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

Abstract

The application discloses a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver and relates to the technical field of radio orientation. The method comprises the following steps: performing antenna pointing deviation analysis on a shipborne moving target indication (MTI) antenna according to predicted ship attitude information in a preset time window to obtain a predicted pointing deviation angle sequence; performing feature extraction to obtain a pointing deviation trend feature and determine the calculation complexity of four radio frequency signals of the shipborne MTI antenna; dynamically configuring the phase comparison algorithm processing precision, filtering processing mode and signal compensation mechanism of the digital beacon receiver to generate an adaptive signal calculation process; and performing calculation and processing on continuous wave satellite downlink beacon signals in the preset time window through the digital beacon receiver according to the adaptive signal calculation process to obtain a single-pulse phase comparison tracking signal and perform real-time regulation and control on the azimuth and elevation of the shipborne MTI antenna. The application solves the technical problem of poor radio orientation effect in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radio orientation technology, in particular to a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver. BACKGROUND

[0002] In the field of satellite communication, it is crucial to ensure that a stable and high-gain communication link is established and maintained between a ship-borne terminal and a geosynchronous orbit satellite. The ship-borne "on-the-move" system is the core equipment to achieve this goal, which accurately points the antenna beam to the target satellite in real time on a moving ship to compensate for the pointing deviation caused by the ship's sway, thereby ensuring continuous communication. When the ship sails on the sea, its motion posture is highly nonlinear and time-varying due to the sea conditions. Especially in severe sea conditions, the high-frequency and large-amplitude sway of the ship will cause a dramatic and rapid dynamic deviation of the antenna pointing, thereby degrading the antenna tracking performance and subsequent signal processing effect. SUMMARY

[0003] The present application provides a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver, which is used to solve the technical problem of poor radio orientation effect in the prior art.

[0004] In view of the above problems, the present application provides a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver, which comprises:

[0005] analyzing the antenna pointing deviation of the ship-borne on-the-move antenna according to the predicted ship posture information within a preset time window to obtain a sequence of predicted pointing deviation angles;

[0006] extracting features from the sequence of predicted pointing deviation angles to obtain a pointing deviation trend feature, and determining the solution complexity of the four-way radio frequency signal of the ship-borne on-the-move antenna according to the pointing deviation trend feature;

[0007] dynamically configuring the phase comparison algorithm processing precision, filtering processing mode and signal compensation mechanism of the digital beacon receiver according to the solution complexity to generate an adaptive signal solution process;

[0008] According to the adaptive signal solution process, the continuous wave satellite downlink beacon signal within the preset time window is processed by the digital beacon receiver to obtain a single-pulse phase comparison tracking signal, and the azimuth and elevation of the ship-borne on-the-move antenna are real-time regulated and controlled.

[0009] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0010] The application provides a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver. Compared with the prior art, the technical scheme provided by the application breaks through the deviation of the fixed signal processing flow when facing time-varying and nonlinear ship motion, and achieves the technical effects of improving the stability of satellite link maintenance and the accuracy of signal processing of the shipborne dynamic communication system when facing complex and changeable marine environment. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the application, the drawings needed to be used in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative effort.

[0012] Figure 1 A flowchart of the single-pulse phase comparison tracking signal processing method based on the digital beacon receiver provided by the embodiments of the application is shown.

[0013] Figure 2 A flowchart of constructing an antenna pointing deviation prediction channel in the single-pulse phase comparison tracking signal processing method based on the digital beacon receiver provided by the embodiments of the application is shown. DETAILED DESCRIPTION

[0014] The application provides a single-pulse phase comparison tracking signal processing method based on a digital beacon receiver, which is used to solve the technical problem of poor radio direction effect in the prior art.

[0015] The technical solutions in the embodiments of the application will be clearly and completely described in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative effort fall within the scope of protection of the application.

[0016] It should be noted that the terms "comprising" and "having" are intended to cover the inclusions without being exclusive, for example, a process, method, system, product or server including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to the process, method, product or device.

[0017] Embodiments, such as Figure 1As shown, the present application provides a single pulse phase comparison tracking signal processing method based on a digital beacon receiver, wherein the method comprises:

[0018] S10: Analyzing the antenna pointing deviation of the shipborne dynamic in-motion antenna according to the predicted ship attitude information in the preset time window to obtain a predicted pointing deviation angle sequence.

[0019] In the single pulse tracking process of the traditional shipborne dynamic in-motion system, the perception and processing of the antenna pointing deviation are usually based on the lag feedback of the real-time measurement signal, that is, only when the ship attitude change has actually caused the pointing deviation and is reflected in the received signal, the control system begins to perform the deviation correction calculation.

[0020] The step S10 in the method provided by the embodiment of the present application comprises:

[0021] The ship is short-time attitude predicted by the shipborne high-precision inertial navigation system, and a ship motion state prediction sequence in a preset time window is obtained as the predicted ship attitude information, wherein the ship motion state at least includes roll angle, pitch angle, yaw angle, and corresponding angular velocity and angular acceleration;

[0022] Based on the historical operation log of the same type of shipborne dynamic in-motion antenna, a sample data set is collected to train a long short-term memory network, and an antenna pointing deviation prediction channel is constructed;

[0023] Based on the historical operation log of the same type of shipborne dynamic in-motion antenna, a sample data set is collected to train a long short-term memory network, and an antenna pointing deviation prediction channel is constructed, such as Figure 2 As shown, it comprises:

[0024] The ship attribute information and the attribute information of the shipborne dynamic in-motion antenna are taken as equipment constraints, and the time span of the preset time window is taken as a conditional constraint. The historical operation log of the same type of shipborne dynamic in-motion antenna is retrieved, a sample ship attitude information set is collected, and a 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;

[0025] The sample ship attitude information set and the sample pointing deviation angle sequence set are taken as training data, and K-fold cross-validation is performed to obtain K sample training sets, wherein K is an integer greater than or equal to 10;

[0026] The sample ship attitude information is taken as input, and the sample pointing deviation angle sequence is taken as label. The K sample training sets are used to train the long short-term memory network to convergence respectively, and K antenna pointing deviation prediction branches are generated.

[0027] The K antenna pointing deviation prediction branches are integrated according to the mean fusion strategy to construct an antenna pointing deviation prediction channel.

[0028] 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.

[0029] 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:

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Specifically, first, the historical operation log of the same type of shipborne dynamic directional antenna is retrieved with the ship attribute information and the attribute information of the shipborne dynamic directional antenna as the equipment constraint, with the time span of the preset time window as the conditional constraint, the 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 the sample pointing deviation angle sequence, and the sample pointing deviation angle sequence set is obtained. From the historical log library, data records matching the equipment attributes and the preset time window are filtered. For example, for each filtered historical navigation segment, the actual ship attitude information in that time period is extracted as the sample ship attitude information set, and the pointing deviation angle sequence actually measured by the antenna in that time period is extracted synchronously to obtain the sample pointing deviation angle sequence set.

[0037] Further, the sample ship attitude information set and the sample pointing deviation angle sequence set are used as training data, and K-fold cross-validation is performed to obtain K sample training sets, wherein K is an integer greater than or equal to 10. For example, the training data is evenly divided into 10 parts to obtain 10 sample training sets.

[0038] Further, a long short-term memory network is used as the core model. For example, a two-layer LSTM network structure is constructed, the first layer LSTM is set to 64 memory units, the second layer LSTM is set to 32 memory units, and a fully connected layer is finally connected to output a prediction sequence consistent with the length of the preset time window.

[0039] Further, the sample ship attitude information is used as input, the sample pointing deviation angle sequence is used as label, and the K sample training sets are used to train the long short-term memory network to convergence respectively, to generate K antenna pointing deviation prediction branches. For example, the total data set is evenly divided into 10 parts, 9 of which are combined as a training set in turn, and the remaining 1 part is used as a validation set, and the training is performed 10 times to obtain 10 LSTM model branches with the same structure 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 target. The mean square error is used as the loss function to measure the prediction, and the Adam optimization algorithm is used to continuously adjust the parameters inside the model until the prediction error on the validation set no longer decreases significantly.

[0040] Further, the K antenna pointing deviation prediction branches are integrated according to the mean fusion strategy to construct an antenna pointing deviation prediction channel. For example, for a new prediction task, let the K branch models predict respectively, and then take the arithmetic mean of the K prediction sequences output by them at the corresponding time points as the final output result of the antenna pointing deviation prediction channel.

[0041] Further, the ship operation fluctuation state is evaluated according to the predicted ship attitude information to determine a ship operation fluctuation coefficient, the antenna pointing deviation prediction channel is activated according to the ship operation fluctuation coefficient, and a predicted pointing deviation angle sequence in the preset time window is analyzed according to the predicted ship attitude information.

[0042] Specifically, first, the index variation coefficients of a plurality of 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 the plurality of index variation coefficients. From the predicted ship attitude information, the predicted value sequences of nine indexes including the roll angle, the pitch angle, the yaw angle, and their respective angular velocities and angular accelerations are extracted. The variation coefficients of the nine sequences are calculated respectively to measure the fluctuation dispersion degree of each index. For example, the roll angle variation coefficient = |roll angle standard deviation / pitch angle mean value|. Further, the nine variation coefficients are assigned weights, wherein the weight values can be set according to experience. For example, it is believed that the angular acceleration of the roll angle has a greater impact, and therefore a higher weight is given. The weighted nine variation coefficients are added to obtain the ship operation fluctuation coefficient that finally reflects the overall fluctuation condition.

[0043] Further, the ratio of the ship operation fluctuation coefficient to the maximum historical ship operation fluctuation coefficient recorded in a historical time period is multiplied by K to obtain the optimal branch selection number J, wherein 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 in a past long period, for example, one year. The ratio is obtained by dividing the currently calculated ship operation fluctuation coefficient by the maximum ship operation fluctuation coefficient. The ratio is multiplied by the total number of branches K of the prediction channel, and the product is rounded to the optimal branch selection number J. J = ship operation fluctuation coefficient / maximum ship operation fluctuation coefficient x K. For example, J = 3.7 is calculated, and J is rounded down to 3. For example, J = 0.8 is calculated, and J is rounded down to 2 to ensure that at least two branches are used for prediction.

[0044] Further, J antenna pointing deviation prediction branches are randomly selected from the K antenna pointing deviation prediction branches of the antenna pointing deviation prediction channel for antenna pointing deviation analysis. The current predicted ship attitude information is input into the J selected branch models at the same time, and each branch outputs a predicted pointing deviation angle sequence. Finally, the J prediction results are averaged and fused to obtain the predicted pointing deviation angle sequence.

[0045] By introducing short-time attitude prediction information based on high-precision inertial navigation and mapping it as a predicted antenna pointing deviation angle sequence in a future specific time window, the limitations of the traditional method in lag response are effectively solved. The method provided in the application is no longer passive compensation according to the error signal at the current time, but can predict how the antenna pointing will change in a short period of time in the future, including the size and trend of deviation, so that signal solving and servo control can be changed from passive response to active planning.

[0046] S20: performing feature extraction on the predicted pointing deviation angle sequence to obtain a pointing deviation trend feature, and determining the solving complexity of the four-way radio frequency signal of the shipborne dynamic directional antenna according to the pointing deviation trend feature.

[0047] If only the original deviation angle sequence data is available, and the essential features representing the motion intensity and dynamic characteristics cannot be extracted from it, it is difficult to accurately distinguish the signal processing requirements in different sea conditions.

[0048] The step S20 in the method provided in the embodiments of the application comprises:

[0049] extracting the maximum deviation amplitude, average angular velocity and angular acceleration extreme value of the predicted pointing deviation angle sequence in the preset time window as the pointing deviation trend feature;

[0050] Based on the historical operation log of the same type of shipborne dynamic directional antenna, a deviation trend feature-solving complexity mapping table is configured, wherein the deviation trend feature-solving complexity mapping table contains a plurality of mapping relationships, and each mapping relationship includes a sample maximum deviation amplitude threshold, a sample average angular velocity threshold, a sample angular acceleration extreme value threshold and a corresponding sample solving complexity;

[0051] The deviation trend feature-solving complexity mapping table is used to determine the solving complexity of the four-way radio frequency signal of the shipborne dynamic directional antenna according to the pointing deviation trend feature.

[0052] In the embodiments of the application, the predicted pointing deviation angle sequence is subjected to feature extraction to obtain a pointing deviation trend feature, and the solving complexity of the four-way radio frequency signal of the shipborne dynamic directional antenna is determined according to the pointing deviation trend feature.

[0053] Specifically, first, the maximum deviation amplitude, average angular velocity and angular acceleration extreme value of the predicted pointing deviation angle sequence within the preset time window are extracted as the pointing deviation trend features. Illustratively, the absolute value of the angle value of all time points in the sequence is found out, and the angle value with the maximum absolute value is obtained. For example, the angle values in a sequence are 0.1 degrees, -0.3 degrees, 0.8 degrees and -0.05 degrees, and the maximum deviation amplitude is 0.8 degrees. Further, the average angular velocity of the sequence is calculated, and the value with the maximum absolute value of the angular acceleration is extracted as the angular acceleration extreme value.

[0054] Further, based on the historical operation log of the shipborne dynamic SATCOM antenna of the same type, a deviation trend feature-complexity of calculation mapping table is configured, wherein the deviation trend feature-complexity of calculation mapping table contains a plurality of mapping relationships, and each mapping relationship includes a sample maximum deviation amplitude threshold, a sample average angular velocity threshold, a sample angular acceleration extreme value threshold and a corresponding sample complexity of calculation. Illustratively, based on the historical data, the typical characteristic value range of the antenna pointing deviation under different sea conditions and ship motion states is analyzed, and the best signal processing strategy actually required or verified to maintain stable tracking under these states is analyzed. These experiences are summarized to form a structured mapping table. The mapping table contains a plurality of mapping relationships, and each line represents a typical dynamic scene. For example, when the maximum deviation amplitude is small (such as less than 0.5 degrees), the average angular velocity is low (such as less than 1 degree / second), and the angular acceleration extreme value is also small (such as less than 5 degrees / square second), the signal processing challenge is small, and a relatively stable complexity of calculation, i.e. a stable mode, is adapted. The processing strategy corresponding to the mode is to enable the most simplified algorithm and strong noise suppression filtering to save resources and power consumption. The mapping table also contains several other modes, which respectively correspond to general dynamic, severe dynamic and extreme dynamic scenes, and a special mode for signal initial capture or recapture.

[0055] Further, the complexity of calculation of the four-way radio frequency signal of the shipborne dynamic SATCOM antenna is determined according to the pointing deviation trend features by using the deviation trend feature-complexity of calculation mapping table. For example, the extracted feature values are: maximum deviation amplitude = 1.2 degrees, average angular velocity = 2.5 degrees / second, and angular acceleration extreme value = 10 degrees / square second. It is found by querying the mapping table that these values simultaneously satisfy the threshold range defined by the standard mode, and the complexity of calculation of the four-way radio frequency signal of the shipborne dynamic SATCOM antenna is the standard mode.

[0056] By extracting the features of the predicted pointing deviation angle sequence, the continuous time series data is condensed into key pointing deviation trend features such as the maximum deviation amplitude, the average angular velocity, and the angular acceleration extreme value. These features quantify the intensity, speed, and acceleration of the antenna pointing change in the future period of time, directly reflecting the potential influence of environmental dynamics on signal stability and calculation accuracy, and then determining the calculation complexity based on these features to achieve an objective and forward-looking rating of the signal processing task difficulty.

[0057] S30: Dynamically configure the phase comparison algorithm processing precision, filtering processing mode, and signal compensation mechanism of the digital beacon receiver according to the calculation complexity, and generate an adaptive signal calculation process.

[0058] The signal calculation process of the traditional digital beacon receiver is often statically preset or has only a few fixed modes, which cannot be finely matched with the continuously changing ship motion state and the corresponding signal calculation complexity. When the calculation complexity is low, using high-precision complex algorithms and strong filtering may lead to slow response and resource waste; when the calculation complexity is high, if simple algorithms and weak filtering are still used, the error voltage signal calculated will contain a large amount of noise and distortion, which seriously reduces the quality of the tracking control signal.

[0059] The step S30 in the method provided by the embodiments of the present application comprises:

[0060] Constructing a calculation complexity-operation parameter table of the digital beacon receiver, wherein the operation parameters include the phase comparison algorithm processing precision, the filtering processing mode, and the signal compensation mechanism;

[0061] The phase comparison algorithm processing precision includes a plurality of processing algorithms with different processing precisions, wherein the processing algorithms at least include complex baseband and difference phase comparison processing, phase difference demodulation, zero-crossing phase detection, and amplitude ratio;

[0062] The filtering processing mode includes a plurality of filtering processing schemes, wherein each filtering processing scheme includes a filter type, a filter order, a cutoff bandwidth, and a filtering strategy;

[0063] The signal compensation mechanism includes temperature compensation, frequency response compensation, and non-linear compensation, wherein the frequency response compensation includes center frequency point frequency response compensation, multi-point frequency response compensation, and full-band frequency response compensation;

[0064] Using the calculation complexity-operation parameter table, the adaptive operation parameters are obtained as the adaptive signal calculation process according to the calculation complexity matching.

[0065] In the embodiments of the present application, the phase comparison algorithm processing precision, the filtering processing mode, and the signal compensation mechanism of the digital beacon receiver are dynamically configured according to the calculation complexity, and an adaptive signal calculation process is generated.

[0066] Specifically, first, a solution complexity-operation parameter table of the digital beacon receiver is constructed, wherein the operation parameters include a phase comparison algorithm processing precision, a filtering processing mode, and a signal compensation mechanism.

[0067] Specifically, the performance requirements of the shipborne SOTM system under various typical sea conditions and ship motion states are analyzed, and a number of discrete solution complexity levels from low to high are defined, for example, named L0 to L4. For each level, a set of optimized operation parameters is fixedly configured in combination with hardware processing capacity and algorithm performance, which cover three core aspects: phase comparison algorithm processing precision, filtering processing mode, and signal compensation mechanism. For example, for the smooth mode, a simple phase comparison algorithm, a narrowband low-order filter, and a basic signal compensation strategy are configured; and for the severe sea condition mode, a high-precision complex algorithm, a wideband high-order filter, and a comprehensive real-time compensation strategy are configured.

[0068] The phase comparison algorithm processing precision includes a plurality of processing algorithms with different processing precisions, wherein the processing algorithms at least include complex baseband and difference phase comparison processing, phase difference demodulation, zero-crossing phase detection, and amplitude ratio. The phase comparison algorithm is a digital signal processing method for calculating the angular deviation between the antenna pointing 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, and can process the preprocessed sum and difference channel baseband signals into single-pulse phase comparison tracking signals (i.e., azimuth / elevation error voltages). The amplitude ratio algorithm estimates the error by calculating the ratio of the amplitudes of the difference channel and the sum channel signal, which is the simplest to calculate but has limited precision. The zero-crossing phase detection algorithm calculates the phase difference by detecting the time difference of the zero-crossing points of the two signals, which has moderate calculation amount. The phase difference demodulation algorithm uses a phase-locked loop to extract the instantaneous phase of the signal and performs difference operation, which has larger calculation amount but higher precision. The complex baseband and difference phase comparison processing performs correlation operation and normalization processing on the complex representation of the two signals, which has the most complex calculation but the best linearity and anti-interference. For example, when the solution complexity is determined to be the standard mode, the phase difference demodulation algorithm is automatically selected as the configuration of the current phase comparison algorithm processing precision.

[0069] The filter processing mode includes several filter processing schemes, each of which includes a filter type, a filter order, a cutoff bandwidth, and a filter strategy. For example, each filter processing scheme is defined by four elements: the filter type includes FIR or IIR, the filter order includes multiple orders from 1st to 8th order, the cutoff bandwidth includes multiple bandwidths from several Hz to several tens of Hz, and the filter strategy includes single-stage or cascade. In a low-complexity mode such as a stationary mode, an IIR type, a low order, and a narrow cutoff bandwidth scheme is preferred to ensure signal smoothing and low computational overhead. In a high-complexity mode such as a severe sea state mode, an FIR type, a high order, and a wide cutoff bandwidth scheme is preferred to suppress noise while preserving the real dynamic changes of the error signal as much as possible.

[0070] The signal compensation mechanism includes temperature compensation, frequency response compensation, and non-linear compensation. The frequency response compensation includes center frequency point frequency response compensation, multi-point frequency response compensation, and full-band frequency response compensation. Specifically, the temperature compensation corrects the gain and phase changes by querying a compensation table or applying a compensation coefficient according to the real-time reading of the internal temperature sensor data. The accuracy mode can be high-precision real-time compensation, low-precision slow-changing compensation, or off. The frequency response compensation is used to correct the amplitude and phase inconsistency between the radio frequency channels. The options include fixed value compensation for the center working frequency point, compensation for multiple discrete frequency points, or continuous compensation for the entire working frequency band. Non-linear compensation is generally enabled under extreme conditions to offset the non-linear distortion of devices such as power amplifiers. For example, in the standard mode, real-time temperature compensation and center frequency point frequency response compensation are enabled simultaneously. In the severe sea state mode, full-featured real-time temperature compensation, full-band frequency response compensation, and non-linear compensation are enabled.

[0071] Further, the adaptive signal solving process is obtained by matching the solving complexity with the running parameter table. The solving complexity level is used as an index to accurately search in the table, and the specific configuration content of the corresponding phase comparison algorithm processing precision, filter processing mode, and signal compensation mechanism is read to form an adaptive signal solving process for the current scene.

[0072] Based on the real-time solving complexity determined in the foregoing, the core processing links of the digital beacon receiver are dynamically and adaptively configured, including the phase comparison algorithm processing precision, the filter type and parameters, and the specific strategy of the signal compensation mechanism, thereby generating a signal solving process that is most suitable for the current and near-term expected dynamic environment. In the stationary period, a simple and efficient process with low delay can be automatically selected to ensure fast response. In the turbulent period, the process is intelligently switched to a high-precision, strong-anti-noise, and compensation-enabled robust process to ensure the accuracy and reliability of the error signal.

[0073] S40: According to the adaptive signal processing procedure, the continuous wave satellite downlink beacon signal in the preset time window is processed by the digital beacon receiver to obtain a monopulse phase comparison tracking signal, and the azimuth and elevation of the shipborne moving target indication antenna are controlled in real time.

[0074] In the traditional method, signal processing and servo control are two relatively independent links, and the error voltage signal obtained by processing may have quality fluctuations due to the mismatch between the processing procedure and the environment, and directly using such a signal for control may cause unstable action of the servo system, oscillation or reduced tracking accuracy.

[0075] The step S40 in the method provided in the embodiment of the application comprises:

[0076] According to the adaptive signal processing procedure, the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne moving target indication antenna in the preset time window is processed by the digital beacon receiver to generate azimuth error voltage and elevation error voltage in real time.

[0077] In the preset time window, the azimuth axis and the elevation axis of the shipborne moving target indication antenna are controlled based on the azimuth error voltage and the elevation error voltage.

[0078] In the embodiment of the application, according to the adaptive signal processing procedure, the continuous wave satellite downlink beacon signal in the preset time window is processed by the digital beacon receiver to obtain a monopulse phase comparison tracking signal, and the azimuth and elevation of the shipborne moving target indication antenna are controlled in real time.

[0079] Specifically, first, according to the adaptive signal processing procedure, the continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne moving target indication antenna in the preset time window is processed by the digital beacon receiver to generate azimuth error voltage and elevation error voltage in real time. The continuous wave satellite downlink beacon signal received by the four-horn feed of the shipborne moving target indication antenna in the preset time window is processed by the digital beacon receiver using the acquired adaptive signal processing procedure to generate azimuth error voltage and elevation error voltage in real time. The size and polarity of the azimuth error voltage represent the distance and direction of the antenna beam center from the satellite in the horizontal direction, and the size and polarity of the elevation error voltage represent the deviation in the vertical direction. The two voltage signals together constitute a high-quality monopulse phase comparison tracking signal.

[0080] Further, within the preset time window, based on the azimuth error voltage and the elevation error voltage, servo drive regulation is performed on the azimuth axis and the elevation axis of the shipborne moving channel antenna. For example, a continuously positive azimuth error voltage will cause the controller to command the azimuth axis motor to rotate in a direction that reduces the error; the greater the error voltage, the greater the speed command for the motor rotation. Similarly, the elevation error voltage independently controls the action of the elevation axis motor until the error voltage approaches zero, indicating that the antenna has been accurately re-aligned with the satellite, effectively countering the pointing disturbance caused by the ship's sway.

[0081] According to the dynamically optimized adaptive signal solving process, the continuously received continuous wave satellite beacon signal is solved, and azimuth and elevation error voltages are generated in real time. Since the solving process is specially mapped and obtained for the expected dynamic environment in the current time window, the single pulse phase tracking signal solved by the solving process reaches the optimal balance in terms of accuracy, real-time performance and anti-interference performance in the environment.

[0082] In summary, the embodiments of the present application have at least the following technical effects:

[0083] The present application proposes a single pulse phase tracking signal processing method based on a digital beacon receiver, which significantly improves the tracking accuracy, response speed and overall robustness of the shipborne moving channel antenna in high dynamic sea conditions by prospectively analyzing the ship attitude disturbance trend and dynamically configuring the optimal signal solving process. Specifically, by integrating short-time attitude prediction data of a high-precision inertial navigation system, the maximum amplitude, average rate of change and acceleration of the antenna pointing deviation in the future time window can be quantitatively evaluated, so as to predict the challenge level that the tracking system will face in advance; based on this prediction, the deviation trend is quantified as the signal solving complexity, and the most suitable phase comparison algorithm processing precision, filtering strategy and signal compensation mechanism are dynamically matched based on this, so that a high-efficiency and simple solving process is used when the ship is moving smoothly to reduce system load and delay, and a higher-precision, stronger anti-interference and compensation-capable solving process is automatically enabled when the ship is moving violently to ensure the accuracy and stability of error extraction; this closed-loop prediction-configuration mechanism enables the antenna servo control system to always obtain high-quality single pulse phase tracking signals that best match the current and near-future dynamic environment, thereby driving the actuator to make more accurate and timely adjustment actions, effectively avoiding problems such as tracking lag and excessive error signal noise caused by mismatch between the solving process and the dynamic environment. Compared with the traditional method, the technical solution provided by the present application significantly breaks through the deviation of the fixed signal processing process in the face of time-varying and nonlinear ship motion, and achieves the technical effect of improving the stability of satellite link maintenance and signal processing accuracy when the shipborne moving channel system faces complex and variable marine environments.

[0084] It should be noted that the above-mentioned embodiment sequences of the present application are merely for description only, but not for representing the advantages and disadvantages of the embodiments. And the above-mentioned embodiments of the present specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0085] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0086] The specification and drawings are merely exemplary of the present application, and any and all modifications, variations, combinations or equivalents that are within the scope of the present application should be included. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method of monopulse phase comparison tracking signal processing based on a digital beacon receiver, characterized by, The method comprises: performing antenna pointing deviation analysis on the shipborne dynamic antenna based on the predicted ship attitude information within the preset time window to obtain a predicted pointing deviation angle sequence; performing feature extraction on the predicted pointing deviation angle sequence to obtain a pointing deviation trend feature, and determining the resolution complexity of the four-way radio frequency signal of the shipborne dynamic antenna according to the pointing deviation trend feature; dynamically configuring the phase comparison algorithm processing precision, filtering processing mode and signal compensation mechanism of the digital beacon receiver according to the resolution complexity to generate an adaptive signal resolution process; According to the adaptive signal resolution process, the continuous wave satellite downlink beacon signal within the preset time window is resolved and processed by the digital beacon receiver to obtain a single pulse phase comparison tracking signal, and the azimuth and elevation of the shipborne dynamic antenna are real-time regulated.

2. The digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 1, wherein, The ship is short-time attitude predicted by the shipborne high-precision inertial navigation system, and the ship motion state prediction sequence within the preset time window is obtained as the predicted ship attitude information, wherein the ship motion state at least includes roll angle, pitch angle, yaw angle and corresponding angular velocity and angular acceleration.

3. The digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 1, wherein, According to the predicted ship attitude information within the preset time window, the antenna pointing deviation of the shipborne dynamic antenna is analyzed, and the predicted pointing deviation angle sequence is obtained, which comprises: Based on the historical operation log of the same type of shipborne dynamic antenna, sample data set is collected to train long short-term memory network, and antenna pointing deviation prediction channel is constructed; According to the predicted ship attitude information, the ship running fluctuation state is evaluated to determine the ship running fluctuation coefficient, and the antenna pointing deviation prediction channel is activated according to the ship running fluctuation coefficient, and the predicted pointing deviation angle sequence within the preset time window is obtained according to the predicted ship attitude information.

4. The digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 3, wherein, Based on the historical operation log of the same type of shipborne dynamic antenna, sample data set is collected to train long short-term memory network, and antenna pointing deviation prediction channel is constructed, which comprises: Taking the ship attribute information and the attribute information of the shipborne dynamic antenna as the equipment constraint, and taking the time span of the preset time window as the conditional constraint, the historical operation log of the same type of shipborne dynamic antenna is retrieved, the 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 the sample pointing deviation angle sequence, and the 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 validation is performed to obtain K sample training sets, wherein K is an integer greater than or equal to 10; Taking the sample ship attitude information as input and the sample pointing deviation angle sequence as label, the long short-term memory network is trained respectively with the K sample training sets until convergence, and K antenna pointing deviation prediction branches are generated; According to the mean fusion strategy, the K antenna pointing deviation prediction branches are integrated to construct the antenna pointing deviation prediction channel.

5. The digital beacon receiver based single pulse phase comparison tracking signal processing method of claim 4, wherein, According to the predicted ship attitude information, the ship running fluctuation state is evaluated to determine the ship running fluctuation coefficient, and the antenna pointing deviation prediction channel is activated according to the ship running fluctuation coefficient, which comprises: Calculate the index variation coefficients of the plurality of predicted state index sequences in the predicted ship attitude information respectively, and perform weighted summation on the plurality of index variation coefficients to obtain a ship operation fluctuation coefficient; Multiply the ship operation fluctuation coefficient by the maximum historical ship operation fluctuation coefficient recorded in the historical time period, and multiply the result by K to obtain the optimal branch selection number J, wherein J is greater than or equal to 2 and less than or equal to K; Randomly select J antenna pointing deviation prediction branches from the K antenna pointing deviation prediction branches of the antenna pointing deviation prediction channel for antenna pointing deviation analysis.

6. The digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 1, wherein, Feature extraction is performed on the predicted pointing deviation angle sequence to obtain a pointing deviation trend feature, and the resolution complexity of the four-way radio frequency signal of the shipborne active phased array antenna is determined according to the pointing deviation trend feature, including: Extracting the maximum deviation amplitude, average angular velocity, and angular acceleration extreme value within the preset time window of the predicted pointing deviation angle sequence as the pointing deviation trend feature; Based on the historical operation log of the same type of shipborne active phased array antenna, a deviation trend feature-resolution complexity mapping table is configured, wherein the deviation trend feature-resolution complexity mapping table contains a plurality of mapping relationships, and each mapping relationship includes a sample maximum deviation amplitude threshold, a sample average angular velocity threshold, a sample angular acceleration extreme value threshold, and a corresponding sample resolution complexity; Using the deviation trend feature-resolution complexity mapping table, the resolution complexity of the four-way radio frequency signal of the shipborne active phased array antenna is determined according to the pointing deviation trend feature.

7. The digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 1, wherein, According to the resolution complexity, the phase comparison algorithm processing precision, filtering processing mode, and signal compensation mechanism of the digital beacon receiver are dynamically configured to generate an adaptive signal resolution process, including: Constructing a resolution complexity-operation parameter correspondence table for the digital beacon receiver, wherein the operation parameters include phase comparison algorithm processing precision, filtering processing mode, and signal compensation mechanism; Using the resolution complexity-operation parameter correspondence table, the adaptive operation parameters are matched and obtained according to the resolution complexity as the adaptive signal resolution process.

8. The digital beacon receiver based single pulse phase comparison tracking signal processing method of claim 7, wherein, The phase comparison algorithm processing precision includes a plurality of processing algorithms with different processing precisions, wherein the processing algorithms at least include complex baseband and difference phase comparison processing, phase difference demodulation, zero-crossing phase discrimination, and amplitude ratio; The filtering processing mode includes a plurality of filtering processing schemes, wherein each filtering processing scheme includes a filter type, a filter order, a cutoff bandwidth, and a filtering strategy.

9. The digital beacon receiver based single pulse comparison phase tracking signal processing method of claim 7, wherein, 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 digital beacon receiver based monopulse phase comparison tracking signal processing method of claim 1, wherein, According to the adaptive signal resolution process, the continuous wave satellite downlink beacon signal received by the four horn feed sources of the shipborne active phased array antenna within the preset time window is resolved and processed by the digital beacon receiver to generate azimuth error voltage and elevation error voltage in real time; Within the preset time window, based on the azimuth error voltage and the elevation error voltage, the azimuth axis and the elevation axis of the shipborne active phased array antenna are executed for servo drive regulation.

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