A method for cluster timing of Beidou navigation equipment

Abstract

The present invention relates to the field of navigation information technology, and in particular to a Beidou navigation device cluster timing method. The method comprises the following steps: starting a navigation device in a Beidou navigation device cluster, placing it in a standby state, and detecting a spread spectrum signal to determine whether a timing broadcast signal exists; if a spread spectrum signal is detected, controlling the navigation device to capture the spread spectrum signal to obtain the spread spectrum signal; demodulating the spread spectrum signal to obtain the signal content, wherein the signal content includes timing information and telegram content; extracting time information from the signal content to obtain time information, and performing time synchronization operations on each navigation device in the Beidou navigation device cluster according to the time information. Based on the high-precision ranging characteristics of the spread spectrum signal and utilizing the spread spectrum signal processing capability of the existing navigation receiver, the present invention provides a safe, reliable, higher-precision solution that is fully compatible with the existing Beidou navigation receiver hardware and software.

Description

Technical Field

[0001] The present invention relates to the field of navigation information technology, and in particular to a Beidou navigation equipment cluster timing method. Background Art

[0002] Beidou navigation equipment needs a reference time to capture Beidou authorization signals. The higher the accuracy of the time reference relative to Beidou time, the more conducive it is for navigation equipment to quickly complete the capture and tracking of authorization signals, thereby obtaining the space-time information provided by the Beidou navigation system, improving the level of informatization and rapid response capabilities. There are currently a variety of solutions for timing Beidou navigation equipment. Common ones include injecting and maintaining time information through the timing line, which is too inefficient for tens of thousands of devices; timing by receiving the general civil signal of Beidou satellites, but the general civil signal broadcast by the satellite is weak and easily deceived by the enemy; and the Beidou short message RDSS timing method cannot be used to time navigation equipment that does not support the RDSS system, and RDSS is accessed on a large scale at the same time within a beam range, and the satellite payload will be very heavy. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a Beidou navigation equipment cluster timing method to solve at least one of the above technical problems.

[0004] The present application provides a Beidou navigation device cluster timing method, the method comprising:

[0005] S1. Start the navigation equipment in the Beidou navigation equipment cluster, put it in standby mode, and detect the spread spectrum signal to determine whether there is a timing broadcast signal;

[0006] S2. If a spread spectrum signal is detected, control the navigation device to capture the spread spectrum signal to obtain the spread spectrum signal;

[0007] S3, demodulating the spread spectrum signal to obtain signal content, wherein the signal content includes timing information and message content;

[0008] S4. Extract time information from the signal content to obtain time information, and perform time synchronization operations on each navigation device in the Beidou navigation device cluster based on the time information.

[0009] In the present invention, by capturing and demodulating the spread spectrum signal, time information can be extracted quickly and accurately, thereby achieving synchronization of the navigation device time and improving the consistency of the internal time of the navigation device cluster. The use of spread spectrum signals for time synchronization can reduce system errors, improve the positioning accuracy and navigation accuracy of the navigation device, and help improve the overall performance of the navigation system. By detecting the existence of the spread spectrum signal and demodulating the signal content, it is possible to timely detect and take measures when the signal is unstable or interfered, thereby enhancing the reliability and stability of the navigation system. The navigation device detects the spread spectrum signal in the standby state, and only performs subsequent operations when the signal is detected, which effectively saves energy consumption and extends the service life of the equipment. The use of spread spectrum signals compatible with the Beidou navigation system for time synchronization ensures the compatibility of the system with existing navigation equipment, avoids the cost of equipment replacement and updating, and improves the sustainable development capability of the system.

[0010] Optionally, the spread spectrum signal is sent via a mobile carrier, which includes an unmanned aerial vehicle, a car, a helicopter, and other carriers with mobility capabilities, and the spread spectrum signal is a time broadcast signal modulated by spread spectrum.

[0011] In the present invention, by utilizing mobile carriers, the coverage of timing broadcast signals can be expanded to a wider area, including various terrains such as cities, suburbs, and mountainous areas, thereby improving the coverage and applicability of navigation equipment. Mobile carriers have the characteristics of rapid deployment and mobility, and can adjust their positions and coverage at any time according to actual needs, flexibly respond to navigation needs in different regions, and improve the resilience and response speed of the system. Compared with traditional fixed base stations, the use of mobile carriers to send spread spectrum signals can reduce the cost of infrastructure construction, and does not require fixed installation equipment, saving manpower, material resources and maintenance costs. Mobile carriers are mobile and can adjust their positions and directions as needed, which helps to make up for blind spots that cannot be covered by fixed base stations, and improves the coverage robustness and stability of the system. Mobile carriers can select safe locations for deployment according to actual conditions to avoid being affected by factors such as severe weather, natural disasters or man-made damage, thereby improving the safety and reliability of the system.

[0012] Optionally, the code initial phase, frame format, information rate, information content, information scrambling encryption strategy and other contents related to the receiver software processing in the spread spectrum signal are different from the corresponding contents in the Beidou general civil code signal. The other contents related to the receiver software processing include data demodulation algorithm, bit error rate correction method, channel equalization processing, pseudo code tracking, pseudo code generation method, signal filtering strategy and receiver software update mechanism.

[0013] In the present invention, by configuring the spread spectrum signal specifically, including differentiated settings such as the initial phase of the code, information scrambling and encryption, the security and anti-interference ability of the signal can be improved, the signal can be prevented from being illegally tampered with or maliciously interfered, and the normal operation of the navigation system can be guaranteed. Compared with the general civil code signal, the differentiated configuration of the spread spectrum signal can reduce interference and interference between systems, improve the stability and reliability of the system, and reduce the possibility of errors. By adjusting the parameters such as the information rate and information content of the spread spectrum signal, it can better adapt to the needs of the navigation equipment, optimize the system performance, improve the navigation accuracy and positioning accuracy, and enhance the user experience. Although different from the general civil code signal, the specific configuration of the spread spectrum signal still maintains compatibility with the Beidou navigation equipment, ensures the reception and demodulation of the new signal by the existing equipment, reduces the cost of equipment update and replacement, and improves the sustainable development capability of the system. By processing the information scrambling and encryption of the spread spectrum signal, the user's privacy information can be protected, sensitive data can be prevented from being illegally obtained or stolen, and the security of the system and the user's trust are improved.

[0014] Optionally, the frame header, time service week and seconds of the week carried by the message content are different from the frame header, time service week and seconds of the week used in the Beidou universal civil code signal.

[0015] In the present invention, by differentially designing the content of the telegram, especially optimizing key information such as the timing week and seconds in the week, the precision and accuracy of the timing information can be improved, ensuring that the time synchronization within the navigation device cluster is more stable and reliable. Customized design of key information such as frame header, timing week and seconds in the week helps to enhance the security of the system, prevent signal interference or malicious attacks from unknown sources, and ensure the normal operation of the navigation system. By optimizing the content of the telegram, the redundancy of data transmission can be reduced, the efficiency and speed of data transmission can be improved, and the time and energy consumption of signal processing by the navigation device can be reduced, thereby improving the overall performance of the system. Customized design of the content of the telegram according to actual needs can better adapt to navigation needs in different environments and application scenarios, improve the flexibility and adaptability of the system, and meet the diverse needs of users. By optimizing the content of the telegram, especially key information such as the timing week and seconds in the week, the positioning accuracy and navigation accuracy of the navigation device can be improved, the user experience and satisfaction can be improved, and the user's trust and loyalty to the navigation system can be enhanced.

[0016] Optionally, the spread spectrum signal includes a first spread spectrum signal and a second spread spectrum signal, the first spread spectrum signal includes a first priority spread spectrum signal and a second priority spread spectrum signal, and before S1, the following steps are also included:

[0017] S101, obtaining a spread spectrum signal action carrier and a spread spectrum signal action range through a mobile carrier, wherein the spread spectrum signal action carrier includes a first spread spectrum signal action carrier and a second spread spectrum signal action carrier, and importance of the first spread spectrum signal action carrier is greater than importance of the second spread spectrum signal action carrier;

[0018] S102, dividing the first spread spectrum signal action carrier to obtain a first priority action carrier and a second priority action carrier;

[0019] S103, generating a first information scrambling encryption strategy and a second information scrambling encryption strategy according to the first priority carrier and the second priority carrier to encrypt signals respectively, thereby sending a first priority spread spectrum signal to the first priority carrier, and sending a second priority spread spectrum signal to the second priority carrier;

[0020] S104: Generate a third information scrambling encryption strategy according to the second spread spectrum signal carrier to perform signal encryption, thereby sending the second spread spectrum signal to the second spread spectrum signal carrier.

[0021] In the present invention, the action carrier of the spread spectrum signal and the action range of the spread spectrum signal are obtained through a mobile carrier, and the carrier and coverage range can be flexibly selected according to actual conditions, thereby improving the coverage range and applicability of the system. The action carrier of the first spread spectrum signal is divided, and the corresponding information scrambling encryption strategy is generated, which helps to optimize resource allocation and improve the efficiency and performance of signal transmission. Through different scrambling encryption strategies, the security of the signal can be improved, the signal can be prevented from being illegally attacked or tampered with, and the reliability and stability of the system can be enhanced. According to the characteristics and importance of different carriers, different encryption strategies and sending methods can be adopted to optimize system performance and improve the overall performance and performance of the system. Optimizing the signal transmission method and encryption strategy can improve the positioning accuracy and navigation accuracy of the navigation equipment and enhance the user experience and satisfaction.

[0022] Optionally, S101 specifically includes:

[0023] S111: Acquire satellite signal orbit parameter data and antenna coverage data;

[0024] S112: Calculate the action range of the spread spectrum signal according to the satellite signal orbit parameter data and the antenna coverage data to obtain the action range of the spread spectrum signal;

[0025] S113: Generate a range map according to the action range of the spread spectrum signal to obtain a spread spectrum signal range map;

[0026] S114: marking the action carrier according to the spread spectrum signal range map to obtain a spread spectrum signal range marking map;

[0027] S115: Acquire an action carrier target, and generate a spread spectrum signal action carrier according to the action carrier target and the spread spectrum signal range annotation map.

[0028] In the present invention, by acquiring satellite signal orbit parameter data and antenna coverage data, and combining calculations, the scope of action of the spread spectrum signal can be accurately calculated to ensure the accuracy and reliability of the coverage. According to the calculated spread spectrum signal scope, a scope map is generated to intuitively display the coverage of the signal, providing a visual reference for subsequent steps. According to the spread spectrum signal range map, the action carrier is marked, and the spread spectrum signal action carrier can be clearly identified, which is helpful for subsequent signal transmission and data processing. By obtaining the action carrier target and combining the spread spectrum signal range marking map, the signal sending object can be accurately determined, ensuring the accurate transmission of the signal and improving the reliability and stability of the system. According to the scope map and the action carrier marking, resources can be reasonably allocated, the efficiency of signal transmission can be optimized, and the cost and resources of the system can be saved.

[0029] Optionally, S102 specifically includes:

[0030] S121: extracting features of the first spread spectrum signal action carrier to obtain first spread spectrum signal action carrier features, wherein the first spread spectrum signal action carrier features include action carrier coverage features, action carrier importance, action carrier device type, and action carrier communication link quality;

[0031] S122: performing clustering calculation on the carrier characteristics of the first spread spectrum signal to obtain carrier clustering characteristics;

[0032] S123: extracting the active carrier of the first spread spectrum signal according to the cluster center in the carrier clustering feature to obtain a pre-active carrier;

[0033] S124: performing signal quality estimation according to the pre-action carrier to obtain the pre-action carrier signal estimation quality;

[0034] S125: Divide the first spread spectrum signal action carriers according to the pre-action carrier signal estimated quality and carrier clustering feature data to obtain first priority action carriers and second priority action carriers.

[0035] In the present invention, by extracting features and performing cluster calculations on the features of the first spread spectrum signal action carrier, the action carrier with similar features can be accurately identified, and the pre-action carrier is extracted according to the cluster center, thereby ensuring the accurate identification and extraction of the action carrier. According to the pre-action carrier, the signal quality is estimated to obtain the pre-action carrier signal estimated quality, which can accurately evaluate the transmission quality and stability of the signal, and provide an important basis for the decision-making of subsequent steps. According to the pre-action carrier signal estimated quality and carrier clustering feature data, the first spread spectrum signal action carrier is divided to obtain the first priority action carrier and the second priority action carrier, which helps to optimize resource allocation and improve the efficiency and performance of signal transmission. Through accurate action carrier extraction and signal quality estimation, as well as optimized action carrier division, the performance and stability of the system can be improved, the transmission quality and reliability of the signal are ensured, and a more efficient and reliable solution is provided for the timing method of the Beidou navigation equipment cluster.

[0036] Optionally, the carrier clustering feature includes a first carrier clustering feature and a second carrier clustering feature, and S122 is specifically:

[0037] Performing complexity calculation on the carrier characteristic of the first spread spectrum signal to obtain characteristic complexity;

[0038] When it is determined that the feature complexity is less than a preset feature complexity threshold, a mean clustering calculation is performed on the first spread spectrum signal acting carrier feature to obtain a first carrier clustering feature;

[0039] When it is determined that the feature complexity is greater than or equal to a preset feature complexity threshold, a hierarchical clustering calculation is performed on the first spread spectrum signal carrier feature to obtain a second carrier clustering feature.

[0040] In the present invention, by calculating the complexity of the first spread spectrum signal action carrier feature and comprehensively considering the complexity of the feature, it is helpful to determine which clustering method is more suitable, thereby improving the flexibility and applicability of the clustering algorithm. According to the threshold of the feature complexity, the mean clustering or hierarchical clustering algorithm is selected, which can be flexibly adjusted according to specific circumstances, thereby ensuring the accuracy and stability of the clustering algorithm. According to the different feature complexities, the appropriate clustering algorithm is selected, which can better adapt to different types of data features and improve the accuracy and reliability of the clustering results. Through the comprehensive consideration of the feature complexity, the features of the action carrier can be better distinguished and extracted, providing an accurate basis for the extraction of the action carrier in the subsequent steps. The optimized clustering algorithm selection and the comprehensive consideration of the feature complexity can improve the performance and stability of the system, and provide a more efficient and reliable solution for the timing method of the Beidou navigation equipment cluster.

[0041] Optionally, S124 is specifically:

[0042] Extracting signal quality features and relative distance change features from the pre-action carrier to obtain signal quality features and relative distance change features;

[0043] The signal quality is estimated by using a preset signal quality estimation model based on the signal quality characteristics and the relative distance change characteristics to obtain the estimated quality of the pre-acting carrier signal;

[0044] The specific steps for constructing the preset signal quality prediction model are as follows:

[0045] Obtaining historical pre-action carriers and corresponding historical pre-action carrier signal estimated quality;

[0046] Signal quality feature extraction and relative distance change feature extraction are performed according to the historical pre-action carrier to obtain historical signal quality features and historical relative distance change features;

[0047] Perform feature fusion on historical signal quality features and historical relative distance change features to obtain signal fusion features;

[0048] Perform feature enhancement on the signal fusion feature to obtain the signal fusion enhanced feature;

[0049] Performing time series processing on the signal fusion enhancement features to obtain signal fusion time series features;

[0050] Perform convolution layer processing on the signal fusion time series features to obtain signal fusion convolution layer features;

[0051] Perform self-attention weighted calculation on the signal fusion convolutional layer features to obtain signal fusion weighted features;

[0052] Performing pooling layer processing on the signal fusion weighted features to obtain signal fusion pooling layer features;

[0053] Perform full connection calculation on the signal fusion pooling layer features to obtain the signal fusion full connection index;

[0054] Iterative training is performed based on the signal fusion full connection index and the estimated quality of the historical pre-action carrier signal to obtain a signal quality estimation model.

[0055] In the present invention, a signal quality prediction model is constructed by extracting signal quality features and relative distance change features from the pre-action carrier, and combining the historical pre-action carrier signal estimation quality. The model utilizes multiple features, and through complex steps such as feature fusion, enhancement, timing processing, convolution layer processing, self-attention weighted calculation, pooling layer processing and full connection calculation, it can more accurately estimate the signal quality, and improve the accuracy and stability of the prediction. The signal quality prediction model comprehensively considers the historical signal quality features, relative distance change features and other related features, and effectively combines these features through steps such as feature fusion and enhancement, making the model more comprehensive and accurate. By iterative training based on the signal fusion full connection index and the historical pre-action carrier signal estimation quality, the model parameters are continuously optimized and adjusted, so that the model can adapt to changes in different environments, and the robustness and generalization ability of the model are improved. Accurate signal quality prediction can provide important reference information for the system, help optimize the selection of action carriers and resource allocation, improve the performance and stability of the system, and provide a more reliable and efficient solution for the timing method of the Beidou navigation equipment cluster.

[0056] Optionally, the feature enhancement step is specifically as follows:

[0057] Perform feature gain on the signal fusion feature to obtain a signal fusion gain feature;

[0058] Performing feature transformation on the signal fusion gain feature to obtain a signal fusion transformation feature;

[0059] Performing auto-encoding feature reconstruction on the signal fusion transformation feature to obtain a first signal fusion reconstruction feature;

[0060] Generate an adversarial network on the signal fusion transformation feature to obtain a second signal fusion reconstruction feature;

[0061] Feature selection is performed on the first signal fusion reconstruction feature and the second signal fusion reconstruction feature to obtain a signal fusion enhancement feature.

[0062] The present invention can enhance the characterization ability and discrimination of features by performing gain processing on signal fusion features, thereby improving the quality and reliability of features. Gain processing can make features more prominent and accurately reflect the important characteristics of data, which is helpful to extract more valuable information. Feature transformation can map the original feature space to a new feature space that is more conducive to model learning, so that data can be more easily distinguished and classified in the new feature space, enhance the expression ability of features, and make it easier for the model to capture the inherent structure and law of data. By reconstructing features through autoencoders, feature representations with more potential information can be extracted from the original features. Autoencoders can learn the compressed representation of data, so that the reconstructed features can better reflect the essential characteristics of data, which helps to improve the characterization ability of features and the generalization ability of models. Features generated by adversarial networks can increase the diversity and richness of data, so that the model can learn the distribution characteristics of data more comprehensively. This feature generation can enhance the characterization ability of data sets and improve the robustness and generalization ability of models. By performing feature selection on the first signal fusion reconstruction feature and the second signal fusion reconstruction feature, the features that have the greatest impact on model performance can be screened out, the dimension of the feature space is reduced, and the training efficiency and generalization ability of the model are improved.

[0063] The purpose of the present invention is to quickly respond to the existence of a timing broadcast signal by detecting a spread spectrum signal and capturing it in real time, thereby ensuring that the time synchronization operation within a navigation device cluster can be performed in a timely manner. This real-time feature can ensure that the system's time information has a high degree of accuracy, which helps to improve the positioning accuracy and navigation performance of the navigation device.

[0064] Enhanced system stability: Using spread spectrum signals for time synchronization can effectively improve the stability and reliability of the system. The broadcast coverage of spread spectrum signals is wide, and can cover a large range of navigation equipment clusters, so that time synchronization operations can run stably in a variety of environments without being affected by external interference. Spread spectrum signals are used as timing broadcast signals, which have similar characteristics to Beidou universal civil code signals, but are different in terms of code initial phase, frame format, etc., thereby enhancing the adaptability of the system. This differentiated design can effectively meet the timing needs of different devices and scenarios, and improve the flexibility and applicability of the system. By demodulating and extracting time information from spread spectrum signals, the security and reliability of the time information extracted from the signal are ensured. At the same time, scrambling codes for deception are added to the content of the telegram, which further improves the security of the signal, prevents malicious attacks and data tampering, and ensures the safe operation of navigation equipment. This method can start the navigation equipment only when needed, avoiding energy waste in a long-term working state, thereby saving energy costs. In addition, real-time capture and processing of spread spectrum signals can effectively control the operating time and energy consumption of the system, and improve the energy efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting implementations made with reference to the following drawings:

[0066] Figure 1 A flowchart showing a method for cluster timing of navigation devices according to an embodiment is shown;

[0067] Figure 2 A schematic diagram of a specific implementation system of a navigation device cluster timing method according to an embodiment is shown;

[0068] Figure 3 A flowchart illustrating a specific implementation process of a navigation device cluster timing method according to an embodiment is shown;

[0069] Figure 4 A flowchart of a Beidou navigation device cluster timing method according to an embodiment is shown;

[0070] Figure 5 A flow chart showing the steps of a spread spectrum signal transmission method according to an embodiment is shown;

[0071] Figure 6 A flow chart showing a method for generating a spread spectrum signal carrier and range according to an embodiment of the present invention is provided;

[0072] Figure 7 A flowchart showing a method for dividing a first spread spectrum signal carrier according to an embodiment of the present invention is provided;

[0073] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0074] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0075] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0076] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0077] The present invention provides a Beidou navigation equipment cluster timing method. Based on the high-precision ranging characteristics of spread spectrum signals and utilizing the spread spectrum signal processing capability of existing navigation receivers, the navigation equipment is switched to a timing communication mode through soft switching, and real-time time transmission is performed within a distance of 100 kilometers. The timing error is less than 1 millisecond. The method provides a safe, reliable, and more accurate solution that is fully compatible with the existing Beidou navigation receiver hardware and software for fast and mobile timing of large-scale Beidou navigation equipment in a wartime environment.

[0078] like Figure 1 As shown, the technical solution provided by the present invention is as follows:

[0079] S10: When mobile carrier A synchronizes its time to BeiDou;

[0080] S11: A broadcasts the timing broadcast spread spectrum signal B with appropriate power to cover the area where the target navigation equipment cluster is located. The definition of spread spectrum signal B is consistent with the Beidou civil signal, only the code initial phase configuration is different, and the existing Beidou navigation equipment is fully compatible;

[0081] S21: The Beidou navigation device switches to the mobile timing mode, and the software automatically switches the initial phase of the code to the agreed spread spectrum code, which is consistent with the spread spectrum signal B;

[0082] S22: The navigation device detects the timing broadcast spread spectrum signal B in the mobile timing mode, and completes the capture and tracking of the signal B;

[0083] S23: Demodulate the timing information and message in signal B. The timing information consists of the code phase, code period, bit synchronization count, and frame synchronization count of the spread spectrum code, which is similar to the traditional navigation processing method. The frame header, timing week, and seconds in the week carried in the message are all added with scrambling codes that are different from the Beidou general civil signal to prevent deception;

[0084] S24: According to the time information extracted from signal B, the navigation equipment cluster in the coverage area of ​​signal B obtains the Beidou time with millisecond-level accuracy, and the timing is completed;

[0085] S25: The navigation device switches to navigation mode and captures the Beidou authorization signal;

[0086] The following is combined with the accompanying drawings in the embodiments of the present application ( Figure 2 , Figure 3 ), the technical solutions in the embodiments of the present application are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0087] like Figure 2 As shown in the schematic diagram of the specific implementation system of the method of the present invention, a Beidou navigation device cluster timing method of the present invention uses an unmanned aerial vehicle as a mobile carrier to cruise and provide timing over a cluster assembly area with a large number of Beidou navigation devices, and the coverage range can reach tens or even hundreds of kilometers.

[0088] like Figure 3 The specific implementation flow chart shown in the figure, the specific implementation steps of the navigation device cluster timing method of the present invention are as follows:

[0089] S010: The UAV synchronizes to Beidou time and then cruises over the target cluster (the UAV synchronizes to Beidou time and cruises within 1km altitude in the target time airspace);

[0090] S011: During the drone cruise, the timing broadcast spread spectrum signal B is broadcast to cover the 10-kilometer range where the target navigation equipment cluster is located. The definition of spread spectrum signal B is consistent with the Beidou civil signal, only the initial phase configuration of the code is different, and the existing Beidou navigation equipment is fully compatible;

[0091] S021: Beidou navigation equipment switches to mobile timing mode, and the software automatically switches the initial phase of the code to the agreed spread spectrum code, which is consistent with spread spectrum signal B;

[0092] S022: The navigation device detects the timing broadcast spread spectrum signal B in the maneuvering timing mode, and completes the capture and tracking of the signal B;

[0093] S023: Demodulate the timing information and message in signal B. The timing information consists of the code phase, code period, bit synchronization count, and frame synchronization count of the spread spectrum code, which is similar to the traditional navigation processing method. The frame header, timing week, and seconds in the week carried in the message are all added with scrambling codes that are different from the Beidou general civil signal to prevent deception;

[0094] S024: Based on the time information extracted from signal B, the navigation equipment cluster in the coverage area of ​​signal B obtains the Beidou time with millisecond-level accuracy, and the timing is completed;

[0095] S025: The navigation device switches to navigation mode and captures the Beidou authorization signal.

[0096] In the specific implementation step S010 of the present invention, the mobile carrier may be a communication vehicle or a helicopter, preferably a drone, which quickly flies to the target area without terrain restrictions after completing the timing of a single machine at the base;

[0097] In the specific implementation step S011 of the present invention, the timing broadcast spread spectrum signal B broadcast by the drone has the same signal characteristics and ranging code polynomial G1 / G2 as the Beidou B3I frequency point. The specific example is as follows:

[0098] Frequency: B3I

[0099] Code rate: 10.23MHZ

[0100] Code length: 10230 (cycle 1ms)

[0101] Ranging code G1: 13'h100d

[0102] Ranging code G2: 13'h1b71

[0103] The signal characteristics are the same as those of the Beidou B3I frequency, so that existing Beidou navigation receivers can receive the timing broadcast spread spectrum signal B without any modification.

[0104] In the specific implementation step S010 of the present invention, the timing broadcast spread spectrum signal B broadcast by the drone uses the Beidou B3I frequency point, which is only a preferred method of this example. As long as it is a universal Beidou frequency point supported by the existing Beidou navigation receiver, it can be selected.

[0105] In the specific implementation step S011 of the present invention, the timing broadcast spread spectrum signal B broadcast by the drone has a ranging code initial phase different from the Beidou B3I frequency point, and the modulation information is scrambled. The specific example is as follows:

[0106] Initial code phase 1: 13'h1fff

[0107] Code initial phase 2: 13'h1abc

[0108] Information rate: 100bps

[0109] Information content: Beidou time week count, seconds within the week

[0110] The information frame is 1 second long, each frame is 100 bits, the bit period is 10ms, and there are 10 periods of spread spectrum code in the bit.

[0111] Information scrambling code: 32'h2AB309BE

[0112] The specific implementation step S011 of the present invention, the timing broadcast spread spectrum signal B broadcast by the drone, the specific initial phase, information rate, information content and frame format, etc., are only a preferred method of this example. As long as it is the initial phase of the ranging code that does not overlap with the existing Beidou satellite in orbit, it can be selected; the information rate can also be 200bps, 50bps, etc.; the information content can also be UTC time, etc.; the information frame structure, information scrambling code, etc. can all be customized, or the information content can be encrypted to further prevent the enemy from cheating and interfering. One of the cores of the method of the present invention is to broadcast a timing broadcast spread spectrum signal B compatible with the current Beidou signal, so that the existing Beidou navigation receiver can implement the method described in the present invention without any hardware modification, only by upgrading the software. The definition of the specific timing broadcast spread spectrum signal B can be uniformly designed or dynamically generated based on the upper computer software, and the present invention does not limit it.

[0113] In the specific implementation step S021 described in the present invention, the Beidou navigation device switches to the mobile timing mode, and the software automatically switches the code initial phase to the agreed spread spectrum code, which is consistent with the spread spectrum signal B. After the Beidou navigation device is turned on, it enters the mobile timing mode through the user interface; or the software detects that the device has no valid timing, it automatically enters the mobile timing mode. After entering the mobile timing mode, the receiver reads the B3I ranging code defined by the code initial phase 1: 13'h1fff and the code initial phase 2: 13'h1abc from the preset timing broadcast configuration item to search;

[0114] In the specific implementation step S022 of the present invention, the receiver calls the same capture and tracking engine as the navigation ranging code to capture and track the ranging code in the timing broadcast spread spectrum signal B;

[0115] In the specific implementation step S023 of the present invention, the receiver software uses the information scrambling code 32'h2AB309BE to descramble and synchronize the message. The timing information and message carried in signal B, the timing information consists of the code phase, code period, bit synchronization count, and frame synchronization count of the spread spectrum code, which is similar to the traditional navigation processing method. The frame header, timing week, and seconds in the week carried in the message are all added with scrambling codes that are different from the Beidou general civil signal for anti-spoofing;

[0116] The specific implementation step S024 of the present invention can accurately determine the signal transmission time to the code phase level of the ranging code according to the time information extracted from signal B. In this embodiment, the B3I ranging code is used, the code rate is 10.23MHz, and the chip-level accuracy is 100ns. Since the distance from the UAV to the target navigation device is less than 100km, that is, the transmission delay of the transmitted signal is less than 1ms, the estimated error of the entire signal transmission time is within 1ms. That is, the navigation device cluster in the coverage area of ​​the timing broadcast spread spectrum signal B can obtain the Beidou time with millisecond accuracy, and the timing is completed. Taking into account the processing delay of the digital and analog circuits of the transmitting and receiving equipment and the software processing delay, the timing accuracy can be controlled within 10ms; if the B1I ranging code is used in actual application, the code rate is 1.023MHz, and the chip-level accuracy is also 1us, which has almost no effect on the timing accuracy.

[0117] In the specific implementation step S024 of the present invention, the timing accuracy is at the millisecond level, which is already a very high accuracy. When the Beidou navigation receiver captures the authorization signal, for higher robustness, a larger time search range is generally adopted - conventional wired timing or manual timing methods, the accuracy is often at the second level.

[0118] In the specific implementation step S025 of the present invention, the navigation device switches to the navigation mode to capture the Beidou authorization signal. After receiving the Beidou time in milliseconds in the timing mode, the navigation device software automatically switches to the navigation mode to capture the authorization signal.

[0119] See also Figures 4 to 7 The present application provides a Beidou navigation device cluster timing method, the method comprising:

[0120] S1. Start the navigation equipment in the Beidou navigation equipment cluster, put it in standby mode, and detect the spread spectrum signal to determine whether there is a timing broadcast signal;

[0121] S2. If a spread spectrum signal is detected, control the navigation device to capture the spread spectrum signal to obtain the spread spectrum signal;

[0122] S3, demodulating the spread spectrum signal to obtain signal content, wherein the signal content includes timing information and message content;

[0123] S4. Extract time information from the signal content to obtain time information, and perform time synchronization operations on each navigation device in the Beidou navigation device cluster based on the time information.

[0124] In the present invention, by capturing and demodulating the spread spectrum signal, time information can be extracted quickly and accurately, thereby achieving synchronization of the navigation device time and improving the consistency of the internal time of the navigation device cluster. The use of spread spectrum signals for time synchronization can reduce system errors, improve the positioning accuracy and navigation accuracy of the navigation device, and help improve the overall performance of the navigation system. By detecting the existence of the spread spectrum signal and demodulating the signal content, it is possible to timely detect and take measures when the signal is unstable or interfered, thereby enhancing the reliability and stability of the navigation system. The navigation device detects the spread spectrum signal in the standby state, and only performs subsequent operations when the signal is detected, which effectively saves energy consumption and extends the service life of the equipment. The use of spread spectrum signals compatible with the Beidou navigation system for time synchronization ensures the compatibility of the system with existing navigation equipment, avoids the cost of equipment replacement and updating, and improves the sustainable development capability of the system.

[0125] Optionally, the spread spectrum signal is sent via a mobile carrier, which includes an unmanned aerial vehicle, a car, a helicopter, and other carriers with mobility capabilities, and the spread spectrum signal is a time broadcast signal modulated by spread spectrum.

[0126] In the present invention, by utilizing mobile carriers, the coverage of timing broadcast signals can be expanded to a wider area, including various terrains such as cities, suburbs, and mountainous areas, thereby improving the coverage and applicability of navigation equipment. Mobile carriers have the characteristics of rapid deployment and mobility, and can adjust their positions and coverage at any time according to actual needs, flexibly respond to navigation needs in different regions, and improve the resilience and response speed of the system. Compared with traditional fixed base stations, the use of mobile carriers to send spread spectrum signals can reduce the cost of infrastructure construction, and does not require fixed installation equipment, saving manpower, material resources and maintenance costs. Mobile carriers are mobile and can adjust their positions and directions as needed, which helps to make up for blind spots that cannot be covered by fixed base stations, and improves the coverage robustness and stability of the system. Mobile carriers can select safe locations for deployment according to actual conditions to avoid being affected by factors such as severe weather, natural disasters or man-made damage, thereby improving the safety and reliability of the system.

[0127] Optionally, the code initial phase, frame format, information rate, information content, information scrambling encryption strategy and other contents related to the receiver software processing in the spread spectrum signal are different from the corresponding contents in the Beidou general civil code signal. The other contents related to the receiver software processing include data demodulation algorithm, bit error rate correction method, channel equalization processing, pseudo code tracking, pseudo code generation method, signal filtering strategy and receiver software update mechanism.

[0128] The present invention provides an embodiment in which the specific contents of the data demodulation algorithm, the bit error rate correction method, the channel equalization processing, the pseudo code tracking, the pseudo code generation method, the signal filtering strategy and the receiver software update mechanism are adjusted based on the code initial phase, the frame format, the information rate, the information content and the information scrambling encryption strategy in the spread spectrum signal, so that the present invention achieves the purpose of the contents related to the Beidou universal civil code signal.

[0129] The spread spectrum signal is demodulated using a binary phase shift keying (BPSK) data demodulation algorithm in the signal processing module of the receiver. The received spread spectrum signal is first filtered and then enters the demodulation module. The BPSK modulated signal is mixed with the local reference signal through a mixer to remove the carrier frequency and restore it to a baseband signal. After that, the baseband signal passes through the corresponding matched filter and timing recovery module to extract the symbol information and demodulate it into a binary data stream.

[0130] Convolutional codes in forward error correction (FEC) technology are used for bit error rate correction. After the received signal is demodulated, the convolutional code is decoded by a decoder (such as a Viterbi decoder) to correct the bit errors caused by noise and interference during the transmission process. The receiver determines the bit error by calculating the difference between the transmitted data and the expected data, and monitors the signal quality through the bit error rate (BER) calculation module, and feeds back to the receiving system to adjust the modulation and coding methods.

[0131] In a wireless channel environment with multipath propagation, an equalization algorithm (such as the LMS algorithm) is used to eliminate the multipath interference of the signal. After the received signal passes through the equalizer, the equalizer estimates the channel response and adjusts the gain and phase of each frequency component to eliminate the multipath effect. The receiver dynamically adjusts the equalizer parameters based on the channel state information (CSI) to restore the original signal.

[0132] Pseudo-code tracking uses a delay locked loop (DLL) to ensure that the receiver can accurately align the pseudo-random code (PRN) sequence. In the received spread spectrum signal, the phase of the local pseudo-code generator is adjusted by comparing the phase difference between the locally generated pseudo-code and the received pseudo-code. The tracking loop continuously adjusts to keep the local pseudo-code synchronized with the received pseudo-code, thereby ensuring the correctness of signal demodulation and decoding.

[0133] Pseudo-code generation uses linear feedback shift register (LFSR) technology to generate spread spectrum codes. Inside the receiver, by setting the initial state and feedback function of the LFSR, a pseudo-random code sequence (PRN sequence) is generated with a length of 1023 bits. The pseudo-code sequence is used to capture and despread the spread spectrum signal to ensure that the received signal can be correctly demodulated and tracked.

[0134] The receiver uses an adaptive bandpass filter (ABF) to suppress out-of-band interference signals. The received spread spectrum signal is roughly filtered through a wideband filter and then enters the adaptive bandpass filter. The ABF dynamically adjusts the bandwidth according to the real-time noise and signal spectrum to keep the signal within the desired frequency range and suppress external interference and noise to ensure the quality of the demodulated signal.

[0135] The embedded operating system in the receiver provides an OTA (Over-The-Air) software update mechanism. When a new software version is detected, the receiver downloads the update package through the wireless network and verifies it. The update package includes the new version of the demodulation algorithm, correction module, pseudo-code tracking algorithm, etc. The receiver automatically restarts after the update, loads the new software module and runs it to ensure real-time update of the receiver processing strategy and function optimization.

[0136] In the present invention, by configuring the spread spectrum signal specifically, including differentiated settings such as the initial phase of the code, information scrambling and encryption, the security and anti-interference ability of the signal can be improved, the signal can be prevented from being illegally tampered with or maliciously interfered, and the normal operation of the navigation system can be guaranteed. Compared with the general civil code signal, the differentiated configuration of the spread spectrum signal can reduce interference and interference between systems, improve the stability and reliability of the system, and reduce the possibility of errors. By adjusting the parameters such as the information rate and information content of the spread spectrum signal, it can better adapt to the needs of the navigation equipment, optimize the system performance, improve the navigation accuracy and positioning accuracy, and enhance the user experience. Although different from the general civil code signal, the specific configuration of the spread spectrum signal still maintains compatibility with the Beidou navigation equipment, ensures the reception and demodulation of the new signal by the existing equipment, reduces the cost of equipment update and replacement, and improves the sustainable development capability of the system. By processing the information scrambling and encryption of the spread spectrum signal, the user's privacy information can be protected, sensitive data can be prevented from being illegally obtained or stolen, and the security of the system and the user's trust are improved.

[0137] Optionally, the frame header, time service week and seconds of the week carried by the message content are different from the frame header, time service week and seconds of the week used in the Beidou universal civil code signal.

[0138] In the present invention, by differentially designing the content of the telegram, especially optimizing key information such as the timing week and seconds in the week, the precision and accuracy of the timing information can be improved, ensuring that the time synchronization within the navigation device cluster is more stable and reliable. Customized design of key information such as frame header, timing week and seconds in the week helps to enhance the security of the system, prevent signal interference or malicious attacks from unknown sources, and ensure the normal operation of the navigation system. By optimizing the content of the telegram, the redundancy of data transmission can be reduced, the efficiency and speed of data transmission can be improved, and the time and energy consumption of signal processing by the navigation device can be reduced, thereby improving the overall performance of the system. Customized design of the content of the telegram according to actual needs can better adapt to navigation needs in different environments and application scenarios, improve the flexibility and adaptability of the system, and meet the diverse needs of users. By optimizing the content of the telegram, especially key information such as the timing week and seconds in the week, the positioning accuracy and navigation accuracy of the navigation device can be improved, the user experience and satisfaction can be improved, and the user's trust and loyalty to the navigation system can be enhanced.

[0139] Optionally, the spread spectrum signal includes a first spread spectrum signal and a second spread spectrum signal, the first spread spectrum signal includes a first priority spread spectrum signal and a second priority spread spectrum signal, and before S1, the following steps are also included:

[0140] S101, obtaining a spread spectrum signal action carrier and a spread spectrum signal action range through a mobile carrier, wherein the spread spectrum signal action carrier includes a first spread spectrum signal action carrier and a second spread spectrum signal action carrier, and importance of the first spread spectrum signal action carrier is greater than importance of the second spread spectrum signal action carrier;

[0141] In one embodiment of the present invention, the parameter data of the satellite signal, such as position, strength, direction, etc., is obtained by an airborne sensor. Based on the satellite signal parameter data, the coverage of the satellite signal is calculated, and the effective range of the spread spectrum signal is determined. The type and location information of the carrier of the spread spectrum signal are identified, such as a drone, a car, a helicopter, etc.

[0142] S102, dividing the first spread spectrum signal action carrier to obtain a first priority action carrier and a second priority action carrier;

[0143] In one embodiment of the present invention, the spread spectrum signal action carriers are classified and divided into first priority action carriers and second priority action carriers according to the type and position of the spread spectrum signal action carriers.

[0144] S103, generating a first information scrambling encryption strategy and a second information scrambling encryption strategy according to the first priority carrier and the second priority carrier to encrypt signals respectively, thereby sending a first priority spread spectrum signal to the first priority carrier, and sending a second priority spread spectrum signal to the second priority carrier;

[0145] In one embodiment of the present invention, a suitable encryption algorithm is selected according to the type and security requirements of the carrier of the spread spectrum signal. An encryption algorithm based on a symmetric key is selected to encrypt the first priority spread spectrum signal and the second priority spread spectrum signal, wherein the complexity of the former is higher than the complexity of the latter, such as the former adopts a symmetric encryption algorithm based on a linear key, and the latter adopts a symmetric encryption algorithm based on graph encryption.

[0146] S104: Generate a third information scrambling encryption strategy according to the second spread spectrum signal carrier to perform signal encryption, thereby sending the second spread spectrum signal to the second spread spectrum signal carrier.

[0147] In one embodiment of the present invention, considering that the carrier of the second spread spectrum signal may be located in an area far from the signal source or with weak signal coverage, an encryption algorithm based on a symmetric key is selected to ensure signal security.

[0148] For the second spread spectrum signal, according to its relatively low complexity and low security requirements, a symmetric encryption algorithm with a lower computational complexity than the second information scrambling encryption strategy is selected for encryption. According to the characteristics of the second spread spectrum signal carrier and the selection of the encryption algorithm, a corresponding information scrambling encryption strategy is formulated, including determining the generation and management method of the encryption key, the parameter configuration of the encryption algorithm, etc. It is necessary to design an encryption strategy that can effectively protect the security of signal transmission according to specific security requirements and communication environment to ensure that the second spread spectrum signal is not easily eavesdropped or tampered with during transmission. Using the generated information scrambling encryption strategy, the second spread spectrum signal is encrypted, and the signal content and the encryption key are processed to generate encrypted signal data. The encryption operation needs to ensure the integrity and confidentiality of the signal, while minimizing the impact of the encryption operation on the signal transmission performance to ensure the timeliness and accuracy of the signal. The encrypted second spread spectrum signal is sent to the corresponding second spread spectrum signal carrier, ensuring that the signal can maintain its security and integrity during transmission even if it may be interfered with or eavesdropped.

[0149] In the present invention, the action carrier of the spread spectrum signal and the action range of the spread spectrum signal are obtained through a mobile carrier, and the carrier and coverage range can be flexibly selected according to actual conditions, thereby improving the coverage range and applicability of the system. The action carrier of the first spread spectrum signal is divided, and the corresponding information scrambling encryption strategy is generated, which helps to optimize resource allocation and improve the efficiency and performance of signal transmission. Through different scrambling encryption strategies, the security of the signal can be improved, the signal can be prevented from being illegally attacked or tampered with, and the reliability and stability of the system can be enhanced. According to the characteristics and importance of different carriers, different encryption strategies and sending methods can be adopted to optimize system performance and improve the overall performance and performance of the system. Optimizing the signal transmission method and encryption strategy can improve the positioning accuracy and navigation accuracy of the navigation equipment and enhance the user experience and satisfaction.

[0150] Optionally, S101 specifically includes:

[0151] S111: Acquire satellite signal orbit parameter data and antenna coverage data;

[0152] In one embodiment of the present invention, a satellite signal receiving device is used to obtain orbital parameter data of a satellite signal to obtain orbital parameters of a satellite, such as orbital altitude, inclination, ascending node longitude, etc. An antenna is placed at a specific location, and the signal strength within its coverage is recorded to generate antenna coverage data, including signal strength at different locations.

[0153] S112: Calculate the action range of the spread spectrum signal according to the satellite signal orbit parameter data and the antenna coverage data to obtain the action range of the spread spectrum signal;

[0154] In one embodiment of the present invention, satellite orbit parameters are analyzed to determine the orbit range, and the actual coverage range of the satellite signal is calculated in combination with antenna coverage range data to obtain a map of the actual coverage range of the satellite signal.

[0155] S113: Generate a range map according to the action range of the spread spectrum signal to obtain a spread spectrum signal range map;

[0156] In one embodiment of the present invention, GIS software or map data processing tools are used to generate a map based on the spread spectrum signal range data, and to generate a map layer based on the satellite signal range.

[0157] S114: marking the action carrier according to the spread spectrum signal range map to obtain a spread spectrum signal range marking map;

[0158] The present invention provides an embodiment in which an image processing algorithm is used to identify an effective carrier target in a spread spectrum signal range map. Carrier targets such as drones, vehicles, and airplanes in the map are identified. According to the identified carrier targets, the position and type of the effective carrier are marked on the map to obtain a spread spectrum signal range marked map.

[0159] S115: Acquire an action carrier target, and generate a spread spectrum signal action carrier according to the action carrier target and the spread spectrum signal range annotation map.

[0160] In one embodiment of the present invention, an effective carrier target is obtained through a preset target selection method, a software input interface or a manual input method (including a touch screen, keyboard input or other manual input methods), and a spread spectrum signal range map marked with the effective carrier is generated according to the effective carrier target and the spread spectrum signal range marking map.

[0161] Use equipment such as drones, satellites, or ground sensors to obtain the location and type of the action carrier. Obtain the target data of the action carrier, including location coordinates and type information. Match the acquired action carrier target data with the spread spectrum signal range annotation map. Generate spread spectrum signal action carrier data that matches the actual action carrier.

[0162] In the present invention, by acquiring satellite signal orbit parameter data and antenna coverage data, and combining calculations, the scope of action of the spread spectrum signal can be accurately calculated to ensure the accuracy and reliability of the coverage. According to the calculated spread spectrum signal scope, a scope map is generated to intuitively display the coverage of the signal, providing a visual reference for subsequent steps. According to the spread spectrum signal range map, the action carrier is marked, and the spread spectrum signal action carrier can be clearly identified, which is helpful for subsequent signal transmission and data processing. By obtaining the action carrier target and combining the spread spectrum signal range marking map, the signal sending object can be accurately determined, ensuring the accurate transmission of the signal and improving the reliability and stability of the system. According to the scope map and the action carrier marking, resources can be reasonably allocated, the efficiency of signal transmission can be optimized, and the cost and resources of the system can be saved.

[0163] Optionally, S102 specifically includes:

[0164] S121: extracting features of the first spread spectrum signal action carrier to obtain first spread spectrum signal action carrier features, wherein the first spread spectrum signal action carrier features include action carrier coverage features, action carrier importance, action carrier device type, and action carrier communication link quality;

[0165] The present invention provides, in one embodiment, a coverage feature of a function carrier, for each spread spectrum signal function carrier, by measuring its signal coverage, determining its influence range and expressing it quantitatively. Function carrier importance, evaluating and ranking the function carrier according to its importance in the entire navigation system to determine its priority in the time synchronization operation. Function carrier device type, identifying and recording the device type of the function carrier, such as drones, cars, ships, etc., for subsequent function carrier management and allocation. Function carrier communication link quality, evaluating the communication link quality between the function carrier and the navigation device, including indicators such as signal strength and signal-to-noise ratio, to ensure a stable communication connection.

[0166] S122: performing clustering calculation on the carrier characteristics of the first spread spectrum signal to obtain carrier clustering characteristics;

[0167] In one embodiment provided by the present invention, a clustering algorithm (such as K-means clustering, hierarchical clustering, etc.) is used to calculate and analyze the extracted features to identify groups of action carriers with similar features and determine cluster centers.

[0168] S123: extracting the active carrier of the first spread spectrum signal according to the cluster center in the carrier clustering feature to obtain a pre-active carrier;

[0169] In one embodiment provided by the present invention, based on the clustering result, the action carriers with similar characteristics are divided into the same group, and the cluster center of each group is determined as the pre-action carrier.

[0170] S124: performing signal quality estimation according to the pre-action carrier to obtain the pre-action carrier signal estimation quality;

[0171] The present invention provides an embodiment in which a deep learning algorithm (such as a neural network algorithm, specifically, as shown in other embodiments of the present invention) is used to estimate the signal quality of a pre-action carrier based on its characteristics and historical data to evaluate its performance and reliability in time synchronization operations.

[0172] S125: Divide the first spread spectrum signal action carriers according to the pre-action carrier signal estimated quality and carrier clustering feature data to obtain first priority action carriers and second priority action carriers.

[0173] The present invention provides an embodiment in which the first priority and second priority carriers are determined according to the predicted signal quality and clustering results, so as to allocate and manage resources in subsequent time synchronization operations. The signal quality of the pre-action carrier is evaluated, and the pre-action carrier is divided into different quality levels, such as high quality, good, general, poor, etc. according to the predicted signal quality value. According to actual needs and resource allocation strategies (such as the estimated quality of the pre-action carrier signal is good and the corresponding number of carriers is more), it is determined which quality levels of pre-action carriers will be classified as first priority carriers and which will be classified as second priority carriers. The characteristics of the pre-action carriers are clustered using a clustering algorithm, and the pre-action carriers with similar characteristics are classified into the same category. The clustering results are analyzed, and according to the characteristics of the number of pre-action carriers in each cluster cluster, the coverage range, the quality of the communication link, etc., it is determined which cluster clusters will be classified as first priority carriers and which will be classified as second priority carriers. The signal quality prediction results and the carrier clustering characteristics are combined (calculated using a weighted calculation formula), and the signal quality and carrier distribution are comprehensively considered. Design weighing factors or priorities (provide preset weights) and adjust the weights of the signal quality prediction results and clustering characteristics on the action carriers according to actual conditions to determine the first and second priority action carriers.

[0174] In the present invention, by extracting features and performing cluster calculations on the features of the first spread spectrum signal action carrier, the action carrier with similar features can be accurately identified, and the pre-action carrier is extracted according to the cluster center, thereby ensuring the accurate identification and extraction of the action carrier. According to the pre-action carrier, the signal quality is estimated to obtain the pre-action carrier signal estimated quality, which can accurately evaluate the transmission quality and stability of the signal, and provide an important basis for the decision-making of subsequent steps. According to the pre-action carrier signal estimated quality and carrier clustering feature data, the first spread spectrum signal action carrier is divided to obtain the first priority action carrier and the second priority action carrier, which helps to optimize resource allocation and improve the efficiency and performance of signal transmission. Through accurate action carrier extraction and signal quality estimation, as well as optimized action carrier division, the performance and stability of the system can be improved, the transmission quality and reliability of the signal are ensured, and a more efficient and reliable solution is provided for the timing method of the Beidou navigation equipment cluster.

[0175] Optionally, the carrier clustering feature includes a first carrier clustering feature and a second carrier clustering feature, and S122 is specifically:

[0176] Performing complexity calculation on the carrier characteristic of the first spread spectrum signal to obtain characteristic complexity;

[0177] The present invention provides an embodiment in which methods such as entropy and conditional entropy in information theory are used to perform complexity calculation on the characteristics of the carrier of the first spread spectrum signal.

[0178] When it is determined that the feature complexity is less than a preset feature complexity threshold, a mean clustering calculation is performed on the first spread spectrum signal acting carrier feature to obtain a first carrier clustering feature;

[0179] In one embodiment provided by the present invention, a K-means clustering algorithm is used to perform clustering calculation on the characteristics of the first spread spectrum signal action carrier to generate first carrier clustering characteristics, including a clustering center and a cluster cluster to which each action carrier belongs.

[0180] When it is determined that the feature complexity is greater than or equal to a preset feature complexity threshold, a hierarchical clustering calculation is performed on the first spread spectrum signal carrier feature to obtain a second carrier clustering feature.

[0181] In one embodiment of the present invention, a hierarchical clustering algorithm (such as top-down agglomerative clustering or bottom-up divisive clustering) is used to perform hierarchical clustering calculations on the characteristics of the first spread spectrum signal carrier to generate second carrier clustering characteristics, including a clustering tree or a cluster division result of the hierarchical clustering.

[0182] In the present invention, by calculating the complexity of the first spread spectrum signal action carrier feature and comprehensively considering the complexity of the feature, it is helpful to determine which clustering method is more suitable, thereby improving the flexibility and applicability of the clustering algorithm. According to the threshold of the feature complexity, the mean clustering or hierarchical clustering algorithm is selected, which can be flexibly adjusted according to specific circumstances, thereby ensuring the accuracy and stability of the clustering algorithm. According to the different feature complexities, the appropriate clustering algorithm is selected, which can better adapt to different types of data features and improve the accuracy and reliability of the clustering results. Through the comprehensive consideration of the feature complexity, the features of the action carrier can be better distinguished and extracted, providing an accurate basis for the extraction of the action carrier in the subsequent steps. The optimized clustering algorithm selection and the comprehensive consideration of the feature complexity can improve the performance and stability of the system, and provide a more efficient and reliable solution for the timing method of the Beidou navigation equipment cluster.

[0183] Optionally, S124 is specifically:

[0184] Extracting signal quality features and relative distance change features from the pre-action carrier to obtain signal quality features and relative distance change features;

[0185] The signal quality is estimated by using a preset signal quality estimation model based on the signal quality characteristics and the relative distance change characteristics to obtain the estimated quality of the pre-acting carrier signal;

[0186] The specific steps for constructing the preset signal quality prediction model are as follows:

[0187] Obtaining historical pre-action carriers and corresponding historical pre-action carrier signal estimated quality;

[0188] The present invention provides an embodiment in which information on historical pre-action carriers and corresponding estimated quality data are queried and extracted from a database recording historical data.

[0189] Signal quality feature extraction and relative distance change feature extraction are performed according to the historical pre-action carrier to obtain historical signal quality features and historical relative distance change features;

[0190] The present invention provides an embodiment in which signal processing and feature engineering techniques are used to process signal data of historical pre-action carriers to extract signal quality features and relative distance change features.

[0191] Perform feature fusion on historical signal quality features and historical relative distance change features to obtain signal fusion features;

[0192] In one embodiment provided by the present invention, feature fusion technology (such as principal component analysis, factor analysis, etc.) is used to fuse historical signal quality features and historical relative distance change features into a comprehensive signal fusion feature.

[0193] Perform feature enhancement on the signal fusion feature to obtain the signal fusion enhanced feature;

[0194] In one embodiment provided by the present invention, feature gain processing is performed on the signal fusion features, such as adding high-order statistical features, nonlinear transformation features, etc., to enhance the distinguishability and characterization ability of the features.

[0195] Performing time series processing on the signal fusion enhancement features to obtain signal fusion time series features;

[0196] In one embodiment of the present invention, the enhanced features are subjected to time series processing, for example, using a sliding window or a time series model to capture the time correlation of the signal data.

[0197] Perform convolution layer processing on the signal fusion time series features to obtain signal fusion convolution layer features;

[0198] In one embodiment of the present invention, a convolution operation (maximum value convolution layer, minimum value convolution layer, average value convolution layer or Gaussian convolution layer) is performed on the time series features to extract the relationship between the local features and the time series features.

[0199] Perform self-attention weighted calculation on the signal fusion convolutional layer features to obtain signal fusion weighted features;

[0200] The present invention provides an embodiment in which a self-attention mechanism (convolution calculation, activation layer calculation, pooling layer calculation, weighted calculation and feature concatenation) is used to perform weighted calculation on convolution layer features to enhance the importance of different time steps.

[0201] Performing pooling layer processing on the signal fusion weighted features to obtain signal fusion pooling layer features;

[0202] In one embodiment provided by the present invention, a pooling layer (a maximum pooling layer, a minimum pooling layer, an average pooling layer) is used to perform dimensionality reduction processing on weighted features to reduce feature dimensions and the amount of calculation.

[0203] Perform full connection calculation on the signal fusion pooling layer features to obtain the signal fusion full connection index;

[0204] In one embodiment provided by the present invention, a fully connected layer neural network is applied to perform fully connected calculations on pooling layer features to obtain a signal fusion fully connected index.

[0205] Iterative training is performed based on the signal fusion full connection index and the estimated quality of the historical pre-action carrier signal to obtain a signal quality estimation model.

[0206] In one embodiment of the present invention, the signal quality prediction model is trained using the full connection index and the historical pre-action carrier signal prediction quality data, for example, using the gradient descent method or the Adam optimization algorithm for model training, or using the mean square error loss function or the mean absolute error loss function for model training.

[0207] In the present invention, a signal quality prediction model is constructed by extracting signal quality features and relative distance change features from the pre-action carrier, and combining the historical pre-action carrier signal estimation quality. The model utilizes multiple features, and through complex steps such as feature fusion, enhancement, timing processing, convolution layer processing, self-attention weighted calculation, pooling layer processing and full connection calculation, it can more accurately estimate the signal quality, and improve the accuracy and stability of the prediction. The signal quality prediction model comprehensively considers the historical signal quality features, relative distance change features and other related features, and effectively combines these features through steps such as feature fusion and enhancement, making the model more comprehensive and accurate. By iterative training based on the signal fusion full connection index and the historical pre-action carrier signal estimation quality, the model parameters are continuously optimized and adjusted, so that the model can adapt to changes in different environments, and the robustness and generalization ability of the model are improved. Accurate signal quality prediction can provide important reference information for the system, help optimize the selection of action carriers and resource allocation, improve the performance and stability of the system, and provide a more reliable and efficient solution for the timing method of the Beidou navigation equipment cluster.

[0208] Optionally, the feature enhancement step is specifically as follows:

[0209] Perform feature gain on the signal fusion feature to obtain a signal fusion gain feature;

[0210] In one embodiment of the present invention, a gain factor or a weight is used to amplify or reduce the signal fusion feature to enhance the distinguishability and characterization ability of the feature. For the signal fusion feature vector [0.2, 0.4, 0.6, 0.8], a gain factor of 2 can be used to amplify the feature vector to [0.4, 0.8, 1.2, 1.6].

[0211] Performing feature transformation on the signal fusion gain feature to obtain a signal fusion transformation feature;

[0212] In one embodiment of the present invention, a linear transformation, a nonlinear transformation or other transformation method is used to transform the signal fusion gain feature to extract a new feature representation. For the signal fusion gain feature vector [0.4, 0.8, 1.2, 1.6], a square transformation can be performed to obtain a new feature vector [0.16, 0.64, 1.44, 2.56].

[0213] Performing auto-encoding feature reconstruction on the signal fusion transformation feature to obtain a first signal fusion reconstruction feature;

[0214] The present invention provides an embodiment in which an autoencoder model is used to encode and decode signal fusion transformation features to reconstruct the original features and learn higher-order feature representations. An autoencoder model is trained to encode the signal fusion transformation features into a low-dimensional space representation, and then decoded to restore the original features.

[0215] Generate an adversarial network on the signal fusion transformation feature to obtain a second signal fusion reconstruction feature;

[0216] The present invention provides an embodiment in which a new signal fusion transformation feature is generated using a generative adversarial network (GAN) model, so that the generated feature is difficult to distinguish from the real feature, thereby extracting more representative features. A generator and a discriminator are trained so that the generator can generate fake features similar to the real signal fusion transformation features, and the discriminator cannot distinguish between the real and fake features.

[0217] Feature selection is performed on the first signal fusion reconstruction feature and the second signal fusion reconstruction feature to obtain a signal fusion enhancement feature.

[0218] In one embodiment of the present invention, a feature selection algorithm (such as L1 regularization, variance threshold, etc.) is used to select the first signal fusion reconstruction feature and the second signal fusion reconstruction feature to screen out the most representative features. Using the L1 regularization method, by adjusting the regularization parameter, the feature with a higher weight in the reconstruction feature is selected as the final signal fusion enhancement feature.

[0219] The present invention can enhance the characterization ability and discrimination of features by performing gain processing on signal fusion features, thereby improving the quality and reliability of features. Gain processing can make features more prominent and accurately reflect the important characteristics of data, which is helpful to extract more valuable information. Feature transformation can map the original feature space to a new feature space that is more conducive to model learning, so that data can be more easily distinguished and classified in the new feature space, enhance the expression ability of features, and make it easier for the model to capture the inherent structure and law of data. By reconstructing features through autoencoders, feature representations with more potential information can be extracted from the original features. Autoencoders can learn the compressed representation of data, so that the reconstructed features can better reflect the essential characteristics of data, which helps to improve the characterization ability of features and the generalization ability of models. Features generated by adversarial networks can increase the diversity and richness of data, so that the model can learn the distribution characteristics of data more comprehensively. This feature generation can enhance the characterization ability of data sets and improve the robustness and generalization ability of models. By performing feature selection on the first signal fusion reconstruction feature and the second signal fusion reconstruction feature, the features that have the greatest impact on model performance can be screened out, the dimension of the feature space is reduced, and the training efficiency and generalization ability of the model are improved.

[0220] The purpose of the present invention is to quickly respond to the existence of a timing broadcast signal by detecting a spread spectrum signal and capturing it in real time, thereby ensuring that the time synchronization operation within a navigation device cluster can be performed in a timely manner. This real-time feature can ensure that the system's time information has a high degree of accuracy, which helps to improve the positioning accuracy and navigation performance of the navigation device.

[0221] Enhanced system stability: Using spread spectrum signals for time synchronization can effectively improve the stability and reliability of the system. The broadcast coverage of spread spectrum signals is wide, and can cover a large range of navigation equipment clusters, so that time synchronization operations can run stably in a variety of environments without being affected by external interference. Spread spectrum signals are used as timing broadcast signals, which have similar characteristics to Beidou universal civil code signals, but are different in terms of code initial phase, frame format, etc., thereby enhancing the adaptability of the system. This differentiated design can effectively meet the timing needs of different devices and scenarios, and improve the flexibility and applicability of the system. By demodulating and extracting time information from spread spectrum signals, the security and reliability of the time information extracted from the signal are ensured. At the same time, scrambling codes for deception are added to the content of the telegram, which further improves the security of the signal, prevents malicious attacks and data tampering, and ensures the safe operation of navigation equipment. This method can start the navigation equipment only when needed, avoiding energy waste in a long-term working state, thereby saving energy costs. In addition, real-time capture and processing of spread spectrum signals can effectively control the operating time and energy consumption of the system, and improve the energy efficiency of the system.

[0222] Therefore, from any point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the attached application documents rather than the above description, and it is intended that all changes falling within the meaning and scope of equivalent elements of the application documents are included in the present invention.

[0223] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A Beidou navigation equipment cluster timing method, characterized in that: The method comprises: S1. Start the navigation equipment in the Beidou navigation equipment cluster, put it in standby mode, and detect the spread spectrum signal to determine whether there is a timing broadcast signal; S2. If a spread spectrum signal is detected, control the navigation device to capture the spread spectrum signal to obtain the spread spectrum signal; S3, demodulating the spread spectrum signal to obtain signal content, wherein the signal content includes timing information and message content; S4, extracting time information from the signal content to obtain time information, and performing time synchronization operations on each navigation device in the Beidou navigation device cluster according to the time information; The spread spectrum signal includes a first spread spectrum signal and a second spread spectrum signal, the first spread spectrum signal includes a first priority spread spectrum signal and a second priority spread spectrum signal, and before S1, the following steps are also included: S101, obtaining a spread spectrum signal action carrier and a spread spectrum signal action range through a mobile carrier, wherein the spread spectrum signal action carrier includes a first spread spectrum signal action carrier and a second spread spectrum signal action carrier, and importance of the first spread spectrum signal action carrier is greater than importance of the second spread spectrum signal action carrier; S102, dividing the first spread spectrum signal action carrier to obtain a first priority action carrier and a second priority action carrier; S103, generating a first information scrambling encryption strategy and a second information scrambling encryption strategy according to the first priority carrier and the second priority carrier to encrypt signals respectively, thereby sending a first priority spread spectrum signal to the first priority carrier, and sending a second priority spread spectrum signal to the second priority carrier; S104: Generate a third information scrambling encryption strategy according to the second spread spectrum signal carrier to perform signal encryption, thereby sending the second spread spectrum signal to the second spread spectrum signal carrier.

2. The method according to claim 1, characterized in that The spread spectrum signal is sent through a mobile carrier, and the spread spectrum signal is a time broadcast signal modulated by spread spectrum.

3. The method according to claim 2, characterized in that The code initial phase, frame format, information rate, information content, information scrambling and encryption strategy in the spread spectrum signal and other contents related to the receiver software processing are different from the corresponding contents in the Beidou general civil code signal. The other contents related to the receiver software processing include data demodulation algorithm, bit error rate correction method, channel equalization processing, pseudo code tracking, pseudo code generation method, signal filtering strategy and receiver software update mechanism.

4. The method according to claim 1, characterized in that: The frame header, time period and seconds of the week carried in the message content are different from those used in the Beidou universal civil code signal.

5. The method according to claim 1, characterized in that S101 is as follows: S111: Acquire satellite signal orbit parameter data and antenna coverage data; S112: Calculate the action range of the spread spectrum signal according to the satellite signal orbit parameter data and the antenna coverage data to obtain the action range of the spread spectrum signal; S113: Generate a range map according to the action range of the spread spectrum signal to obtain a spread spectrum signal range map; S114: marking the action carrier according to the spread spectrum signal range map to obtain a spread spectrum signal range marking map; S115: Acquire an action carrier target, and generate a spread spectrum signal action carrier according to the action carrier target and the spread spectrum signal range annotation map.

6. The method according to claim 1, characterized in that S102 is specifically: S121: extracting features of the first spread spectrum signal action carrier to obtain first spread spectrum signal action carrier features, wherein the first spread spectrum signal action carrier features include action carrier coverage features, action carrier importance, action carrier device type, and action carrier communication link quality; S122: performing clustering calculation on the carrier characteristics of the first spread spectrum signal to obtain carrier clustering characteristics; S123: extracting the active carrier of the first spread spectrum signal according to the cluster center in the carrier clustering feature to obtain a pre-active carrier; S124: performing signal quality estimation according to the pre-action carrier to obtain the pre-action carrier signal estimation quality; S125: Divide the first spread spectrum signal action carriers according to the pre-action carrier signal estimated quality and carrier clustering feature data to obtain first priority action carriers and second priority action carriers.

7. The method according to claim 6, characterized in that The carrier clustering feature includes a first carrier clustering feature and a second carrier clustering feature, and S122 is specifically: Performing complexity calculation on the carrier characteristic of the first spread spectrum signal to obtain characteristic complexity; When it is determined that the feature complexity is less than a preset feature complexity threshold, a mean clustering calculation is performed on the first spread spectrum signal acting carrier feature to obtain a first carrier clustering feature; When it is determined that the feature complexity is greater than or equal to a preset feature complexity threshold, a hierarchical clustering calculation is performed on the first spread spectrum signal carrier feature to obtain a second carrier clustering feature.

8. The method according to claim 6, characterized in that S124 is specifically: Extracting signal quality features and relative distance change features from the pre-action carrier to obtain signal quality features and relative distance change features; The signal quality is estimated by using a preset signal quality estimation model based on the signal quality characteristics and the relative distance change characteristics to obtain the estimated quality of the pre-acting carrier signal; The specific steps for constructing the preset signal quality prediction model are as follows: Obtaining historical pre-action carriers and corresponding historical pre-action carrier signal estimated quality; Signal quality feature extraction and relative distance change feature extraction are performed according to the historical pre-action carrier to obtain historical signal quality features and historical relative distance change features; Perform feature fusion on historical signal quality features and historical relative distance change features to obtain signal fusion features; Perform feature enhancement on the signal fusion feature to obtain the signal fusion enhanced feature; Performing time series processing on the signal fusion enhancement features to obtain signal fusion time series features; Perform convolution layer processing on the signal fusion time series features to obtain signal fusion convolution layer features; Perform self-attention weighted calculation on the signal fusion convolutional layer features to obtain signal fusion weighted features; Performing pooling layer processing on the signal fusion weighted features to obtain signal fusion pooling layer features; Perform full connection calculation on the signal fusion pooling layer features to obtain the signal fusion full connection index; Iterative training is performed based on the signal fusion full connection index and the estimated quality of the historical pre-action carrier signal to obtain a signal quality estimation model.

9. The method according to claim 8, characterized in that Features The specific steps of enhancement are: Perform feature gain on the signal fusion feature to obtain a signal fusion gain feature; Performing feature transformation on the signal fusion gain feature to obtain a signal fusion transformation feature; Performing auto-encoding feature reconstruction on the signal fusion transformation feature to obtain a first signal fusion reconstruction feature; Generate an adversarial network on the signal fusion transformation feature to obtain a second signal fusion reconstruction feature; Feature selection is performed on the first signal fusion reconstruction feature and the second signal fusion reconstruction feature to obtain a signal fusion enhancement feature.

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