Beidou communication method and system in electromagnetic suppression scene

Abstract

The invention belongs to the technical field of satellite communication, and discloses a Beidou communication method and system in an electromagnetic suppression scene. The method comprises the following steps: firstly, sensing an electromagnetic environment around the Beidou terminal equipment; whether electromagnetic suppression interference exists in the electromagnetic environment is judged from the energy domain and the time-frequency domain, and whether the current communication scene is an electromagnetic suppression scene or a common communication scene is judged; if it is judged that the current communication scene is the electromagnetic suppression scene, feature extraction and analysis are carried out on electromagnetic suppression interference, and the type of the electromagnetic suppression interference is further judged; secondly, countering the type of electromagnetic suppression interference; and finally, adjusting Beidou communication configuration according to the current communication scene and completing Beidou communication. According to the Beidou communication method provided by the invention, the Beidou terminal equipment can accurately judge whether electromagnetic suppression exists in the surrounding environment or not, and counteracts and adjusts the Beidou communication configuration in time in an electromagnetic suppression scene, so that the communication quality and the system stability are ensured, and the accuracy and the reliability of Beidou communication are improved.

Description

Technical Field

[0001] The present invention belongs to the field of satellite communication technology, and in particular relates to a Beidou communication method and system under electromagnetic suppression scenarios. Background Art

[0002] The Global Navigation Satellite System (GNSS) boasts unique advantages such as all-weather coverage, wide coverage, and high positioning accuracy, and has become an indispensable infrastructure for the modern information society. The BeiDou Navigation Satellite System, a global satellite navigation system independently developed by my country, is now operational and operating stably. The system provides navigation, positioning, timing, and communication services to users worldwide and is widely used in key areas such as transportation, agricultural production, and emergency rescue.

[0003] However, with the widespread adoption and in-depth application of the Beidou navigation system, external challenges are becoming increasingly prominent. In particular, navigation countermeasures have become a potential threat that cannot be ignored. Electromagnetic interference, a common method of interference in navigation countermeasures, involves transmitting high-power electromagnetic waves. These waves overwhelm the receiver's operating frequency band, degrading signal reception quality and making it difficult for the receiver to extract valid information from the noise. This, in turn, impacts the normal operation of devices that rely on GNSS for communication and navigation services. In particular, strong electromagnetic interference scenarios can render various devices using the Beidou satellite navigation system inoperable, severely impacting the accuracy and reliability of Beidou communications.

[0004] Therefore, studying a communication method that can effectively resist electromagnetic suppression interference and ensure stable and reliable Beidou communication quality in electromagnetic suppression scenarios has become a technical problem that needs to be solved urgently. Summary of the Invention

[0005] The purpose of the present invention is to propose a Beidou communication method under electromagnetic suppression scenarios, which can timely counter and adjust the Beidou communication configuration for electromagnetic suppression scenarios, ensure the communication quality of Beidou terminal equipment, and improve the accuracy and reliability of Beidou communication.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

[0007] A BeiDou communication method in an electromagnetic suppression scenario includes the following steps:

[0008] Step 1. Sense the electromagnetic environment around the Beidou terminal device;

[0009] Step 2. Determine whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain;

[0010] If electromagnetic suppression interference exists in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process goes to step 3; if electromagnetic suppression interference does not exist in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process goes to step 5;

[0011] Step 3. Separate the electromagnetic suppression interference from the mixed signal of the electromagnetic environment, and extract the features of the electromagnetic suppression interference to determine the type of the electromagnetic suppression interference;

[0012] Step 4. Countermeasures against the type of electromagnetic suppression interference;

[0013] Step 5. Adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

[0014] In addition, based on the Beidou communication method in the electromagnetic suppression scenario, the present invention also proposes a Beidou communication system in the electromagnetic suppression scenario adapted thereto, which adopts the following technical solutions:

[0015] A BeiDou communication system for electromagnetic suppression scenarios includes the following modules:

[0016] Environmental perception module, used to perceive the electromagnetic environment around Beidou terminal equipment;

[0017] The scene judgment module is used to judge whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain;

[0018] If there is electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process is switched to the countermeasure adjustment module. If there is no electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process is switched to the Beidou communication module.

[0019] The countermeasure adjustment module is used to separate electromagnetic suppression interference from the mixed signals of the electromagnetic environment and extract the characteristics of the electromagnetic suppression interference, so as to determine the type of electromagnetic suppression interference and take countermeasures according to the type of electromagnetic suppression interference;

[0020] The Beidou communication module is used to adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

[0021] In addition, based on the above-mentioned Beidou communication method in the electromagnetic suppression scenario, the present invention also proposes a computer device, which includes a memory and one or more processors;

[0022] The memory stores executable code, and when the processor executes the executable code, it is used to implement the steps of the Beidou communication method in the electromagnetic suppression scenario mentioned above.

[0023] In addition, based on the above-mentioned Beidou communication method under electromagnetic suppression scenario, the present invention also proposes a computer-readable storage medium on which a program is stored; when the program is executed by the processor, it is used to implement the steps of the Beidou communication method under electromagnetic suppression scenario mentioned above.

[0024] The present invention has the following advantages:

[0025] As described above, the present invention relates to a Beidou communication method in an electromagnetic suppression scenario. The method first senses the electromagnetic environment around the Beidou terminal device; then determines whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain, and then determines whether the current communication scenario is an electromagnetic suppression scenario or a normal communication scenario; if the current communication scenario is determined to be an electromagnetic suppression scenario, the electromagnetic suppression interference is feature extracted and analyzed, and the type of electromagnetic suppression interference is determined, and then countermeasures are taken for the type of electromagnetic suppression interference; finally, the Beidou communication configuration is adjusted according to the current communication scenario and the Beidou communication is completed. The method of the present invention adopts a comprehensive judgment method of the energy domain and the time-frequency domain, which reduces the misjudgment of electromagnetic suppression interference by a single energy threshold detection and improves the accuracy of electromagnetic suppression interference detection in the electromagnetic environment; in addition, the method of the present invention achieves accurate classification of electromagnetic suppression interference by extracting features of electromagnetic suppression interference, and can take corresponding countermeasures in a targeted manner and adaptively adjust communication parameters to meet the high-reliability communication requirements in complex electromagnetic environments. The method of the present invention enables Beidou terminal equipment to accurately judge whether there is electromagnetic suppression in the surrounding environment, and to take timely countermeasures in the electromagnetic suppression scenario and adjust the Beidou communication configuration, thereby ensuring communication quality and system stability and improving the accuracy and reliability of Beidou communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of the Beidou communication method in an electromagnetic suppression scenario in an embodiment of the present invention.

[0027] Figure 2 This is an architectural diagram of the Beidou communication method in an electromagnetic suppression scenario in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0029] Example 1

[0030] This embodiment proposes a Beidou communication method for an electromagnetic suppression scenario. The method first senses the electromagnetic environment surrounding the Beidou terminal device. It then determines whether electromagnetic suppression interference exists in the electromagnetic environment, thereby determining whether the current communication scenario is an electromagnetic suppression scenario or a normal communication scenario. If the current communication scenario is determined to be an electromagnetic suppression scenario, the electromagnetic suppression interference features in the electromagnetic suppression scenario are extracted and analyzed. Next, countermeasures are taken against the results of the electromagnetic suppression interference feature extraction and analysis, and the Beidou communication configuration is adjusted to the communication configuration for the electromagnetic suppression scenario. Finally, Beidou communication in the electromagnetic suppression scenario is completed. The Beidou communication method for an electromagnetic suppression scenario of the present invention enables the Beidou terminal device to accurately determine whether electromagnetic suppression exists in the surrounding environment, and to promptly countermeasure and adjust the Beidou communication configuration in the electromagnetic suppression scenario, thereby ensuring communication quality and system stability, and improving the accuracy and reliability of Beidou communication.

[0031] like Figure 1 As shown, a Beidou communication method in an electromagnetic suppression scenario specifically includes the following steps:

[0032] Step 1. Sense the electromagnetic environment around the Beidou terminal device.

[0033] The electromagnetic environment surrounding Beidou terminal devices contains useful signals such as communication and navigation signals, as well as intentional interference signals such as suppression jamming and deceptive jamming. The electromagnetic environment quantitative characterization system typically encompasses six dimensions: time domain, frequency domain, spatial domain, energy domain, polarization domain, and modulation domain, enabling a comprehensive characterization of the electromagnetic environment.

[0034] For electromagnetic suppression scenarios, since the power of electromagnetic suppression interference is significantly larger, it can be effectively distinguished only from the energy domain and time-frequency domain. Therefore, the present invention, for electromagnetic suppression scenarios, monitors the energy domain and time-frequency domain of real-time signals, thereby realizing rapid perception of the electromagnetic environment in the energy domain and time-frequency domain. Among them, the perception of the electromagnetic environment around the Beidou terminal device in the energy domain can be achieved by analyzing the signal frequency domain energy distribution through power spectral density PSD, which directly reflects the power strength of the signal. The perception of the electromagnetic environment around the Beidou terminal device in the time-frequency domain can be characterized with the help of a time-frequency spectrum diagram.

[0035] In this embodiment, step 1 of the Beidou communication method in the electromagnetic suppression scenario is specifically as follows:

[0036] Monitor and sample real-time signals in the electromagnetic environment and express them in the following form:

[0037]

[0038] Where x(n) is the monitoring signal, i.e., the real-time signal in the electromagnetic environment around the Beidou terminal device; s(n) is the useful signal; j(n) is the electromagnetic suppression interference; ω(n) is the noise; H0 indicates that there is no electromagnetic suppression interference in the monitoring signal; and H1 indicates that there is electromagnetic suppression interference in the monitoring signal.

[0039] Specifically, the perception of the energy domain directly reflects the power strength of the signal. In this embodiment, the power spectrum density is used to analyze the energy distribution of the signal in the frequency domain. The PSD of the discrete signal is expressed using the Welch method as follows:

[0040]

[0041] Among them, P(f k ) represents the frequency f k The power spectrum density when K is the number of segments, L is the length of each segment, x i (n) represents the monitoring signal of the i-th segment, i∈[1, K], u(n) is the window function, n∈[1, L-1], U is the window energy compensation factor, j represents the imaginary unit, f k =kf s / N,f s is the sampling frequency, k = 0, 1, ..., N / 2, N is the number of sampling points, and the unit of power spectrum density is W / Hz. In electromagnetic suppression scenarios, the power spectrum density of the monitoring signal will fluctuate significantly or have abnormal peaks.

[0042] In order to reduce the misjudgment of electromagnetic suppression interference by single energy threshold detection and improve the accuracy of electromagnetic suppression interference detection in the electromagnetic environment, the method of the present invention adopts a comprehensive judgment method in the energy domain and time-frequency domain. Therefore, it is also necessary to perceive the electromagnetic environment around the Beidou terminal device in the time-frequency domain.

[0043] Specifically, perception of the time-frequency domain is represented by a time-spectrogram. A time-spectrogram is a two-dimensional image created by applying a short-time Fourier transform (STFT) to a signal. Its horizontal axis represents time, its vertical axis represents frequency, and its color depth represents signal strength. A time-spectrogram combines time and frequency on a single image, facilitating simultaneous observation of both time and frequency domain information.

[0044] Step 2. Determine whether electromagnetic suppression interference exists in the electromagnetic environment based on the energy domain and time-frequency domain. If electromagnetic suppression interference exists in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process proceeds to step 3. If electromagnetic suppression interference does not exist in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process proceeds to step 5.

[0045] The current communication scenario includes normal communication scenarios and electromagnetic suppression scenarios. Normal communication scenarios refer to scenarios where no electromagnetic suppression interference is detected in the electromagnetic environment and Beidou communication terminal devices operate normally. Electromagnetic suppression scenarios refer to scenarios where electromagnetic suppression interference is detected in the electromagnetic environment and Beidou communication terminal devices need to cope with electromagnetic suppression. The determination of whether electromagnetic suppression interference exists in the electromagnetic environment, and therefore whether the current communication scenario is an electromagnetic suppression scenario or a normal communication scenario, is based on the aforementioned perception results in the energy and time-frequency domains. If electromagnetic suppression is detected in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario. If electromagnetic suppression is not detected in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario.

[0046] In step 2 of the Beidou communication method under the electromagnetic suppression scenario of this embodiment, it is comprehensively judged from the perspective of the energy domain and the time-frequency domain whether there is electromagnetic suppression interference in the electromagnetic environment. From the perspective of the energy domain, when the monitoring signal strength is greater than the minimum suppression power threshold, or the actual value of the calculated suppression coefficient is greater than the suppression coefficient threshold, it is judged that electromagnetic suppression may exist in the electromagnetic environment. To ensure the accuracy of electromagnetic suppression interference detection, it is necessary to further determine whether there is electromagnetic suppression in the electromagnetic environment from the perspective of the time-frequency domain. From the perspective of the time-frequency domain, the presence of electromagnetic suppression in the electromagnetic environment is judged by analyzing the time-frequency spectrum. When the difference in the spectrum characteristics meets the judgment threshold, it is judged that electromagnetic suppression exists in the electromagnetic environment.

[0047] In step 2, the process of preliminarily judging whether there is electromagnetic suppression interference in the electromagnetic environment from the perspective of energy domain is as follows:

[0048] First, in terms of visualization, we can observe whether the power spectrum density of the monitoring signal fluctuates significantly or has abnormal peaks, thereby preliminarily judging whether there may be electromagnetic suppression interference. In addition, we can further calculate the strength of the monitoring signal by calculating the power spectrum density. The formula is as follows:

[0049]

[0050] Where Δf is the frequency resolution, Δf = f s / N,f s is the sampling frequency, and N is the number of sampling points.

[0051] In electromagnetic suppression, the suppression coefficient reflects the minimum suppression power that can suppress the target electromagnetically. The suppression coefficient is defined as the ratio of the minimum suppression power to the signal receiving power to achieve effective suppression interference.

[0052] The mean signal receiving power in a normal communication scenario without electromagnetic suppression interference is taken as the default value P s , and the threshold of the minimum suppression power is preset as Thus, the suppression coefficient threshold J is calculated th for:

[0053] When the monitoring signal strength P m Less than or equal to the minimum suppression power threshold When P m ≤P jth When the signal strength P is monitored, it is determined that there is no electromagnetic suppression interference in the electromagnetic environment, and the current communication scene is determined to be a normal communication scene, and the process goes to step 5. m Greater than the minimum suppression power threshold When When , it is preliminarily judged that there may be electromagnetic suppression interference in the electromagnetic environment, and further judgment is needed from the perspective of time and frequency domain.

[0054] Or calculate the actual value of the suppression coefficient J m =P m / P s , when the actual value of the suppression coefficient J m Less than or equal to the suppression coefficient threshold J th When J m ≤J th When the actual value of the suppression coefficient J is , it is determined that there is no electromagnetic suppression interference in the electromagnetic environment, and then the current communication scene is determined to be a normal communication scene, and the process goes to step 5. m Greater than the suppression coefficient threshold J th When J m >J th When the electromagnetic environment is affected, it can be preliminarily judged that there is electromagnetic suppression interference, and then further judgment is needed from the perspective of time and frequency domain.

[0055] After preliminarily judging the possible existence of electromagnetic suppression interference in the energy domain, the present invention further makes an accurate judgment in the time-frequency domain.

[0056] In step 2, the process of determining whether there is electromagnetic suppression interference in the electromagnetic environment from the perspective of time and frequency domain is as follows:

[0057] The presence of electromagnetic suppression in the electromagnetic environment can be further determined by analyzing the time-frequency spectrum. Using the time-frequency spectrum in a typical communication scenario as a reference spectrum, the time-frequency spectrum of the real-time monitoring signal as the real-time spectrum. By comparing the real-time spectrum with the reference spectrum and conducting preliminary observation and analysis, a preliminary judgment can be made regarding the potential presence of electromagnetic suppression. In addition to visually observing the time-frequency variations of electromagnetic signals, since the time-frequency spectrum is a two-dimensional image, image processing techniques such as feature extraction and matching can be used to accurately determine the presence of electromagnetic suppression in the time-frequency domain. For example, the scale-invariant feature transform (SIFT) method can be used to extract and match features from the time-frequency spectrum.

[0058] In this embodiment, the process of SIFT feature extraction and matching is as follows:

[0059] (1) Spectrogram preprocessing: The real-time spectrogram and the reference spectrogram are preprocessed, the spectrum power value is mapped to a 0 to 255 grayscale image, and Gaussian blur noise reduction and edge enhancement are performed.

[0060] (2) Key point detection and descriptor generation: The multi-scale features of useful and interference signals are captured by constructing a Gaussian pyramid, extreme value detection is performed to locate power mutation points, direction allocation is performed to reflect the time-frequency variation trend, and descriptor generation is performed to encode the local power distribution features of key points.

[0061] (3) Feature matching and difference quantification: Using nearest neighbor matching, bidirectionally match the key points of the reference spectrum and the real-time spectrum, and determine the difference based on the ratio of unmatched key points and the average Euclidean distance between matched key points.

[0062] The thresholds for determining the ratio of unmatched key points and the average Euclidean distance between matched key points in the preset electromagnetic suppression scenario are set.

[0063] If the spectral features between the reference spectrum and the real-time spectrum are significantly different, that is, the proportion of unmatched key points and the average Euclidean distance between matched key points are both greater than the judgment threshold, it is judged that electromagnetic suppression interference exists in the electromagnetic environment, and the current communication scenario is judged to be an electromagnetic suppression scenario, and the process goes to step 3; otherwise, it is judged that there is no electromagnetic suppression interference in the electromagnetic environment, and the current communication scenario is judged to be a normal communication scenario, and the process goes to step 5.

[0064] Step 3: Separate the electromagnetic suppression interference from the mixed signal of the electromagnetic environment, and extract the features of the electromagnetic suppression interference to determine the type of the electromagnetic suppression interference.

[0065] Based on the frequency band and bandwidth of electromagnetic suppression interference, electromagnetic suppression interference is classified into blocking interference, aiming interference, and sweeping interference. If the current communication scenario is determined to be an electromagnetic suppression scenario, the electromagnetic suppression interference features in the electromagnetic suppression scenario are extracted and analyzed to further determine the type of electromagnetic suppression interference.

[0066] In step 3 of the Beidou communication method in the electromagnetic suppression scenario of this embodiment, it is first necessary to separate the electromagnetic suppression interference from the mixed signal, and then perform feature extraction on the electromagnetic suppression interference. Since the real-time monitoring signal in the electromagnetic suppression scenario is a mixture of electromagnetic suppression interference and useful signals, it is first necessary to separate the electromagnetic suppression interference from the mixed signal. Then, feature extraction and analysis of the electromagnetic suppression interference is performed. The electromagnetic suppression interference feature extraction and analysis is to further extract features of the electromagnetic suppression interference in the electromagnetic suppression scenario. The features of the suppression interference need to be extracted from the time domain, frequency domain, and time-frequency domain, thereby laying the foundation for subsequent timely and accurate countermeasures against electromagnetic suppression. This embodiment performs peak-to-average ratio feature extraction and analysis in the time domain, bandwidth share and spectral entropy feature extraction and analysis in the frequency domain, and time-frequency distribution extraction and analysis in the time-frequency domain.

[0067] Specifically, in step 3, electromagnetic suppression interference is first separated from the mixed signal. This embodiment adopts a suppression interference signal separation technology based on STFT-ICA joint processing, and its specific process includes:

[0068] (1) STFT time-frequency transform: extract the amplitude spectrum from the time-frequency spectrum of the real-time monitoring signal after STFT, and construct the amplitude spectrum matrix, where the time-frequency spectrum of the real-time monitoring signal has been obtained in step 2.

[0069] (2) ICA independent component separation: The amplitude spectrum matrix is ​​used as input, and after fast independent component analysis, the time-frequency distribution of the independent components is obtained.

[0070] (3) Interference component identification: Calculate the peak-to-average ratio (PAPR). The PAPR calculation formula is as follows:

[0071]

[0072] Among them, PAPR i represents the peak-to-average ratio, S i Indicates independent components after separation.

[0073] The component with the highest PAPR is selected as the electromagnetic suppression interference, and the electromagnetic suppression interference time-frequency distribution matrix is ​​output.

[0074] (4) Inverse STFT recovery of time-domain electromagnetic suppression interference: Perform inverse STFT on the time-frequency distribution matrix of electromagnetic suppression interference to obtain the time-frequency spectrum of electromagnetic suppression interference.

[0075] In step 3, the process of extracting features of electromagnetic suppression interference and determining the type of electromagnetic suppression interference is as follows:

[0076] For the electromagnetic suppression interference separated from the mixed signal, the peak-to-average ratio feature is extracted from the time domain, the bandwidth ratio and spectrum entropy feature are extracted from the frequency domain, and the time-frequency distribution feature is extracted from the time-frequency domain.

[0077] The peak-to-average ratio threshold, bandwidth ratio threshold, and spectrum entropy value threshold are preset to determine the type of electromagnetic suppression interference.

[0078] If the electromagnetic suppression interference characteristics simultaneously meet the following conditions: the bandwidth ratio changes dynamically, the spectrum entropy value fluctuates periodically, the peak-to-average ratio is higher than the preset peak-to-average ratio threshold and fluctuates periodically, and the time-frequency distribution is a slant line or a curved time-frequency trajectory, then the type of electromagnetic suppression interference is determined to be swept frequency interference.

[0079] If the electromagnetic suppression interference characteristics simultaneously meet the following conditions: the bandwidth ratio is wider than the preset bandwidth ratio threshold, the spectrum entropy value is greater than the preset spectrum entropy value threshold, the peak-to-average ratio is lower than the preset peak-to-average ratio threshold, and the time-frequency distribution is uniformly distributed across the entire frequency band, then the type of electromagnetic suppression interference is determined to be blocking interference.

[0080] If the electromagnetic suppression interference characteristics simultaneously meet the conditions that the bandwidth ratio is narrower than the preset bandwidth ratio threshold, the spectrum entropy value is less than the preset spectrum entropy value threshold, the peak-to-average ratio is higher than the preset peak-to-average ratio threshold, and the time-frequency distribution is fixed narrowband focusing, then the type of electromagnetic suppression interference is determined to be aiming interference.

[0081] Table 1 Characteristics of three types of suppression interference in different feature dimensions

[0082] Feature Dimension Blocking interference Aiming interference Sweep frequency interference Bandwidth share Width narrow Dynamic changes Spectral entropy big Small Cyclical fluctuations Peak-to-average ratio Low high High and cyclical Time-frequency distribution Evenly distributed across the entire frequency band Fixed narrowband focusing Slant / curved time-frequency trace

[0083] Specifically, feature extraction and analysis of electromagnetic suppression interference is performed to determine the type of electromagnetic suppression interference and select subsequent countermeasures. In this embodiment, electromagnetic suppression interference is divided into blocking interference, aiming interference, and sweeping interference based on the suppression frequency band and bandwidth. Table 1 shows the characteristics of the three types of suppression interference in different feature dimensions. Blocking interference has a wide bandwidth, aiming interference is narrowband and targets a specific frequency, and the frequency of sweeping interference varies over time.

[0084] The characteristics of electromagnetic suppression interference need to be extracted from the time domain, frequency domain, and time-frequency domain.

[0085] In the time domain, peak-to-average ratio (PAPR) feature extraction and analysis are performed to calculate the peak-to-average ratio (PAPR) of the suppressed interference signal. Blocking interference exhibits a low PAPR and evenly distributed energy. Aiming or sweeping interference exhibits a high PAPR and concentrated energy. Sweeping interference also produces periodic amplitude fluctuations due to frequency changes.

[0086] In the frequency domain, bandwidth share and spectral entropy feature extraction and analysis are performed. In this embodiment, bandwidth share is analyzed by calculating the power spectral density (PSD) of the suppressed interference signal. Blocking interference has a wide bandwidth share, while targeting interference has a narrow bandwidth share. Spectral entropy describes the complexity and randomness of the signal in the frequency domain. A larger entropy value means that the signal contains more frequency components, and the changes are more complex and disordered. The formula for spectral entropy is expressed as:

[0087] H(f) = -∑P(f)log(P(f)).

[0088] Where H(f) represents the spectrum entropy and P(f) represents the power spectrum density. The spectrum entropy of blocking interference is large, the spectrum entropy of aiming interference is small, and the spectrum entropy of sweeping interference fluctuates periodically.

[0089] In the time-frequency domain, the time-frequency distribution must be extracted, which is obtained synchronously when separating and suppressing interference. Time-frequency analysis captures the change in frequency over time and detects linear or nonlinear changes in frequency. Sweep interference will appear as a diagonal or curved time-frequency trajectory.

[0090] Step 4: Take countermeasures based on the electromagnetic suppression interference feature extraction and analysis results, that is, the type of electromagnetic suppression interference.

[0091] After extracting and analyzing the electromagnetic suppression interference characteristics, the type of suppression interference is determined and then targeted countermeasures are taken. Adaptive zeroing technology is used for aiming interference, and adaptive cancellation technology is used for blocking interference and sweeping frequency interference.

[0092] Adaptive nulling technology is used to target interference. It leverages the array antenna's beamforming capabilities to adjust the antenna array weights to create a null in the interference direction, thereby suppressing the interference. Adaptive cancellation technology is applicable to blocking and swept-frequency interference. It cancels the interference by generating a reconstructed signal with equal amplitude and opposite phase to the interference. Table 2 compares adaptive nulling and adaptive cancellation technologies.

[0093] Table 2 Comparison of adaptive nulling and adaptive cancellation techniques

[0094] Dimensions Adaptive zeroing Adaptive Cancellation Suppression Dimension airspace Frequency domain / time domain Applicable Scenarios Narrowband directional interference Broadband / dynamic interference Real-time requirements High (requires fast weight updates) Medium (depends on filter convergence speed) Hardware costs High (array antenna required) Low (single channel can work)

[0095] Specifically, adaptive nulling technology is used to target interference. It uses the array antenna's beamforming capability to adjust the weights of the antenna array to form a null in the interference direction, thereby suppressing interference. The steps of adaptive nulling technology include:

[0096] (1) Signal reception: Signals are collected through a multi-channel array antenna.

[0097] (2) Interference localization: Determine the interference direction based on spatial spectrum estimation, such as the MUSIC algorithm.

[0098] (3) Weight calculation: The optimal weight is calculated using the sampling matrix inversion SMI or the least mean square LMS algorithm.

[0099] (4) Beamforming: Adjust the array weights to generate nulls in the interference direction.

[0100] Specifically, adaptive cancellation technology is used for blocking and sweeping interference, which have a wide coverage in the frequency or time domain. Adaptive cancellation technology achieves interference cancellation by generating a reconstructed signal with equal amplitude and opposite phase to the interference. The steps of adaptive cancellation technology include:

[0101] (1) Reference signal extraction: Obtain the interference reference signal through auxiliary channels or separation algorithms.

[0102] (2) Adaptive filtering: Use LMS or recursive least squares RLS algorithm to train the filter coefficients.

[0103] (3) Interference reconstruction: Generating an exact copy of the interference is called reconstructing the interference.

[0104] (4) Cancellation execution: subtract the reconstructed interference from the main signal. Furthermore, the variable step size algorithm VSS-LMS is used to achieve dynamic interference tracking for the swept frequency interference, and the sub-band decomposition technology is combined to deal with the broadband characteristics of the blocking interference for broadband processing.

[0105] In mixed interference scenarios involving blocking, aiming, and sweeping interference, adaptive nulling can be used to suppress strong aiming interference, and then adaptive cancellation can be used to handle residual blocking / sweeping interference.

[0106] Step 5. Adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

[0107] In this embodiment, the communication configuration of the Beidou terminal device includes a communication configuration for a normal scenario and a communication configuration for a suppression scenario. These two communication configurations correspond to two communication channels: an initial communication channel and a suppression communication channel. The communication configuration of both Beidou terminal devices includes five parameters: operating frequency band, modulation mode, transmit power, channel coding, and beam pattern. The specific configuration information is shown in Table 3, where BPSK stands for binary phase shift keying, QPSK stands for quadrature phase shift keying, FHSS stands for frequency hopping spread spectrum, LDPC stands for low-density parity check code, and Polar stands for polarization code.

[0108] Table 3 Communication configuration for normal and suppression scenarios

[0109] parameter Normal scenario configuration (default) Suppression scene configuration Associated interference type Operating frequency band B2a:1176.45MHz B2b:1207.14MHz General Modulation method BPSK QPSK+FHSS Sweep / Blocking Interference Transmit power Fixed power Adaptive boost power Blocking interference Channel Coding LDPC codes Polar code General Beam pattern Omnidirectional beam Directional beam Aiming interference

[0110] Set the initial default communication configuration for Beidou communication and assign an initial communication channel to it. If the current communication scenario is normal communication, the default communication configuration is used as the normal communication configuration. This occupies the initial communication channel and allows direct Beidou communication. If the current communication scenario is electromagnetic suppression, switch to the suppression communication channel and complete the suppression scenario communication configuration as described in Table 3 before continuing with Beidou communication.

[0111] For targeted interference scenarios, the B2b band is enabled and directional beams are used to suppress directional interference. For sweeping interference scenarios, frequency hopping is used to dynamically match the interference sweep rate. For blocking interference scenarios, transmit power is adaptively increased.

[0112] The Beidou terminal device adopting the method of the present invention will adjust the Beidou communication configuration according to the current communication scenario, and select the corresponding communication channel for subsequent communication, tracking, positioning, etc. The method of the present invention can timely counter-adjust the Beidou communication configuration in the electromagnetic suppression scenario, thereby ensuring the communication quality and system stability, and improving the accuracy and reliability of Beidou communication.

[0113] The present invention reduces the misjudgment of electromagnetic suppression interference by single energy threshold detection through a comprehensive judgment method in the energy domain and time-frequency domain, thereby improving the accuracy of electromagnetic suppression interference detection in the electromagnetic environment; by extracting the characteristics of electromagnetic suppression interference, accurate classification of suppression interference is achieved, and corresponding countermeasures are taken in a targeted manner, realizing a technological transition from passive defense to active confrontation, and being able to adaptively adjust communication parameters, which is particularly suitable for high-reliability communication needs in complex electromagnetic environments.

[0114] Example 2

[0115] This embodiment 2 describes a Beidou communication system in an electromagnetic suppression scenario, which is based on the same inventive concept as the Beidou communication method in the electromagnetic suppression scenario in embodiment 1.

[0116] Specifically, the BeiDou communication system in this electromagnetic suppression scenario includes the following modules:

[0117] The environmental perception module is used to perceive the electromagnetic environment around the Beidou terminal device.

[0118] The scene judgment module is used to judge whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain.

[0119] If there is electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process is transferred to the countermeasure adjustment module; if there is no electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process is transferred to the Beidou communication module.

[0120] The countermeasure adjustment module is used to separate electromagnetic suppression interference from the mixed signals of the electromagnetic environment and extract features of the electromagnetic suppression interference, so as to determine the type of electromagnetic suppression interference and take countermeasures according to the type of electromagnetic suppression interference.

[0121] The Beidou communication module is used to adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

[0122] It should be noted that, in the Beidou communication system under the electromagnetic suppression scenario, the implementation process of the functions and effects of each functional module is specifically described in the implementation process of the corresponding steps in the method in Example 1, and will not be repeated here.

[0123] Example 3

[0124] This embodiment 3 describes a computer device, which includes a memory and one or more processors.

[0125] Executable code is stored in the memory. When the processor executes the executable code, it is used to implement the steps of the Beidou communication method in the electromagnetic suppression scenario in the above-mentioned embodiment 1.

[0126] In this embodiment, the computer device is any device or apparatus with data processing capability, which will not be described in detail here.

[0127] Example 4

[0128] This embodiment 4 describes a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, it is used to implement the steps of the Beidou communication method in an electromagnetic suppression scenario.

[0129] The computer-readable storage medium can be an internal storage unit of any device or apparatus with data processing capabilities, such as a hard disk or memory, or an external storage device of any device with data processing capabilities, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc. equipped on the device.

[0130] Of course, the above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above-mentioned embodiments. It should be noted that all equivalent substitutions and obvious deformation forms made by any technician familiar with this field under the guidance of this specification fall within the substantive scope of this specification and should be protected by the present invention.

Claims

1. A BeiDou communication method in an electromagnetic suppression scenario, characterized in that: The steps include: Step 1. Sense the electromagnetic environment around the Beidou terminal device; Step 2. Determine whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain; If electromagnetic suppression interference exists in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process goes to step 3; if electromagnetic suppression interference does not exist in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process goes to step 5; Step 3. Separate the electromagnetic suppression interference from the mixed signal of the electromagnetic environment, and extract the features of the electromagnetic suppression interference to determine the type of the electromagnetic suppression interference; Step 4. Countermeasures against the type of electromagnetic suppression interference; Step 5. Adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

2. The BeiDou communication method in an electromagnetic suppression scenario according to claim 1, characterized in that: The step 1 is specifically as follows: Monitor and sample real-time signals in the electromagnetic environment around the Beidou terminal device, which can be expressed as follows: Where x(n) is the monitoring signal, i.e., the real-time signal in the electromagnetic environment around the BeiDou terminal device; s(n) is the useful signal; j(n) is the electromagnetic suppression interference; w(n) is the noise; H0 indicates that there is no electromagnetic suppression interference in the monitoring signal; H1 indicates that there is electromagnetic suppression interference in the monitoring signal; In the energy domain, the power spectral density (PSD) is used to analyze the frequency domain energy distribution of the monitoring signal. The Welch method is used to express the PSD of the discrete signal as: Among them, P(f k ) represents the frequency f k The power spectral density when f k =kf s / N,f s is the sampling frequency, k=0, 1, ..., N / 2, N is the number of sampling points, K is the number of segments, L is the length of each segment, x i (n) represents the monitoring signal of the i-th segment, i∈[1,K], n∈[1,L-1], u(n) is the window function, U is the window energy compensation factor, and j represents the imaginary unit; In the time-frequency domain, the electromagnetic environment around the Beidou terminal device is characterized by using the time-spectrogram of the monitoring signal. The time-spectrogram is a two-dimensional image made after the signal undergoes short-time Fourier transform (STFT), where the horizontal axis is time and the vertical axis is frequency. The time-spectrogram uses color depth to represent signal strength.

3. The BeiDou communication method in an electromagnetic suppression scenario according to claim 2, characterized in that: The step 2 is specifically as follows: From the perspective of energy domain, the monitoring signal strength P is obtained by calculating the power spectrum density. m , the formula is: Where Δf is the frequency resolution, Δf = f s / N; The preset minimum suppression power threshold is When the monitoring signal strength P m Less than or equal to the minimum suppression power threshold When the signal strength P is detected, it is determined that there is no electromagnetic suppression interference in the electromagnetic environment, and the current communication scene is determined to be a normal communication scene and go to step 5; m Greater than the minimum suppression power threshold When the electromagnetic environment is affected by electromagnetic interference, it is further judged from the perspective of time-frequency domain whether there is electromagnetic suppression interference; From the perspective of the time-frequency domain, the time-frequency spectrum in a common communication scenario is used as a reference spectrum. The time-frequency spectrum of the real-time monitoring signal, i.e., the real-time spectrum, is compared with the reference spectrum. The scale-invariant feature transform (SIFT) method is used to extract and match the time-frequency spectrum features. The specific process of SIFT feature extraction and matching is as follows: Preprocess the real-time spectrogram and reference spectrogram, map the spectrum power value to a 0 to 255 grayscale image, and perform Gaussian blur noise reduction and edge enhancement processing; Key point detection and descriptor generation are performed. The useful signal and interference signal characteristics of the real-time spectrum and reference spectrum are captured by constructing a Gaussian pyramid at multiple scales. Power mutation points are located by performing extreme value detection. Time-frequency variation trends are reflected by performing direction allocation. Descriptors are used to generate local power distribution characteristics of encoded key points. Perform feature matching and difference quantification, using nearest neighbor matching, bidirectionally matching the key points of the reference spectrum and the real-time spectrum, and determine the difference based on the proportion of unmatched key points and the average Euclidean distance between matched key points; Preset the judgment thresholds for the ratio of unmatched key points and the average Euclidean distance between matched key points in the electromagnetic suppression scenario; If the spectral features between the reference spectrum and the real-time spectrum are significantly different, that is, the proportion of unmatched key points and the average Euclidean distance between matched key points are both greater than the judgment threshold, it is judged that electromagnetic suppression interference exists in the electromagnetic environment, the current communication scenario is judged to be an electromagnetic suppression scenario, and the process goes to step 3; otherwise, it is judged that electromagnetic suppression interference does not exist in the electromagnetic environment, the current communication scenario is judged to be a normal communication scenario, and the process goes to step 5.

4. The Beidou communication method in the electromagnetic suppression scenario according to claim 3, characterized in that: In step 3, the electromagnetic suppression interference is separated from the mixed signal of the electromagnetic environment, i.e., the monitoring signal, by using the suppression interference signal separation technology based on STFT-ICA joint processing. The specific process is as follows: Extract the amplitude spectrum from the time-frequency spectrum of the real-time monitoring signal after STFT and construct the amplitude spectrum matrix; The amplitude spectrum matrix is ​​used as input, and the time-frequency distribution of independent components is obtained after ICA independent component separation; Interference components are identified by calculating the peak-to-average ratio (PAPR). The calculation formula is: Among them, PAPR i represents the peak-to-average ratio, S i Indicates the independent components after separation; Select the component with the highest PAPR as the electromagnetic suppression interference and output the time-frequency distribution matrix of the electromagnetic suppression interference; Perform inverse STFT on the time-frequency distribution matrix of electromagnetic suppression interference to obtain the time-frequency spectrum of electromagnetic suppression interference.

5. The BeiDou communication method in an electromagnetic suppression scenario according to claim 4, characterized in that: In step 3, the process of extracting features of electromagnetic suppression interference and determining the type of electromagnetic suppression interference is specifically as follows: For the electromagnetic suppression interference separated from the mixed signal, the peak-to-average ratio feature is extracted in the time domain, the bandwidth ratio and spectrum entropy feature are extracted in the frequency domain, and the time-frequency distribution feature is extracted in the time-frequency domain. Preset peak-to-average ratio threshold, bandwidth ratio threshold and spectrum entropy value threshold for judging the type of electromagnetic suppression interference; If the electromagnetic suppression interference characteristics simultaneously meet the following conditions: dynamic changes in bandwidth ratio, periodic fluctuations in spectrum entropy, peak-to-average ratio higher than the preset peak-to-average ratio threshold and periodic fluctuations, and a time-frequency distribution that is a slant line or a curved time-frequency trajectory, then the electromagnetic suppression interference is determined to be swept frequency interference. If the electromagnetic suppression interference characteristics simultaneously meet the following conditions: the bandwidth ratio is wider than the preset bandwidth ratio threshold, the spectrum entropy value is greater than the preset spectrum entropy value threshold, the peak-to-average ratio is lower than the preset peak-to-average ratio threshold, and the time-frequency distribution is uniformly distributed across the entire frequency band, then the type of electromagnetic suppression interference is determined to be blocking interference; If the electromagnetic suppression interference characteristics simultaneously meet the conditions that the bandwidth ratio is narrower than the preset bandwidth ratio threshold, the spectrum entropy value is less than the preset spectrum entropy value threshold, the peak-to-average ratio is higher than the preset peak-to-average ratio threshold, and the time-frequency distribution is fixed narrowband focusing, then the type of electromagnetic suppression interference is determined to be aiming interference.

6. The BeiDou communication method in an electromagnetic suppression scenario according to claim 5, characterized in that: The step 4 is specifically as follows: Adaptive nulling technology is used to counter targeted interference. This technology leverages the array antenna's beamforming capability to adjust the antenna array's weights to create a null in the interference direction, thereby suppressing the interference. Adaptive cancellation technology is used to counter blocking interference and sweeping frequency interference. Adaptive cancellation technology achieves interference cancellation by generating a reconstructed signal with equal amplitude and opposite phase to the interference.

7. The BeiDou communication method in an electromagnetic suppression scenario according to claim 6, characterized in that: The step 5 is specifically as follows: The communication configuration of the Beidou terminal device includes the default communication configuration and the suppressed scenario communication configuration. The default communication configuration corresponds to the initial communication channel, and the suppressed scenario communication configuration corresponds to the suppressed communication channel. Preset the parameters of the default communication configuration and the suppression scenario communication configuration, including the operating frequency band, modulation mode, transmit power, channel coding, and beam mode; If the current communication scenario is a normal communication scenario, the default communication configuration is used, and the initial communication channel is occupied to complete Beidou communication; if the current communication scenario is an electromagnetic suppression scenario, the suppression scenario communication configuration is used, and the suppression communication channel is switched to complete Beidou communication under the electromagnetic suppression scenario.

8. A BeiDou communication system in an electromagnetic suppression scenario, characterized in that: include: Environmental perception module, used to perceive the electromagnetic environment around Beidou terminal equipment; The scene judgment module is used to judge whether there is electromagnetic suppression interference in the electromagnetic environment from the energy domain and time-frequency domain; If there is electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be an electromagnetic suppression scenario and the process is switched to the countermeasure adjustment module. If there is no electromagnetic suppression interference in the electromagnetic environment, the current communication scenario is determined to be a normal communication scenario and the process is switched to the Beidou communication module. The countermeasure adjustment module is used to separate electromagnetic suppression interference from the mixed signals of the electromagnetic environment and extract the characteristics of the electromagnetic suppression interference, so as to determine the type of electromagnetic suppression interference and take countermeasures according to the type of electromagnetic suppression interference; The Beidou communication module is used to adjust the Beidou communication configuration according to the current communication scenario and complete Beidou communication.

9. A computer device comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that: When the processor executes the executable code, the steps of the Beidou communication method in the electromagnetic suppression scenario as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by the processor, the steps of the Beidou communication method in the electromagnetic suppression scenario as described in any one of claims 1 to 7 are implemented.

Images