Multi-parameter-based non-inductive signal interference identification method, system and device

Abstract

The invention relates to the technical field of signal interference identification, and provides a non-inductive signal interference identification method, system and device based on multiple parameters. Comprising the following steps: acquiring a sky navigation equipment parameter, an inertial navigation equipment parameter, a receiver equipment parameter and an electromagnetic log parameter of a sensor suspected to be interfered; performing out-of-tolerance identification detection according to the sky navigation equipment parameters, the inertial navigation equipment parameters, the receiver equipment parameters and the electromagnetic log parameters to obtain a first detection result; performing receiver state detection on the receiver equipment to obtain a second detection result; and performing comprehensive judgment according to the first detection result and the second detection result to obtain whether the sensor is interfered, and obtaining a sensor interference judgment result. Interference identification is carried out by adopting a strategy of'forward recovery and majority voting ', signal change can be sensed sensitively, and signal interference is detected and identified so that navigation parameters are prevented from being damaged.

Description

Technical Field

[0001] The present invention relates to the technical field of signal interference identification, and provides a multi-parameter-based non-sensing signal interference identification method, system and device. Background Art

[0002] At present, the commonly used method is interference suppression. At this time, the interference equipment transmits high-power interference signals to the space within a certain range, drowning out the real receiver signal, making it impossible for the receiver to receive and capture the available receiver signal, making it impossible to locate.

[0003] With the changes in support needs and mission tasks, higher requirements are placed on integrated management equipment. The actual position of the receiver is obtained with the help of external means to ensure that the interference signal is synchronized with the real signal. The signal entry cannot cause large fluctuations in the receiver and is not discovered, thereby improving the efficiency of tracking loop support.

[0004] Currently, multi-parameter, sensorless signal interference identification and safety control methods rely solely on sensor data to detect and identify signal interference, thereby protecting navigation parameters from damage. A search of existing domestic documentation reveals a lack of such a method. Therefore, a signal interference identification method implementation solution is provided. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the related art. To this end, the present invention provides a multi-parameter-based non-sensing signal interference identification method, system, and device, which can sensitively perceive signal changes, detect and identify signal interference, and prevent navigation parameters from being damaged.

[0006] The present invention provides a multi-parameter non-sensing signal interference identification method, comprising: S1: Obtain the antenna equipment parameters, inertial navigation equipment parameters, receiver equipment parameters and electromagnetic speed log parameters of the sensor suspected to be interfered with; S2: performing an out-of-tolerance identification test based on the antenna guide device parameters, the inertial navigation device parameters, the receiver device parameters, and the electromagnetic odometer parameters to obtain a first test result; S3: Performing a receiver status detection on the receiver device to obtain a second detection result; S4: Perform a comprehensive judgment based on the first detection result and the second detection result to determine whether the sensor is interfered with, and obtain a sensor interference judgment result.

[0007] According to a multi-parameter non-sensing signal interference identification method provided by the present invention, step S1 includes: Obtaining a position parameter from the antenna device parameters of the sensor; Obtaining position parameters and velocity parameters from the inertial navigation device parameters of the sensor; Obtain the status parameter, position parameter, and speed parameter in the receiver device parameters of the sensor; Obtain the speed parameter in the electromagnetic log of the sensor.

[0008] According to a multi-parameter non-inductive signal interference recognition method provided by the present invention, step S2 includes: S21: Perform out-of-tolerance identification detection based on the position parameter of the receiver device and the position parameter of the inertial navigation device to obtain the result of comparator F1; S22: Perform out-of-tolerance identification detection based on the position parameter of the receiver device and the position parameter of the celestial navigation device to obtain the result of comparator F2; S23: Perform out-of-tolerance identification detection based on the speed parameter of the receiver device and the speed parameter of the inertial navigation device to obtain the result of comparator F3; S24: Perform out-of-tolerance identification detection based on the speed parameter of the receiver device and the speed parameter of the electromagnetic log to obtain the result of comparator F4; S25: Perform out-of-tolerance identification decision based on the results of comparator F1, comparator F2, comparator F3, and comparator F4 to obtain the first detection result.

[0009] According to a multi-parameter non-inductive signal interference recognition method provided by the present invention, the out-of-tolerance identification detection step in step S2 is: S201: Set the initial state of the comparator to A; S202: When the state of the comparator is in state A, sample at the sampling frequency parameter, use the sliding window method for comparison and judgment. When the proportion of out-of-tolerance sample numbers is greater than the first out-of-tolerance threshold, set the state of the comparator to B; when the proportion of out-of-tolerance sample numbers is less than or equal to the first out-of-tolerance threshold, set the state of the comparator to A; S203: When the state of the comparator is in state B, sample at the sampling frequency parameter, use the sliding window method for comparison and judgment. When the proportion of out-of-tolerance sample numbers is less than or equal to the second out-of-tolerance threshold, set the state of the comparator to state A; when the proportion of out-of-tolerance sample numbers is greater than the second out-of-tolerance threshold, set the state of the comparator to state B.

[0010] According to a multi-parameter non-inductive signal interference recognition method provided by the present invention, the judgment method of the first detection result in step S25 is shown in Table 1: Table 1 First Detection Result Judgment Table Among them, L represents strong interference and is not credible; M represents there is certain interference and there is a risk of being interfered; S represents low interference and is highly credible.

[0011] A multi-parameter non-intrusive signal interference recognition method provided by the present invention, the steps of the sliding window method include: S2001: According to the sampling frequency to obtain the first data sequence with a length of and the second data sequence and , wherein, is the data of the first data sequence, is the data of the second data sequence, is the data ordinal number, ; Specifically, the first data sequence is the data of the receiver device corresponding to the comparator, and the second data sequence is the data of another device corresponding to the comparator; S2002: Calculate the comparison difference and determine whether the comparison difference exceeds the difference threshold range : wherein, is the minimum value of the difference threshold range, is the maximum value of the difference threshold range; S2003: Calculate the proportion of the number of out-of-tolerance samples , wherein, is the comparison difference exceeding the difference threshold range the number of data.

[0012] A multi-parameter non-intrusive signal interference recognition method provided by the present invention, step S3 includes: S31: Judge the state of the receiver. If the receiver is in a non-autonomous state, the second detection result is L; S32: When the receiver data is invalid or the receiver is in the autonomous mode for a duration greater than or equal to 8 hours, the second detection result is M; S33: The receiver data is valid, and the state of the receiver is in the autonomous mode, and the duration of the receiver in the autonomous mode is less than 8 hours, the second detection result is S; wherein, L represents that strong interference is not credible; M represents that there is a certain interference and there is a risk of being interfered; S represents that low interference is highly credible.

[0013] A multi-parameter non-intrusive signal interference recognition method provided by the present invention, the method of comprehensive judgment is shown in Table 2: Table 2 Comprehensive Judgment Result Table Among them, L indicates strong interference and is not credible; M indicates there is a certain degree of interference and there is a risk of being interfered; S indicates low interference and high credibility.

[0014] The present invention also provides a multi-parameter non-intrusive signal interference identification system, including: A data acquisition module, configured to acquire the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of the sensor suspected of being interfered. A detection module, configured to perform out-of-tolerance identification detection according to the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result; perform receiver status detection on the receiver device to obtain a second detection result. An interference judgment module, configured to perform comprehensive judgment according to the first detection result and the second detection result to determine whether the sensor is interfered, and obtain a sensor interference judgment result.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps of any one of the above-mentioned multi-parameter non-intrusive signal interference identification methods.

[0016] One or more of the above technical solutions in the embodiments of the present invention have at least one of the following technical effects: A multi-parameter non-intrusive signal interference identification method, system, and device provided by the present invention can sensitively sense signal changes, detect and identify signal interference, and prevent navigation parameters from being damaged by adopting the strategy of "forward recovery, majority voting".

[0017] The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a flowchart of a multi-parameter non-intrusive signal interference identification method provided by the present invention.

[0020] Figure 2 It is a structural block diagram of a multi-parameter non-intrusive signal interference recognition device provided by the present invention.

[0021] Figure 3 It is a schematic structural diagram of an electronic device provided by the present invention.

[0022] Reference numerals: 101, data acquisition module; 102, detection module; 103, interference judgment module; 810, processor; 820, communication interface; 830, memory; 840, communication bus. Detailed implementation manners

[0023] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0024] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without conflict, those skilled in the art can combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0025] The following is combined with Figures 1 to 3 to describe the present invention.

[0026] Embodiment As Figure 1 shown, Figure 1 It is a schematic flow diagram of a multi-parameter non-intrusive signal interference recognition method provided by the present invention, including the following steps: S1: Obtain the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of the sensor suspected of being interfered; S2: Perform out-of-tolerance identification detection according to the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result; S3: Detect the receiver status of the receiver device to obtain a second detection result; S4: Based on the first detection result and the second detection result, make a comprehensive judgment to determine whether the sensor is interfered, and obtain a sensor interference judgment result.

[0027] Specifically, step S1 includes: Obtain the position parameter in the celestial navigation device parameters of the sensor; Obtain the position parameter and speed parameter in the inertial navigation device parameters of the sensor; Obtain the status parameter, position parameter and speed parameter in the receiver device parameters of the sensor; Obtain the speed parameter in the electromagnetic log of the sensor.

[0028] Specifically, step S2 includes: S21: Perform out-of-tolerance identification detection based on the position parameter of the receiver device and the position parameter of the inertial navigation device to obtain the result of comparator F1; S22: Perform out-of-tolerance identification detection based on the position parameter of the receiver device and the position parameter of the celestial navigation device to obtain the result of comparator F2; S23: Perform out-of-tolerance identification detection based on the speed parameter of the receiver device and the speed parameter of the inertial navigation device to obtain the result of comparator F3; S24: Perform out-of-tolerance identification detection based on the speed parameter of the receiver device and the speed parameter of the electromagnetic log to obtain the result of comparator F4; S25: Based on the results of comparator F1, comparator F2, comparator F3 and comparator F4, perform out-of-tolerance identification decision to obtain a first detection result.

[0029] Among them, the strategy of "forward recovery, majority voting" is used for interference identification. Specifically, the steps of out-of-tolerance identification detection are as follows: S201: Set the initial state of the comparator to A; S202: When the state of the comparator is in state A, sample at the sampling frequency parameter, use the sliding window method for comparison and judgment. When the proportion of out-of-tolerance sample quantity is greater than the first out-of-tolerance threshold, set the state of the comparator to B; when the proportion of out-of-tolerance sample quantity is less than or equal to the first out-of-tolerance threshold, set the state of the comparator to A. In the embodiment of the present invention, the first out-of-tolerance threshold is set to 10%. Specifically, the steps of the sliding window method include: S2001: According to the sampling frequency To obtain a first data sequence with a length of And a second data sequence And a second data sequence , Wherein, is the data of the first data sequence, is the data of the second data sequence, is the data ordinal number, ; Specifically, the first data sequence is the data of the receiver device corresponding to the comparator, and the second data sequence is the data of another device corresponding to the comparator; S2002: Calculate the comparison difference and determine whether the comparison difference exceeds the difference threshold range : Wherein, is the minimum value of the difference threshold range, is the maximum value of the difference threshold range; S2003: Calculate the proportion of the number of out-of-tolerance samples , Wherein, is the comparison difference exceeding the difference threshold range the number of data.

[0030] Specifically, in the embodiment of the present invention, position continuity detection is performed. The continuity detection strategy adopts a smooth and effective data frame. The last valid data before this detection is counted as the original valid data, and the first frame, the second frame... and then the 60th frame (in the embodiment of the present invention ) are judged. If all exceed the range, it is considered that the receiver position parameter is abnormal and the receiver data is regarded as invalid; if the difference between the first frame, the second frame... and other data and the original valid data is within the threshold range, the position of the receiver and the inertial navigation (celestial navigation) is judged. If there is within , the receiver data is trusted. If it is outside the threshold, only the receiver data is regarded as abnormal, but the receiver data is not considered invalid. Among them, the receiver and inertial navigation position difference threshold range of comparator F1 is [0, 2) nautical miles, and the receiver and celestial navigation position difference threshold range of comparator F2 is [0, 2.00178) nautical miles.

[0031] Specifically, in the embodiment of the present invention, speed continuity detection is performed. The continuity detection strategy adopts a smooth and effective data frame. The last valid data before this detection is counted as the original valid data, and the first frame, the second frame... and then 60 frames are judged. If all exceed If it is outside the range, the receiver position parameter is considered abnormal and the receiver data is regarded as invalid; if the difference between the data of the first frame, the second frame, etc. and the original valid data is within the threshold range, then the speeds of the receiver and the inertial navigation are judged. If there is within it, the receiver data is trusted. If it is outside the threshold, only the receiver data is regarded as abnormal, but the receiver data is not considered invalid. The threshold range of the speed difference between the receiver and the inertial navigation is [0, 0.8) knots, and the threshold range of the speed difference between the receiver and the electromagnetic log is [0, 0.8) knots.

[0032] S203: When the state of the comparator is in state B, sampling is performed at the sampling frequency parameter, and the sliding window method is used for comparison and judgment. When the proportion of out-of-tolerance sample numbers is less than or equal to the second out-of-tolerance threshold, the state of the comparator is set to state A; when the proportion of out-of-tolerance sample numbers is greater than the second out-of-tolerance threshold, the state of the comparator is set to state B. In the embodiment of the present invention, the second out-of-tolerance threshold is set to 5%.

[0033] Specifically, the judgment method for the first detection result in step S25 is shown in Table 1: Table 1 First Detection Result Judgment Table Among them, L represents strong interference and is not trustworthy; M represents certain interference and there is a risk of being interfered; S represents low interference and is highly trustworthy.

[0034] Specifically, step S3 includes: S31: Judge the state of the receiver. If the receiver is in a non-autonomous state, the second detection result is L; S32: When the receiver data is invalid or the receiver is in the autonomous mode for a duration greater than or equal to 8 hours, the second detection result is M; S33: The receiver data is valid, the state of the receiver is in the autonomous mode, and the duration of the receiver in the autonomous mode is less than 8 hours, the second detection result is S.

[0035] Among them, L represents strong interference and is not trustworthy; M represents certain interference and there is a risk of being interfered; S represents low interference and is highly trustworthy.

[0036] Specifically, the judgment method described in step S4 is shown in Table 2: Table 2 Comprehensive Judgment Result Table Specifically, as shown in Table 3, Table 3 is the specific experimental result of this embodiment: Table 3 Experimental Results of the Embodiment of the Present Invention As shown in Table 3, the experimental results of the present invention are very accurate, which can control the misjudgment rate below 5% and increase the correct recognition rate to 90% - 95%.

[0037] As Figure 2 shown, the present invention provides a structural block diagram of a multi-parameter non-intrusive signal interference recognition device, including the following modules: A data acquisition module 101, configured to acquire the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of a sensor suspected of being interfered. A detection module 102, configured to perform out-of-tolerance recognition detection based on the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result; and perform a receiver status detection on the receiver device to obtain a second detection result. An interference judgment module 103, configured to comprehensively judge based on the first detection result and the second detection result to determine whether the sensor is interfered, and obtain a sensor interference judgment result.

[0038] Figure 3 Illustrates a schematic physical structure diagram of an electronic device. As Figure 3 shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logical instructions in the memory 830 to execute a multi-parameter non-intrusive signal interference recognition method, and the method includes: S1: Acquire the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of a sensor suspected of being interfered. S2: Perform out-of-tolerance recognition detection based on the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result. S3: Perform a receiver status detection on the receiver device to obtain a second detection result. S4: Based on the first detection result and the second detection result, a comprehensive judgment is made to determine whether the sensor is interfered, and a sensor interference judgment result is obtained. In addition, when the logical instructions in the above-mentioned memory 830 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. And the aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0039] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0040] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

[0042] It should be noted that the embodiments of the present disclosure can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic: the software part can be stored in a memory and executed by a suitable instruction execution system such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code is provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.

[0043] In addition, although the operations of the method of the present disclosure are described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. On the contrary, the order of execution of the steps depicted in the flowchart can be changed. Additionally or alternatively, certain steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution. It should also be noted that the features and functions of two or more devices according to the present disclosure can be embodied in one device. Conversely, the features and functions of one device described above can be further divided and embodied by multiple devices.

[0044] Although the present disclosure has been described with reference to several specific embodiments, it should be understood that the present disclosure is not limited to the specific embodiments disclosed. The present disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A multi-parameter non-sensing signal interference identification method, characterized in that: Including: S1: Obtain the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of the sensor suspected of being interfered with; S2: Perform out-of-tolerance identification detection based on the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result; S3: Perform receiver status detection on the receiver device to obtain a second detection result; S4: Perform comprehensive judgment based on the first detection result and the second detection result to determine whether the sensor is interfered with, and obtain a sensor interference judgment result.

2. The multi-parameter non-intrusive signal interference recognition method according to claim 1, characterized in that Step S1 includes: Obtain the position parameters in the celestial navigation device parameters of the sensor; Obtain the position parameters and speed parameters in the inertial navigation device parameters of the sensor; Obtain the status parameters, position parameters, and speed parameters in the receiver device parameters of the sensor; Obtain the speed parameters in the electromagnetic log of the sensor.

3. The method for identifying signal interference based on multi-parameters without induction according to claim 2, characterized in that: Step S2 includes: S21: Perform out-of-tolerance identification detection based on the position parameters of the receiver device and the position parameters of the inertial navigation device to obtain the result of comparator F1; S22: Perform out-of-tolerance identification detection based on the position parameters of the receiver device and the position parameters of the celestial navigation device to obtain the result of comparator F2; S23: Perform out-of-tolerance identification detection based on the speed parameters of the receiver device and the speed parameters of the inertial navigation device to obtain the result of comparator F3; S24: Perform out-of-tolerance identification detection based on the speed parameters of the receiver device and the speed parameters of the electromagnetic log to obtain the result of comparator F4; S25: Perform out-of-tolerance identification judgment based on the results of comparator F1, comparator F2, comparator F3, and comparator F4 to obtain a first detection result.

4. The method for identifying signal interference based on multi-parameters without induction according to claim 3, characterized in that: The out-of-tolerance identification detection steps in step S2 are: S201: Set the initial state of the comparator to A; S202: When the state of the comparator is in state A, sample at the sampling frequency parameter, use the sliding window method for comparison and judgment. When the proportion of out-of-tolerance sample numbers is greater than the first out-of-tolerance threshold, set the state of the comparator to B; when the proportion of out-of-tolerance sample numbers is less than or equal to the first out-of-tolerance threshold, set the state of the comparator to A; S203: When the state of the comparator is in state B, sample at the sampling frequency parameter, use the sliding window method for comparison and judgment. When the proportion of out-of-tolerance sample numbers is less than or equal to the second out-of-tolerance threshold, set the state of the comparator to state A; when the proportion of out-of-tolerance sample numbers is greater than the second out-of-tolerance threshold, set the state of the comparator to state B.

5. The method for identifying multi-parameter non-intrusive signal interference according to claim 4, characterized in that, The judgment method of the first detection result in step S25 is shown in Table 1: Table 1 First Detection Result Judgment Table Among them, L represents strong interference and is not credible; M represents there is certain interference and there is a risk of being interfered; S represents low interference and is highly credible.

6. The method for identifying multi-parameter non-intrusive signal interference according to claim 4, wherein, The steps of the sliding window method include: S2001: Obtain a first data sequence and a second data sequence with lengths of and respectively according to a preset sampling frequency for the sampling frequency and a second data sequence ​ ， Among them, is the data of the first data sequence, is the data of the second data sequence, is the data ordinal number, ; Specifically, the first data sequence is the data of the receiver device corresponding to the comparator, and the second data sequence is the data of another device corresponding to the comparator; S2002: Calculate and compare the difference And determine whether the comparison difference exceeds the difference threshold range : Among them, is the minimum value of the difference threshold range, is the maximum value of the difference threshold range; S2003: Calculate the proportion of out-of-tolerance samples , Among them, is the comparison difference exceeding the difference threshold range the number of data.

7. A multi-parameter non-intrusive signal interference recognition method according to claim 6, characterized in that, Step S3 includes: S31: Judge the state of the receiver. If the receiver is in a non-autonomous state, the second detection result is L; S32: When the receiver data is invalid or the receiver has been in the autonomous mode for a duration greater than or equal to 8 hours, the second detection result is M; S33: When the receiver data is valid, the receiver is in the autonomous mode, and the receiver has been in the autonomous mode for a duration less than 8 hours, the second detection result is S; wherein, L indicates that strong interference is untrustworthy; M indicates that there is certain interference and there is a risk of being interfered; S indicates that low interference is highly trustworthy.

8. A multi-parameter non-intrusive signal interference recognition method according to claim 1, characterized in that The method of the comprehensive judgment is shown in Table 2: Table 2 Comprehensive Judgment Result Table wherein, L indicates that strong interference is untrustworthy; M indicates that there is certain interference and there is a risk of being interfered; S indicates that low interference is highly trustworthy.

9. A multi-parameter non-intrusive signal interference recognition system for implementing a multi-parameter non-intrusive signal interference recognition method according to any one of claims 1 to 8, characterized in that, including: a data acquisition module, configured to acquire the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters of the sensor suspected of being interfered; a detection module, configured to perform out-of-tolerance identification detection according to the celestial navigation device parameters, inertial navigation device parameters, receiver device parameters, and electromagnetic log parameters to obtain a first detection result; perform receiver status detection on the receiver device to obtain a second detection result; an interference judgment module, configured to perform comprehensive judgment according to the first detection result and the second detection result to determine whether the sensor is interfered, and obtain a sensor interference judgment result.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for identifying multi-parameter non-inductive signal interference according to any one of claims 1 to 8.

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