A space-time-frequency based anti-deception interference joint detection method and system

Abstract

The present application relates to a space-time-frequency-based anti-spoofing interference joint detection method and system, which includes obtaining the signal source direction of the received satellite signal, and dividing the signal source direction into channels by angle based on the beamforming criterion; based on the preset capture rule, initiating a capture search for the signal in each channel, and synchronously performing correlation peak detection and array antenna anti-interference detection on the signal, obtaining the angle information of the signal in each channel and the satellite PRN information during the capture process; performing zero-stuck processing on the signal source direction of two or more satellite signals appearing at the same angle; outputting the capture result based on the capture rule, and performing rotation tracking on the capture result that meets the capture rule; performing Doppler frequency shift consistency detection and signal power calculation on the rotation tracked signal, identifying the deception signal and feeding it back to the antenna array for filtering processing. The present application has the effect of expanding the scope of application of the anti-spoofing interference detection method and improving the anti-interference capability of navigation positioning.

Description

Technical Field

[0001] The present application relates to the technical field of global satellite navigation systems, and in particular to a space-time-frequency based anti-spoofing interference joint detection method and system. Background Art

[0002] At present, in the security research of the global satellite navigation system GNSS, since the satellite signal has low power when transmitted to the ground receiver, it is easy to be interfered by human beings. The interference methods are mainly divided into suppression interference and deception interference. Deception interference is an important threat currently faced by satellite navigation equipment. It forges deception signals similar to real satellite signals and mixes them into the receiver processing. It is highly concealed, causing the receiver to give wrong positioning results, which seriously threatens the application security of the satellite navigation system.

[0003] Existing GNSS anti-spoofing and interference detection mainly includes received signal strength detection, signal arrival azimuth detection, signal quality detection, Doppler frequency shift consistency detection, message encryption authentication, spoofing and interference detection based on auxiliary information, and spoofing and interference detection based on machine learning.

[0004] Signal arrival azimuth detection is applicable to the deception mode of single antenna transmission; Doppler frequency shift consistency detection and signal quality detection are affected by the correlation peak interval between the real signal and the deception signal, and are prone to missed detection when there is suppression interference; message encryption authentication has a very low detection effect on forwarding deception interference, and requires a large amount of engineering work to implement; deception interference detection based on auxiliary information requires additional equipment such as IMU, and is not very practical; deception interference detection based on machine learning will encounter problems such as missing features and insufficient training in actual applications.

[0005] Therefore, the anti-spoofing interference detection methods in the prior art are generally not universal, and a single GNSS anti-spoofing interference detection algorithm cannot be applied to a variety of deception interference scenarios; the received signal strength monitoring has the risk of false alarms and other misjudgments, so it needs to be improved. Summary of the invention

[0006] In order to expand the scope of application of the anti-deception interference detection method, to enhance the practicability and accuracy of the anti-deception interference detection, and to improve the anti-interference capability of navigation positioning, the present application provides a space-time-frequency based anti-deception interference joint detection method and system.

[0007] The above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0008] A space-time-frequency based anti-deception interference joint detection method comprises the following steps:

[0009] Acquire the signal source direction of the received satellite signal, and divide the signal source direction into channels according to angles based on a preset beamforming criterion;

[0010] Based on the preset capture rules, a capture search is initiated for the signal in each of the channels, and peak detection and array antenna anti-interference detection are synchronously performed on the signal to obtain the angle information and satellite PRN information of the satellite signal in each of the channels during the capture process;

[0011] Performing null processing on the signal source direction where two or more satellite signals appear at the same angle;

[0012] Outputting capture results based on the capture rules, and tracking the capture results that meet the capture rules;

[0013] The Doppler frequency shift consistency detection and signal power calculation are performed on the rotation tracking signal, and the deception signal is identified and fed back to the antenna array for filtering processing.

[0014] Optionally, the obtaining of the signal source direction of the received satellite signal includes:

[0015] The RF front end receives the satellite signal and outputs a digital intermediate frequency signal after AD conversion and digital down-conversion processing, that is, the signal in the channel;

[0016] The digital intermediate frequency signal is subjected to DOA estimation processing to detect and obtain all the signal source directions.

[0017] Optionally, the step of dividing the signal source direction into channels according to angles based on a preset beamforming criterion includes:

[0018] It is preset that there are signals at m angles in the estimation result of the DOA estimation processing, based on a preset signal processing array, the signal processing array includes a uniform linear array composed of L array elements, and the formula of the beamforming criterion is:

[0019]

[0020] In the formula, k is the sampling number, is the signal obtained after beamforming, is the received signal, is the weight vector of the antenna array under a certain angle signal, Represents the conjugate transpose of the matrix and divides the channels by angle using the preset beamforming criterion.

[0021] Optionally, the initiating a capture search for the signal in each of the channels based on a preset capture rule includes:

[0022] Performing correlation operation on the signal in each of the channels and the local replica code to initiate a capture search;

[0023] Based on a preset first capture threshold, determining whether there is a signal peak value exceeding the first capture threshold;

[0024] If yes, switching to the preset second capture threshold to perform capture search, and judging whether there is a signal peak value exceeding the second capture threshold, and the second capture threshold is less than the first capture threshold;

[0025] If the signal peak value exceeds the second capture threshold again, the capture search start point is offset by a preset base code position according to the captured code phase information and then the capture is performed again;

[0026] If the capture is successful, the current capture result is judged to be in accordance with the capture rules and is determined to be true information for capture and tracking processing. If the capture is unsuccessful, the previous capture result is judged to be in accordance with the capture rules and is transferred to tracking processing.

[0027] Optionally, performing Doppler frequency shift consistency detection and signal power calculation on the signal of the rotation tracking, identifying the spoofing signal and feeding it back to the antenna array for filtering processing, includes:

[0028] Track the signal being tracked, obtain the Doppler observation of the signal, and count the variance under a preset window time, detect and identify the signal with abnormal Doppler frequency change, mark it as a spoofing signal, associate the channel of the current spoofing signal according to the detection result, and feed it back to the antenna array for nulling processing;

[0029] The signal power of the signal is calculated synchronously, the power of the instant branch is divided by the noise power, and the mean is statistically calculated. When it is detected that the difference between the signal power and the preset normal range value is greater than the preset deviation threshold, the channel of the current spoofing signal is associated according to the detection result and fed back to the antenna array for null processing.

[0030] The second object of the invention is achieved by the following technical solutions:

[0031] A space-time-frequency based anti-deception interference joint detection system is used to execute a space-time-frequency based anti-deception interference joint detection method.

[0032] The third objective of the present application is achieved through the following technical solutions:

[0033] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned space-time-frequency based anti-deception interference joint detection method are implemented.

[0034] The fourth objective of the present application is achieved through the following technical solutions:

[0035] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned space-time-frequency based anti-deception interference joint detection method are implemented.

[0036] In summary, the present application includes at least one of the following beneficial technical effects:

[0037] 1. Based on the existing array antenna, the problem of multi-peak detection can only detect whether there is interference and signal power detection false alarm is solved. By dividing the channel in the direction of the signal source and associating the signal detection results of the channel, the specific channel of the deception signal can be accurately identified, reducing the use of external auxiliary information and hardware equipment; by obtaining the angle information of the signal in each channel and the satellite PRN information, it is determined whether there are two or more satellite signals at the same angle, and the signal at this angle is zeroed. It does not depend on the signal format and is suitable for complex deceptive interference environments. It avoids positioning deviation or even inability to position caused by deceptive interference, reduces the false alarm and missed alarm rates, and improves the anti-interference performance of navigation positioning.

[0038] 2. By setting different capture thresholds and switching them, the accuracy of signal capture search can be improved.

[0039] 3. After performing zero-stuck processing on the signal on the selected channel, the gain in that direction is reduced to suppress the spoofing signal. The signal of the channel is further tracked, and the anti-spoofing signal is detected by combining signal power calculation and Doppler frequency shift to detect the anti-spoofing signal more accurately and filter the spoofing signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flow chart of an embodiment of a space-time-frequency based anti-spoofing interference joint detection method of the present application;

[0041] Figure 2 This is a principle block diagram of a computer device of the present application. DETAILED DESCRIPTION

[0042] The following is combined with Figure 1-2 This application is described in further detail.

[0043] Existing GNSS anti-spoofing and interference detection mainly includes received signal strength detection, signal arrival azimuth detection, signal quality detection, Doppler frequency shift consistency detection, message encryption authentication, spoofing and interference detection based on auxiliary information, and spoofing and interference detection based on machine learning.

[0044] Received signal strength detection is a common method for single-antenna receivers, which is generally performed after signal despreading. Its main research idea is that when there is deceptive interference, the received satellite signal will be abnormal in absolute power, carrier-to-noise ratio, and L1 / L2 power ratio. By detecting whether there is an abnormality, we can detect whether there is deceptive interference.

[0045] Array signal processing can bring advantages such as strong anti-interference ability, high signal gain and high spatial resolution, which can serve GNSS receivers and improve the performance of GNSS receivers. Receivers equipped with antennas can use spatial filtering technology to form their receiving beam pattern. This type of receiver can form null suppression for spoofing sources.

[0046] Signal quality monitoring (SQM) technology is based on the interaction between spoofing interference signals and real satellite signals, which leads to the distortion of the tracking phase correlation peak. The output values ​​of the early code, instant code and delayed code correlators in the GNSS receiver tracking loop are calculated to identify the deformation of the correlation function. SQM generally monitors the possible distortion and abnormality of the signal correlation peak by detecting the asymmetry of the correlation peak or the abnormal sharpness and flatness of the correlation peak. The corresponding detection algorithms are Delta algorithm and Ratio algorithm. At present, the real signal and the spoofing signal are mainly analyzed in the time domain and frequency domain by monitoring the correlation peak, finding the difference characteristics and finally realizing the detection.

[0047] Doppler shift refers to the change in phase and frequency of a moving signal when it moves in a certain direction at a constant speed, because the propagation distance will change with the movement. In the process of satellite positioning and navigation, Doppler shift occurs due to the relative motion between the satellite and the receiver. In the propagation of the real signal, the Doppler shift of the pseudo code of the satellite signal and the Doppler shift of the carrier should be consistent. The spoofing signal cannot easily control the relative position of the target receiver and it, so the Doppler shift of the spoofing signal will be abnormal. The spoofing signal is detected by detecting the Doppler consistency.

[0048] By encrypting the reserved bytes on the navigation message, the receiving end performs encryption verification to detect the presence of the spoofing signal. This method has a good detection effect on generative spoofing, but it also has two disadvantages. First, encrypting the navigation message is a huge project, which means changing the entire navigation signal system, and the receiver also needs to make certain improvements, and the encrypted content needs to be updated regularly; second, this method is ineffective for forwarding spoofing, because forwarding spoofing also contains encrypted content.

[0049] When the receiver is deceived, only the satellite signals of the corresponding frequency band are affected. Therefore, the deception signals can be identified with the help of other unaffected auxiliary information, including inertial measurement unit IMU, high-precision chip clock, accelerometer, etc. The GNSS system and the auxiliary information system respectively calculate their own information and send it to the information processing module. The information processing module can detect deception by selecting observation quantities and observing whether there are abnormalities in the observation quantities between different systems.

[0050] At present, the deception detection technology for machine learning is mainly based on supervised learning. The input layer is the satellite signal features. Common features include satellite number, signal-to-noise ratio, pseudorange, carrier phase measurement value, Doppler frequency measurement value, receiver clock error and receiver frequency drift. The hidden layer has different structures depending on the machine learning model used. The result of the output layer is a binary classification result, with 1 and 0 representing credible signals and deception signals respectively. However, the features required for machine learning are complex and require a large amount of training data. Therefore, problems such as missing features and insufficient training may occur in practical applications.

[0051] In one embodiment, if Figure 1 As shown, the present application discloses a space-time-frequency based anti-spoofing interference joint detection method, which specifically includes the following steps:

[0052] S1: Receive satellite signals in real time, and output digital intermediate frequency signals after the RF front end, AD conversion, and digital down-conversion. DOA estimation is performed to detect the directions of all signal sources, and the channels are divided by angle using the beamforming criterion.

[0053] In this embodiment, including but not limited to using a decorrelation MUSIC algorithm to perform DOA estimation, detecting all signal source directions, including but not limited to using an LCMV criterion to divide channels by angle;

[0054] Specifically, the theoretical model of the received digital intermediate frequency signal is:

[0055] (1)

[0056] In the formula, is the received intermediate frequency signal, is the sampling period, is the number of cycles, , are the number of real satellite signals and spoofed signal sources, is the number of spoofed satellite signals transmitted by the zth spoofed signal source; , is the steering vector formed by different DOA signals on the antenna, as shown in equations (2) and (3); is Gaussian white noise.

[0057] (2)

[0058] (3)

[0059] In formula (2) and (3), N is the number of oscillators. is the signal DOA, is the carrier wavelength, is the distance between antenna sources.

[0060] , They are real Beidou signal and spoofing signal. The real Beidou signal and deceptive signals The expression for obtaining is:

[0061] (4)

[0062] (5)

[0063] In formula (4) and (5) is the real Beidou signal power, To deceive the signal power; is the real Beidou signal Doppler frequency, To spoof the signal Doppler frequency; It is the real Beidou signal time shift. To deceive the signal time shift; is the real Beidou signal phase, To deceive the signal phase; For the real Beidou signal message, To deceive the signal message is the real Beidou signal pseudo-random noise code PRN, The deceptive signal is pseudo-random noise code PRN.

[0064] When the DOA estimation result has signals at m angles, according to the array signal processing flow, taking a uniform linear array composed of L array elements as an example, the beamforming formula is:

[0065] ,

[0066] k is the sampling number, and the LCMV beamforming criterion is used to divide the signal source direction into channels according to the angle.

[0067] S2: Based on the preset capture rules, a capture search is initiated for the signal in each of the channels, i.e., the digital intermediate frequency signal of each channel, and correlation peak detection and array antenna anti-interference detection are synchronously performed on the signal to obtain the angle information of the signal in each of the channels and the satellite PRN information during the capture process;

[0068] In this embodiment, the signal in each channel is correlated with a local replica code to initiate a capture search;

[0069] Based on a preset first capture threshold, determining whether there is a signal peak value exceeding the first capture threshold;

[0070] If yes, switching to the preset second capture threshold to perform capture search, and judging whether there is a signal peak value exceeding the second capture threshold, and the second capture threshold is less than the first capture threshold;

[0071] If the signal peak value exceeds the second capture threshold again, the capture search start point is offset by a preset base code position according to the captured code phase information and then the capture is performed again;

[0072] If the capture is successful, the current capture result is considered to be in accordance with the capture rules, and is judged to be true information for capture-to-tracking processing; if the capture is unsuccessful, the previous capture result is considered to be in accordance with the capture rules, and is then transferred to tracking processing;

[0073] Furthermore, a first capture threshold D1 and a search window of 2s are set. The first capture threshold D1 is set according to actual application conditions. If there is a peak that meets the capture of the first capture threshold D1, it is switched to the preset smaller second capture threshold D2 for capture, and the search window is set to 40ms for the second capture. If there is a peak exceeding the threshold D2 again, according to the captured code phase information, the search starting point is offset by 2046 chips and the search window is 2046 chips before the third capture. If the peak captured again exceeds the threshold at this time, the third capture is regarded as real information and the capture is converted to tracking processing. If the capture is unsuccessful, the second capture result is converted to tracking processing.

[0074] The size of the three-time search window and the number of offset base codes are preferred implementation schemes of this embodiment in a specific receiver, and can be adjusted according to actual applications during the specific implementation process.

[0075] S3: Performing nulling processing on the signal source direction where two or more satellite signals appear at the same angle.

[0076] In this embodiment, the signal angle and satellite PRN and other information are obtained from the capture process, and the correlation between the signals is calculated. If the correlation exceeds the threshold or two or more satellite signals appear at the same angle, the direction is determined to be a deception interference source, and zero-steering processing is performed in this direction to reduce the gain in this direction, suppress the deception signal, and mark the channel signal without entering the solution.

[0077] S4: performing Doppler frequency shift consistency detection and signal power calculation on the signal of the rotation tracking, identifying the deception signal and feeding it back to the antenna array for filtering processing;

[0078] S5: Perform Doppler frequency shift consistency detection and signal power calculation on the signal of the rotation tracking, identify the deception signal and feed it back to the antenna array for filtering processing.

[0079] In this embodiment, the signal of the rotation tracking is tracked, the loop filter outputs the Doppler measurement value, the Doppler observation value of the signal is obtained, and the variance under the preset window time is counted to construct the Doppler consistency detection, and the relationship between the output of the code loop loop filter and the corresponding output of the carrier loop filter is used:

[0080] ,

[0081] Should roughly follow a Gaussian distribution;

[0082] in is the C / A code rate, is the signal carrier frequency, is the output of the code loop filter at time k, is the output of the carrier loop filter at time k, and its variance is:

[0083] ,

[0084] , The output variances of the DLL and PLL loop filters are

[0085] The Neyman-Pearson criterion is used to perform test statistics and judgement, to identify abnormal changes in Doppler frequency, to detect and identify the signal with abnormal changes in Doppler frequency, to mark it as a spoofing signal, to associate the channel of the current spoofing signal according to the detection result, and to feed back to the antenna array for nulling processing;

[0086] The signal power of the signal is calculated synchronously, and the power of the instant branch is divided by the noise power, where the power is the sum of squares of the integral values, and the mean is statistically calculated. When it is detected that the difference between the signal power and the preset normal range value is greater than the preset deviation threshold, the channel of the current spoofing signal is associated according to the detection result, and fed back to the antenna array for null processing.

[0087] Furthermore, the signal power is characterized by dividing the current branch power by the noise power, which is a preferred implementation scheme of this embodiment in a specific receiver. During the specific implementation process, it can be adjusted according to actual applications.

[0088] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0089] In one embodiment, a space-time-frequency based anti-spoofing interference joint detection system is provided, which is used to perform a space-time-frequency based anti-spoofing interference joint detection method.

[0090] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 2 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a space-time-frequency-based anti-deception interference joint detection method is implemented.

[0091] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a space-time-frequency-based anti-deception interference joint detection method is implemented.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a space-time-frequency based anti-spoofing interference joint detection method is implemented.

[0093] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0094] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0095] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A space-time-frequency based anti-spoofing interference joint detection method, characterized in that: include: Acquire the signal source direction of the received satellite signal, and divide the signal source direction into channels according to angles based on a preset beamforming criterion; Based on the preset capture rules, a capture search is initiated for the signal in each of the channels, and peak detection and array antenna anti-interference detection are synchronously performed on the signal to obtain the angle information and satellite PRN information of the satellite signal in each of the channels during the capture process; Performing nulling processing on the signal source direction where two or more satellite signals appear at the same angle; Outputting a capture result based on the capture rule, and tracking the capture result; as well as The Doppler frequency shift consistency detection and signal power calculation are performed on the rotation tracking signal, and the deception signal is identified and fed back to the antenna array for filtering processing.

2. The space-time-frequency-based anti-spoofing interference joint detection method according to claim 1, characterized in that: The obtaining of the signal source direction of the received satellite signal comprises: The RF front end receives the satellite signal and outputs a digital intermediate frequency signal after AD conversion and digital down-conversion processing; and The digital intermediate frequency signal is subjected to DOA estimation processing to detect and obtain all the signal source directions.

3. The space-time-frequency-based anti-spoofing interference joint detection method according to claim 2, characterized in that: The step of dividing the signal source direction into channels according to angles based on a preset beamforming criterion includes: It is preset that there are signals at m angles in the estimation result of the DOA estimation process, based on a preset signal processing array, the signal processing array includes a uniform linear array composed of L array elements, and the formula of the beamforming criterion is: , In the formula, k is the sampling number, is the signal obtained after beamforming, is the weight vector of the antenna array under a certain angle signal, represents the conjugate transpose of a matrix, is the received signal; Channels are divided by angle using preset beamforming criteria.

4. The space-time-frequency based anti-spoofing interference joint detection method according to claim 1, characterized in that: The initiating a capture search for the signal in each of the channels based on a preset capture rule includes: Performing correlation operation on the signal in each of the channels and the local replica code to initiate a capture search; Based on a preset first capture threshold, determining whether there is a signal peak value exceeding the first capture threshold; If yes, switching to the preset second capture threshold to perform capture search, and judging whether there is a signal peak value exceeding the second capture threshold, and the second capture threshold is less than the first capture threshold; If the signal peak value exceeds the second capture threshold again, the capture search start point is offset by a preset base code position according to the captured code phase information and then the capture is performed again; If the capture is successful, the current capture result is judged to be in accordance with the capture rules and is determined to be true information for capture and tracking processing. If the capture is unsuccessful, the previous capture result is judged to be in accordance with the capture rules and is transferred to tracking processing.

5. The space-time-frequency based anti-spoofing interference joint detection method according to claim 1, characterized in that: The signal of the rotation tracking is subjected to Doppler frequency shift consistency detection and signal power calculation, and the deception signal is identified and fed back to the antenna array for filtering processing, including: Track the signal being tracked, obtain the Doppler observation of the signal, and count the variance under a preset window time, detect and identify the signal with abnormal Doppler frequency change, mark it as a spoofing signal, associate the channel of the current spoofing signal according to the detection result, and feed it back to the antenna array for nulling processing; The signal power of the signal is calculated synchronously, the power of the instant branch is divided by the noise power, and the mean is statistically calculated. When it is detected that the difference between the signal power and the preset normal range value is greater than the preset deviation threshold, the channel of the current spoofing signal is associated according to the detection result and fed back to the antenna array for null processing.

6. A space-time-frequency based anti-spoofing interference joint detection system, characterized in that: Used to execute a space-time-frequency based anti-spoofing interference joint detection method as described in any one of claims 1 to 5.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the space-time-frequency based anti-deception interference joint detection method as described in any one of claims 1 to 5 are implemented.

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