Unmanned aerial vehicle countering signal identification method and signal identification device

Abstract

The invention provides an unmanned aerial vehicle countering signal identification method and a signal identification device. The unmanned aerial vehicle countering signal identification method comprises the following steps: receiving to-be-identified signal information in a plurality of preset frequency bands; analyzing to obtain GPS information in the signal information to be identified; judging whether an error range of the GPS information and local preset GPS information meets a preset requirement or not, and if the error range meets the preset requirement, judging that a countering signal of the unmanned aerial vehicle exists in the signal information to be identified; if the error range does not meet the preset requirement, generating a spectrogram of the to-be-identified signal information; and judging whether the countering signal of the unmanned aerial vehicle exists in the corresponding to-be-identified signal information according to the image features of the spectrogram, and if so, judging that the countering signal of the unmanned aerial vehicle exists in the to-be-identified signal information. The GPS information and the spectrogram are utilized to comprehensively identify the countering signal of the unmanned aerial vehicle in the plurality of preset frequency bands, so that the accuracy of identifying the countering signal of the unmanned aerial vehicle can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal recognition, and in particular to a method for recognizing a counter-signal of an unmanned aerial vehicle and a signal recognition device. Background Art

[0002] With the rapid development of drone technology, drones have been widely used in agriculture, photography, scientific monitoring and other fields. However, the rapid popularization of drones has also brought many security and privacy issues, so some places may privately set up and install anti-drone systems. When turned on, the anti-drone system will seriously affect the surrounding electromagnetic environment, cause serious interference to the drone's communication, and cause the drone to be forced to land or return, affecting the drone's mission execution in the area.

[0003] Therefore, before a UAV performs a mission, determining whether there is an anti-UAV signal in the mission area has an important impact on whether the UAV can successfully perform the mission. Summary of the invention

[0004] An object of the present invention is to provide a method and a signal recognition device for identifying a UAV counter-signal, which are helpful to improve the accuracy of identifying the UAV counter-signal.

[0005] In particular, the present invention provides a method for identifying a countermeasure signal of a drone, comprising:

[0006] Receiving information of signals to be identified within a plurality of preset frequency bands;

[0007] Analyze and obtain GPS information in the signal information to be identified;

[0008] Determine whether the error range between the GPS information and the locally preset GPS information meets the preset requirements; if so, determine that the signal information to be identified contains a counter-signal of the drone; if the error range does not meet the preset requirements, generate a spectrum graph of the signal information to be identified; determine whether the corresponding signal information to be identified contains a counter-signal of the drone based on the image features of the spectrum graph; if so, determine that the signal information to be identified contains a counter-signal of the drone.

[0009] Optionally, the step of judging whether the corresponding signal information to be identified contains a counter-signal of a drone according to the image features of the spectrum graph includes:

[0010] Detect whether there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold. If so, determine that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of a drone.

[0011] Optionally, before the step of judging whether the corresponding signal information to be identified contains a counter-signal of a drone according to the image features of the spectrum graph, the step includes:

[0012] Preliminarily determine whether the signal information to be identified has a counter signal in a preset manner. If so, execute the step of determining whether the corresponding signal information to be identified has a counter signal of a drone based on the image features of the spectrum graph. If not, determine that the signal information to be identified does not have a counter signal of a drone.

[0013] Optionally, the step of preliminarily determining whether the signal information to be identified contains a counter signal in a preset manner includes:

[0014] The spectrum diagram is compared with the preset spectrum template. If they do not match, it is preliminarily determined that the signal information to be identified contains a counter signal. If they match, it is determined that the signal information to be identified does not contain a counter signal of the drone.

[0015] Optionally, before the step of preliminarily determining whether the signal information to be identified contains a counter signal, the step includes:

[0016] Detect whether there is a point in the spectrum graph whose power exceeds a preset threshold. If so, preliminarily determine that there is a counter signal in the signal information to be identified. If not, determine that there is no counter signal of the drone in the signal information to be identified.

[0017] Optionally, when it is detected that there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold, the method for identifying the drone countermeasure signal further includes:

[0018] Determine whether the signal information to be identified corresponding to the spectrum graph belongs to a preset drone communication frequency band. If so, determine that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of a drone.

[0019] Optionally, the step of determining whether the error range between the GPS information and the locally preset GPS information meets a preset requirement includes:

[0020] Comparing the time information in the GPS information with the local time, and comparing the location information in the GPS information with the local location;

[0021] If the difference between the time information in the GPS information and the local time is greater than a preset time threshold, or if the difference between the location information in the GPS information and the local location is greater than a preset distance threshold, it is determined that the error range between the GPS information and the locally preset GPS information meets the preset requirements.

[0022] Optionally, after the step of determining whether the signal information to be identified contains a counter-signal of a drone, the step includes:

[0023] The frequency, bandwidth, power and transmission status of the countermeasure signal are counted.

[0024] Optionally, after the step of receiving information of signals to be identified in multiple frequency bands, the step further includes:

[0025] Determine whether the signal information to be identified contains a GPS signal. If so, perform the step of parsing to obtain the GPS information in the signal information to be identified. If not, perform the step of generating a spectrum diagram of the signal information to be identified.

[0026] In another aspect of the present application, a drone countermeasure signal recognition device is also provided, comprising:

[0027] A signal processing module includes a memory, a processor, and a machine executable program stored in the memory and running on the processor, and when the processor executes the machine executable program, the method for identifying the drone countermeasure signal according to any of the above items is implemented.

[0028] The method and signal recognition device for identifying the counter-signal of a drone of the present invention receives the signal information to be identified of multiple preset frequency bands, parses and obtains the GPS information in the signal information to be identified, determines whether the error range between the GPS information and the locally preset GPS information meets the preset requirements, and if the error range meets the preset requirements, determines that the signal information to be identified has the counter-signal of the drone, and if the error range does not meet the preset requirements, generates a spectrum diagram of the signal information to be identified, and determines whether the corresponding signal information to be identified has the counter-signal of the drone according to the image features of the spectrum diagram, and if so, determines that the signal information to be identified has the counter-signal of the drone. That is to say, the scheme can receive the signal information to be identified of multiple preset frequency bands, and use the GPS information and the spectrum diagram to comprehensively identify the signal information to be identified of each preset frequency band in multiple preset frequency bands to identify the counter-signal of the drone, thereby realizing the identification of the counter-signal in multiple dimensions, and can more comprehensively and effectively determine whether there is the counter-signal of the drone in the monitoring area, which helps to improve the accuracy of identifying the counter-signal of the drone, reduce the occurrence of the situation that the counter-signal of the drone is missed due to the monitoring of a single frequency band, and further helps to improve the reliability of the subsequent drone task execution.

[0029] Furthermore, because in the same frequency band, in addition to the drone counter-signal, there may also be ordinary WIFI signals, public communication signals and other signals with similar frequencies. Therefore, if the presence of a drone counter-signal is simply identified from the presence or absence of a specific frequency signal, it is easy to cause signal misjudgment. Therefore, by detecting whether there are a continuous preset number of points with power greater than a preset threshold in the spectrum graph, if there are a continuous preset number of points with power greater than the preset threshold, it is determined that the signal information to be identified corresponding to the spectrum graph contains a drone counter-signal, so that it can more accurately determine whether there is a drone counter-signal, further improving the accuracy and reliability of monitoring.

[0030] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0032] Figure 1 is a schematic flow chart of a method for identifying a drone countermeasure signal according to an embodiment of the present invention;

[0033] Figure 2 is a schematic flow chart of determining whether GPS information meets preset requirements in a method for identifying a drone countermeasure signal according to an embodiment of the present invention;

[0034] Figure 3 is a schematic flow chart of a method for identifying a drone countermeasure signal according to another embodiment of the present invention;

[0035] Figure 4 is a schematic flow chart of preliminarily determining whether there is a counter signal in a method for identifying a counter signal of a drone according to another embodiment of the present invention;

[0036] Figure 5 is a schematic flow chart of a method for identifying a drone countermeasure signal according to yet another embodiment of the present invention;

[0037] Figure 6 is a schematic diagram of a method for identifying a drone countermeasure signal according to yet another embodiment of the present invention;

[0038] Figure 7 is a schematic block diagram of a UAV countermeasure signal recognition device according to an embodiment of the present invention;

[0039] Figure 8The figure is a schematic block diagram of a signal processing module in a UAV countermeasure signal recognition device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] It should be understood by those skilled in the art that the embodiments described below are only some embodiments of the present invention, rather than all embodiments of the present invention, and these embodiments are intended to explain the technical principles of the present invention, rather than to limit the protection scope of the present invention. Based on the embodiments provided by the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should still fall within the protection scope of the present invention.

[0041] It should be noted that, in the description of the present invention, each functional module can be a physical module composed of multiple structures, components or electronic components, or a virtual module composed of multiple programs; each functional module can be a module that exists independently of each other, or a module divided according to the function of an integral module. It should be understood by those skilled in the art that, under the premise of being able to implement the technical solution described in the present invention, the composition, implementation and positional relationship of each functional module will not deviate from the technical principle of the present invention no matter how it changes, and therefore should fall within the protection scope of the present invention.

[0042] It should be noted that the logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or equipment (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or equipment and execute instructions), or used in combination with these instruction execution systems, devices or equipment.

[0043] The flow chart provided by the present embodiment is not intended to indicate that the operation of the method will be performed in any particular order, or that all operations of the method are included in all every case. In addition, the method may include additional operations. Within the scope of the technical thinking provided by the present embodiment method, additional changes may be made to the above method.

[0044] like Figure 1 As shown, in one embodiment, the method for identifying the drone countermeasure signal generally includes:

[0045] Step S101, receiving the signal information to be identified in multiple preset frequency bands. Specifically, the counter-signal of the drone can interfere with the normal signals of different frequency bands such as the positioning and remote control of the drone, for example, the commonly used remote control signal bands such as 2.4GHz (gigahertz) and 5.8GHz for drones, and the L1 band (center frequency is 1575.42MHz (megahertz)) and L2 band (center frequency is 1227.60MHz (megahertz)) for the positioning and navigation system. Therefore, the drone counter-signals that interfere with different signals will belong to different frequency bands. Therefore, by receiving signal information in multiple preset frequency bands, it is possible to more comprehensively analyze whether there are drone counter-signals in the monitoring area. The preset frequency band can be set to a common frequency band where counter-signals may exist.

[0046] Step S102, determine whether the signal information to be identified contains a GPS (Global Positioning System) signal, if so, execute step S103, if not, execute step S105. Specifically, in addition to the drone counter signal that interferes with the normal communication of the drone, the drone's counter signal can also be a forged GPS signal sent to the drone. The forged GPS signal will carry false GPS information, thereby causing the drone to deviate from the original route.

[0047] Therefore, for the signal information to be identified in each preset frequency band, it is first determined whether a GPS signal is included. For example, the determination can be made by checking whether the signal is a common GPS signal frequency, or checking whether the modulation method of the signal meets the modulation method of the GPS signal.

[0048] Step S103, parse and obtain GPS information in the signal information to be identified. Specifically, if there is a GPS signal, parse and obtain GPS information carried by the GPS signal, including time information and location information.

[0049] Step S104, determine whether the error range between the GPS information and the local preset GPS information meets the preset requirements, if yes, execute step S107, if not, execute step S105. Specifically, the local preset GPS information is the location of the installation location of the drone counter signal recognition device and the time when the drone counter signal recognition device is synchronized with the server in real time.

[0050] Reference Figure 2 Specifically, this step includes:

[0051] Step S201, compare the time information in the GPS information with the local time, and compare the position information in the GPS information with the local position. Specifically, the time information in the GPS information is compared with the local time of the locally preset GPS information, and the position information in the GPS information is compared with the local position of the locally preset GPS information.

[0052] Step S202: If the difference between the time information in the GPS information and the local time is greater than a preset time threshold, or if the difference between the position information in the GPS information and the local position is greater than a preset distance threshold, it is determined that the error range between the GPS information and the local preset GPS information meets the preset requirements.

[0053] Exemplarily, the preset time threshold may be 3 seconds, and the preset distance threshold may be 50 meters. If the difference between the time information in the GPS information and the local time is greater than 3 seconds, the error range between the GPS information and the local preset GPS information meets the preset requirements; or, if the difference between the location information in the GPS information and the local location is greater than 50 meters, the error range between the GPS information and the local preset GPS information meets the preset requirements.

[0054] Step S105, generating a spectrum diagram of the signal information to be identified. Specifically, for the signal information to be identified in each preset frequency band, if the error range between the GPS information and the locally preset GPS information does not meet the preset requirements, it means that the signal information to be identified in the preset frequency band does not have a fake GPS signal, but there may still be a counter signal that interferes with the drone communication. Therefore, a spectrum diagram is generated for the signal information to be identified in each preset frequency band to determine whether there is a signal that interferes with the communication. The method of converting the signal into a spectrum diagram is a prior art and will not be repeated here.

[0055] Step S106, judging whether the corresponding signal information to be identified contains a counter-signal of a drone according to the image features of the spectrum graph, if so, executing step S107, if not, executing step S108.

[0056] Specifically, this step includes detecting whether there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold. If so, it is determined that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of the drone. If not, it is determined that the signal information to be identified corresponding to the spectrum graph does not contain a counter-signal of the drone.

[0057] After the signal information is converted into a spectrum graph, the spectrum graph shows the power distribution of the frequency of the signal information in the original preset frequency band, with frequency as the horizontal axis and power as the vertical axis. This step is to find the corresponding vertical axis according to the horizontal axis point on the spectrum graph, and find the point with power greater than the preset threshold. If there are a continuous preset number of points with power greater than the preset threshold, it is determined that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of a drone. Among them, those skilled in the art can set the preset threshold and the preset number according to the value of the preset frequency band and the length of the collected signal.

[0058] Step S107, determining whether the signal information to be identified contains a counter signal of a drone. Specifically, if the error range between the GPS information and the locally preset GPS information meets the preset requirement, that is, the corresponding signal information to be identified contains a counter signal of a drone in the form of a forged GPS signal.

[0059] Although the error range between the GPS information and the locally preset GPS information does not meet the preset requirements, there are a continuous preset number of points in the spectrum diagram whose power is greater than the preset threshold, which means that the signal information to be identified has a counter signal, which is a signal that interferes with the drone communication.

[0060] Step S108, determining that the signal information to be identified does not contain a counter signal of the drone. If the error range between the GPS information and the locally preset GPS information does not meet the preset requirements, and there are no consecutive preset number of points in the spectrum graph whose power is greater than the preset threshold, then the signal information to be identified does not contain a counter signal of the drone.

[0061] Step S109, counting the frequency, bandwidth, power and transmission state of the counter signal. Specifically, after determining that the signal information to be identified contains a counter signal of a drone, the signal parameters of the counter signal are counted to facilitate the subsequent response or adjustment of the drone flight strategy during the drone flight.

[0062] In the scheme of this embodiment, by receiving the signal information to be identified of multiple preset frequency bands, parsing and obtaining the GPS information in the signal information to be identified, determining whether the error range between the GPS information and the locally preset GPS information meets the preset requirements, if the error range meets the preset requirements, determining that the signal information to be identified contains the counter signal of the drone, if the error range does not meet the preset requirements, generating a spectrum diagram of the signal information to be identified, and determining whether the corresponding signal information to be identified contains the counter signal of the drone according to the image features of the spectrum diagram, if so, determining that the signal information to be identified contains the counter signal of the drone. That is to say, this scheme can receive the signal information to be identified of multiple preset frequency bands, and use the GPS information and the spectrum diagram to comprehensively identify the counter signal of the drone for the signal information to be identified of each preset frequency band in multiple preset frequency bands, thereby realizing the identification of the counter signal in multiple dimensions, and being able to more comprehensively and effectively determine whether there is a counter signal of the drone in the monitoring area, which helps to improve the accuracy of identifying the counter signal of the drone, and reduce the occurrence of the situation where the counter signal of the drone is missed due to the monitoring of a single frequency band, thereby helping to improve the reliability of the subsequent drone mission execution.

[0063] Furthermore, because in the same frequency band, in addition to the drone counter-signal, there may also be ordinary WIFI signals, public communication signals and other signals with similar frequencies. Therefore, if the presence of a drone counter-signal is simply identified from the presence or absence of a specific frequency signal, it is easy to cause signal misjudgment. Therefore, by detecting whether there are a continuous preset number of points with power greater than a preset threshold in the spectrum graph, if there are a continuous preset number of points with power greater than the preset threshold, it is determined that the signal information to be identified corresponding to the spectrum graph contains a drone counter-signal, so that it can more accurately determine whether there is a drone counter-signal, further improving the accuracy and reliability of monitoring.

[0064] In addition, by determining whether the signal information to be identified contains a GPS signal after receiving the signal information to be identified in multiple frequency bands, and if so, executing the step of parsing to obtain the GPS information in the signal information to be identified, and if not, executing the step of generating a spectrum diagram of the signal information to be identified, it helps to reduce the parsing work and improve efficiency.

[0065] like Figure 3 As shown, in one embodiment, before the step of judging whether the corresponding signal information to be identified has a counter-signal of a drone according to the image features of the spectrum graph, the step includes: preliminarily judging whether the signal information to be identified has a counter-signal according to a preset method, and if so, executing the step of judging whether the corresponding signal information to be identified has a counter-signal of a drone according to the image features of the spectrum graph, and if not, determining that the signal information to be identified does not have a counter-signal of a drone.

[0066] Specifically, the method for identifying the drone countermeasure signal of this embodiment generally includes:

[0067] Step S301, generating a frequency spectrum diagram of the signal information to be identified.

[0068] Step S302, preliminarily determine whether the signal information to be identified contains a counter signal in a preset manner, if so, execute step S303, if not, execute step S305.

[0069] Reference Figure 4 As shown, this step includes:

[0070] Step S401, comparing the spectrum graph with a preset spectrum template. Specifically, the preset spectrum template is a pre-configured spectrum graph template of a common signal or a spectrum graph template of no signal.

[0071] Step S402, determine whether the spectrum diagram matches the preset spectrum template, if yes, execute step S, if no, execute step S403. Common matching methods include square difference matching, correlation matching, normalized cross-correlation matching, etc.

[0072] Step S403, detect whether there is a point in the spectrum graph with power exceeding a preset threshold, if yes, execute step S404, if no, execute step S405. Specifically, it is to detect whether there is a frequency point in the spectrum graph with power exceeding the preset threshold.

[0073] Step S404: Preliminary determination of whether the signal to be identified has a counter signal. If the template does not match and there is a point in the spectrum graph where the power exceeds a preset threshold, it is preliminarily determined that the signal to be identified has a counter signal, and further determination is made later.

[0074] Step S405: determine that the signal information to be identified does not contain a counter-signal of the drone.

[0075] Step S303, judging whether the corresponding signal information to be identified contains a counter signal of a drone according to the image features of the spectrum graph. If so, executing step S304, if not, executing step S305. Specifically, that is to say, when it is preliminarily determined that the signal information to be identified contains a counter signal of a drone, further more accurate identification is performed according to the spectrum graph.

[0076] Step S304: determining whether the signal information to be identified contains a counter-signal of a drone.

[0077] Step S305: determine that the signal information to be identified does not contain a counter-signal of the drone.

[0078] In the scheme of the present embodiment, before the step of judging whether the corresponding signal information to be identified includes the counter signal of the drone according to the image features of the spectrum graph, a preliminary judgment is made in a preset manner as to whether the signal information to be identified includes the counter signal of the drone. If so, a step of judging whether the corresponding signal information to be identified includes the counter signal of the drone according to the image features of the spectrum graph is performed. If not, it is determined that the signal information to be identified does not include the counter signal of the drone. Thus, a simple preliminary judgment can be made based on the spectrum graph first, and then further complex judgment can be made, which helps to improve recognition efficiency.

[0079] like Figure 5 As shown, in one embodiment, when it is detected that there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold, the method for identifying the drone counter-signal also includes: determining whether the signal information to be identified corresponding to the spectrum graph belongs to a preset drone communication frequency band, and if so, determining that the signal information to be identified corresponding to the spectrum graph contains a drone counter-signal.

[0080] Specifically, the method for identifying the drone countermeasure signal of this embodiment generally includes:

[0081] Step S501, generating a frequency spectrum diagram of the signal information to be identified.

[0082] Step S502, detecting whether there are a preset number of consecutive points in the spectrum graph whose power is greater than a preset threshold, if so, executing step S503, if not, executing step S505.

[0083] Step S503, determine whether the signal information to be identified corresponding to the spectrum graph belongs to the preset UAV communication frequency band, if yes, execute step S504, if no, execute step S505. Specifically, when there is no GPS signal or the GPS signal is real in the signal information to be identified in a preset frequency band, the frequency band may not be the UAV communication frequency band, so even if there are a continuous preset number of points with power greater than the preset threshold in the spectrum graph, it will not interfere with the UAV communication, so first check whether the signal information to be identified belongs to the preset UAV communication frequency band.

[0084] Step S504, determining whether the signal information to be identified contains a counter signal of the drone. If the signal information belongs to the preset drone communication frequency band, determining whether the signal information to be identified contains a counter signal of the drone.

[0085] Step S505: determine that the signal information to be identified does not contain a counter signal of the drone. If it does not belong to the preset drone communication frequency band, determine that the signal information to be identified does contain a counter signal of the drone.

[0086] Because this solution requires comprehensive judgment of GPS signals and interference signals, it is necessary to identify the signal information to be identified in multiple frequency bands. For some signals that do not belong to the drone communication frequency band, the original spectrum diagram may have a continuous preset number of points with power greater than the preset threshold. Therefore, it is finally determined whether it belongs to the preset drone communication frequency band, making the identification more accurate.

[0087] like Figure 6 As shown, in one embodiment, the method for identifying the drone countermeasure signal is to collect signal information of multiple frequency bands, and the signal information of each frequency band includes GPS signal collection and decoding, and judge whether the GPS information is normal or abnormal according to the comparison of the decoded time position information and the local time position information. And the identification of the communication interference signal of each frequency band, that is, first judge whether there is a signal in the frequency band, according to Figure 4 The content shown is then detected to see if there are a continuous preset number of points in the spectrum graph whose power is greater than the preset threshold, and finally whether the frequency band communication signal is normal or abnormal. Then, the normal and abnormal conditions of the GPS signal and the frequency band communication signal are combined to determine whether there is a counter signal in the monitoring area. If there is a counter signal, the counter signal is processed, that is, the frequency, bandwidth, power and transmission status of the counter signal are counted.

[0088] like Figure 7 and Figure 8 As shown, in one embodiment, the drone countermeasure signal recognition device 10 includes a signal acquisition module 100 and a signal processing module 200. The signal acquisition module 100 is used to collect signals. The signal processing module 200 is used to receive signals. The signal processing module 200 includes a memory 210, a processor 220, and a machine executable program 230 stored in the memory 210 and running on the processor 220, and the processor 220 implements the drone countermeasure signal recognition method according to any of the above embodiments when executing the machine executable program 230.

[0089] Specifically, the machine executable program 230 for performing the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, computer instructions, computer-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0090] It should be understood that each part of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system.

[0091] Processor 220 may be a single core processor, a multi-core processor, an acquisition cluster, or any number of other configurations. Memory 210 may include random access memory (RAM), read-only memory, flash memory, or any other suitable storage system.

[0092] At this point, those skilled in the art should recognize that, although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived based on the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. A method for identifying a drone countermeasure signal, comprising: Receiving information of signals to be identified within a plurality of preset frequency bands; Analyze and obtain GPS information in the signal information to be identified; Determine whether the error range between the GPS information and the locally preset GPS information meets the preset requirements; if so, determine that the signal information to be identified contains a counter-signal of the drone; if the error range does not meet the preset requirements, generate a spectrum graph of the signal information to be identified; determine whether the corresponding signal information to be identified contains a counter-signal of the drone based on the image features of the spectrum graph; if so, determine that the signal information to be identified contains a counter-signal of the drone.

2. The method for identifying a drone countermeasure signal according to claim 1, wherein: The step of judging whether the corresponding signal information to be identified contains a counter-signal of a drone according to the image features of the spectrum graph comprises: Detect whether there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold. If so, determine that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of a drone.

3. The method for identifying a drone countermeasure signal according to claim 1, wherein: The step of judging whether the corresponding signal information to be identified contains a counter-signal of a drone according to the image features of the spectrum graph includes: Preliminarily determine whether the signal information to be identified has a counter signal in a preset manner. If so, execute the step of determining whether the corresponding signal information to be identified has a counter signal of a drone based on the image features of the spectrum graph. If not, determine that the signal information to be identified does not have a counter signal of a drone.

4. The method for identifying a drone countermeasure signal according to claim 3, wherein: The step of preliminarily determining whether the signal information to be identified has a counter signal in a preset manner includes: The spectrum diagram is compared with the preset spectrum template. If they do not match, it is preliminarily determined that the signal information to be identified contains a counter signal. If they match, it is determined that the signal information to be identified does not contain a counter signal of the drone.

5. The method for identifying a drone countermeasure signal according to claim 4, wherein: The step of preliminarily determining whether the signal information to be identified contains a counter signal includes: Detect whether there is a point in the spectrum graph whose power exceeds a preset threshold. If so, preliminarily determine that there is a counter signal in the signal information to be identified. If not, determine that there is no counter signal of the drone in the signal information to be identified.

6. The method for identifying a drone countermeasure signal according to claim 1, wherein: When it is detected that there are a continuous preset number of points in the spectrum graph whose power is greater than a preset threshold, the method for identifying the drone countermeasure signal further includes: Determine whether the signal information to be identified corresponding to the spectrum graph belongs to a preset drone communication frequency band. If so, determine that the signal information to be identified corresponding to the spectrum graph contains a counter-signal of a drone.

7. The method for identifying a drone countermeasure signal according to claim 1, wherein: The step of determining whether the error range between the GPS information and the locally preset GPS information meets the preset requirements comprises: Comparing the time information in the GPS information with the local time, and comparing the location information in the GPS information with the local location; If the difference between the time information in the GPS information and the local time is greater than a preset time threshold, or if the difference between the location information in the GPS information and the local location is greater than a preset distance threshold, it is determined that the error range between the GPS information and the locally preset GPS information meets the preset requirements.

8. The method for identifying a drone countermeasure signal according to claim 1, wherein: After the step of determining whether the signal information to be identified contains a counter-signal of a drone, the following steps are performed: The frequency, bandwidth, power and transmission status of the countermeasure signal are counted.

9. The method for identifying a drone countermeasure signal according to claim 1, wherein: The step of receiving the information of the signals to be identified in the multiple frequency bands includes: Determine whether the signal information to be identified contains a GPS signal. If so, perform the step of parsing to obtain the GPS information in the signal information to be identified. If not, perform the step of generating a spectrum diagram of the signal information to be identified.

10. A drone countermeasure signal recognition device, comprising: A signal processing module comprises a memory, a processor and a machine executable program stored in the memory and running on the processor, and the processor implements the method for identifying the drone countermeasure signal according to any one of claims 1 to 9 when executing the machine executable program.

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