctuation coefficient is obtained by weighted summation of multiple index coefficients. The optimal number of branches J is obtained by multiplying the ratio of the ship operation fluctuation coefficient to the maximum historical ship operation fluctuation coefficient recorded in the historical time period by K and rounding down, where J is greater than or equal to 2 and less than or equal to K. J antenna pointing deviation prediction branches are randomly selected from the K antenna pointing deviation prediction branches in the antenna pointing deviation prediction channel for antenna pointing deviation analysis.

6. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 1, characterized in that, Feature extraction is performed on the predicted pointing deviation angle sequence to obtain pointing deviation trend features. Based on these pointing deviation trend features, the computational complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined, including: The maximum deviation amplitude, average angular velocity, and extreme values ​​of angular acceleration within the preset time window of the predicted pointing deviation angle sequence are extracted as pointing deviation trend features. Based on the historical operation logs of similar shipborne mobile communication antennas, a deviation trend feature-solution complexity mapping table is configured. The deviation trend feature-solution complexity mapping table contains several mapping relationships, and each mapping relationship includes the maximum deviation amplitude threshold, the average angular velocity threshold, the extreme value threshold of the angular acceleration, and the corresponding sample solution complexity. Using the deviation trend feature-computation complexity mapping table, the computation complexity of the four radio frequency signals of the shipborne mobile communication antenna is determined according to the pointing deviation trend feature.

7. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 1, characterized in that, Based on the aforementioned computational complexity, the phase comparison algorithm processing accuracy, filtering method, and signal compensation mechanism of the digital beacon receiver are dynamically configured to generate an adapted signal computation process, including: A computational complexity-operating parameter comparison table for a digital beacon receiver is constructed, wherein the operating parameters include the phase comparison algorithm processing accuracy, filtering processing method, and signal compensation mechanism; Using the aforementioned solution complexity-running parameter lookup table, appropriate running parameters are obtained based on the solution complexity as an appropriate signal solution process.

8. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 7, characterized in that, The phase comparison algorithm processing accuracy includes multiple processing algorithms with different processing accuracy, wherein the processing algorithm includes at least complex baseband and difference phase comparison processing, phase difference demodulation, zero-crossing phase detection and amplitude ratio; The filtering process includes several filtering schemes, each of which includes a filter type, filter order, cutoff bandwidth, and filtering strategy.

9. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 7, characterized in that, The signal compensation mechanism includes temperature compensation, frequency response compensation, and nonlinear compensation, wherein the frequency response compensation includes center frequency point frequency response compensation, multi-point frequency response compensation, and full-band frequency response compensation.

10. The single-pulse phase tracking signal processing method based on a digital beacon receiver according to claim 1, characterized in that, According to the adaptive signal calculation process, the digital beacon receiver processes the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne mobile communication antenna within the preset time window, and generates azimuth error voltage and elevation error voltage in real time. Within the preset time window, based on the azimuth error voltage and pitch error voltage, servo drive control is performed on the azimuth and pitch axes of the shipborne mobile communication antenna.

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