Method, system and device for realizing full-time frequency spectrum monitoring based on nest unmanned aerial vehicle and fixed monitoring station, processor and storage medium thereof

Abstract

The invention relates to a method for realizing full-time frequency spectrum monitoring based on a nest unmanned aerial vehicle and a fixed monitoring station. The method comprises the following steps: issuing a full-time frequency spectrum monitoring task; continuously scanning the monitoring target frequency band; extracting a signal frequency, and performing parameter measurement; signal parameters which are not matched with the known signal library are stored, and the equipment state is recovered; setting a time interval, and generating a direction finding task list; the unmanned aerial vehicle advances according to a preset track and performs a monitoring direction finding task; the unmanned aerial vehicle returns to enter the nest, and charging and heat dissipation reconditioning are automatically completed; and updating the signal positioning data. By adopting the method, the system, the device, the processor and the computer readable storage medium for realizing full-time frequency spectrum monitoring based on the nest unmanned aerial vehicle and the fixed monitoring station, a reliable positioning result is given through a multi-point direction finding result of the unmanned aerial vehicle on the whole track, high-frequency weak signals are easy to capture, the monitoring utilization rate of the unmanned aerial vehicle is greatly improved, and the real-time performance of the unmanned aerial vehicle is improved. The total element information of the signal is collected, and the management is scientific and accurate.

Description

Technical Field

[0001] This invention relates to the field of spectrum monitoring, particularly to the field of radio spectrum, specifically to a method, system, device, processor, and computer-readable storage medium for achieving real-time spectrum monitoring based on a drone nest and a fixed monitoring station. Background Technology

[0002] Radio spectrum is a finite, reusable natural resource, and also a valuable strategic resource. To ensure the normal operation of various wireless devices and prevent mutual interference, radio management departments need to conduct daily monitoring of the radio spectrum, understand the transmission of radio signals within the region, and promptly investigate and punish illegal radio applications.

[0003] Fixed monitoring stations are the main technical facilities for spectrum monitoring, primarily consisting of monitoring receivers, direction-finding receivers, feeders, antennas, industrial control computers, and display terminals. They can continuously monitor the radio spectrum in the surrounding area and determine the direction of arrival of target signals through direction-finding equipment, thus assisting in interference detection.

[0004] With the advancement of drone technology, the use of drones to carry radio monitoring and direction finding equipment for spectrum monitoring has also seen significant development in recent years. It can overcome the obstruction and reflection of ground buildings, which is beneficial for signal reception and can achieve excellent results in certain specific situations.

[0005] Full-time spectrum monitoring refers to an automated and intelligent monitoring method that continuously acquires regional spectrum signals over a relatively long period of time (7×24 hours), analyzes and locates unknown signals in the spectrum, and issues alarms for illegal signals.

[0006] Fixed monitoring stations are well-equipped and ideally located, enabling long-term monitoring of radio signals in the surrounding area. However, they also have the following problems: 1. The investment in site management is relatively large, so the number of sites will not be too many. They are generally located in the core areas of the city and cannot achieve full coverage.

[0007] 2. As cities continue to develop, the surrounding environment of existing stations is changing rapidly, with tall buildings emerging one after another, causing varying degrees of impact on signal reception.

[0008] 3. The stations are generally far apart, and except for a few low-frequency signals, it is impossible to complete cross-regional collaborative measurements and joint positioning.

[0009] Drone spectrum monitoring also has its own shortcomings: 1. Operating drones requires professional pilots and has high technical requirements, making it impossible to deploy them in large quantities.

[0010] 2. Conventional drones rely on lithium batteries for power, which limits their flight time and cannot meet the requirements for long-term monitoring.

[0011] In summary, existing technologies cannot meet the technical requirements for full-time spectrum monitoring. Summary of the Invention

[0012] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, device, processor and computer-readable storage medium for all-time spectrum monitoring based on UAVs and fixed monitoring stations, which meets the requirements of long-term monitoring, is easy to operate and has a wide range of applications.

[0013] To achieve the above objectives, the present invention provides a method, system, apparatus, processor, and computer-readable storage medium for real-time spectrum monitoring based on a nested unmanned aerial vehicle (UAV) and a fixed monitoring station, as follows: The method for achieving real-time spectrum monitoring based on UAVs and fixed monitoring stations is characterized by the following steps: (1) The full-time spectrum monitoring task is sent to the monitoring receiver through the control terminal of the fixed monitoring station; (2) After receiving the task, the monitoring receiver of the fixed monitoring station automatically starts the panoramic scanning mode according to the task parameters, continuously scans the frequency band of the monitoring target, and transmits the spectrum data back to the control terminal in real time. (3) The control terminal of the fixed monitoring station extracts the signal frequency from the received spectrum data, and the direction-finding receiver measures the parameters of the extracted signal; (4) The control terminal of the fixed monitoring station stores the signal parameters that do not match the known signal library into the unknown signal library, restores the equipment status, and repeats step (2) in a loop. (5) Set time interval, the UAV nest receives data from the unknown signal library and sends it to the compact monitoring and direction finding device on the UAV platform to generate a direction finding task list; (6) The UAV starts up and travels along the preset trajectory. The compact monitoring and orientation-finding equipment performs monitoring and orientation-finding tasks according to the orientation-finding task list cycle, and records the measurement results and time and location information. (7) The UAV returns to the nest and automatically completes charging and heat dissipation preparation. The compact monitoring and direction finding equipment automatically connects to the wireless network hotspot of the UAV nest and transmits the locally stored test data back to the control terminal, waiting for the next time interval. (8) The control terminal will summarize the monitoring and direction finding results returned to the unknown signal library, update the signal positioning data, wait for manual confirmation of the signal's ownership, mark it, and transfer it to the known signal library to realize the monitoring closed loop.

[0014] Preferably, the task parameters in step (2) include the service frequency band to be monitored, the execution duration, and the abnormal signal alarm method.

[0015] Preferably, step (3) specifically includes the following steps: (3.1) The control terminal of the fixed monitoring station starts the signal detection function, automatically analyzes and processes the received spectrum data, and extracts the signal frequency by means of background template or level threshold comparison. (3.2) The direction-finding receiver performs parameter measurements on the extracted signal.

[0016] Preferably, the measurement parameters in step (3.2) include the center frequency, bandwidth, modulation mode, direction of arrival, appearance time, disappearance time, and matching results with the known signal library.

[0017] Preferably, step (5) specifically includes the following steps: At set time intervals, fixed monitoring stations transmit data from the unknown signal database to the UAV nest. The UAV nest then sends the data from the unknown signal database to the compact monitoring and direction-finding device on the UAV platform, generating a direction-finding task list based on the signal parameters of the unknown signal database.

[0018] Preferably, the minimum time interval in step (5) is the total time required for the UAV to take off, execute the predetermined flight path, return, and automatically recharge.

[0019] Preferably, step (6) specifically includes the following steps: (6.1) The UAV starts up and leaves the UAV nest to take off. After reaching the predetermined altitude, the UAV will be monitored and the direction finding equipment will perform the direction finding tasks according to the direction finding task list periodically, record the measurement results and time and location information, and store the data locally. (6.2) The UAV travels along the preset trajectory and the flight trajectory is adjusted according to the actual situation.

[0020] This system, which enables real-time spectrum monitoring based on UAVs in a nest and fixed monitoring stations, is characterized in that the system includes fixed monitoring stations and a UAV monitoring system in a nest. The aforementioned UAV nest monitoring system includes a UAV platform, a compact monitoring and direction-finding system, and a UAV nest. The drone nest is placed in an open area near the fixed monitoring station, connected to the network and power supply system of the fixed monitoring station, and connected to the network module via a network cable. The compact monitoring and direction finding system is installed on the drone platform, connected to the drone's power supply, and wirelessly connected to the drone nest.

[0021] Preferably, the fixed monitoring station includes a control terminal, a network and power supply system, a monitoring receiver and its antenna feed system, and a direction-finding receiver and its antenna feed system. The network and power supply system is connected to the UAV nest of the UAV monitoring system. The control terminal is connected to the network and power supply system. The monitoring receiver and its antenna feed system are connected to the network and power supply system. The direction-finding receiver and its antenna feed system are connected to the network and power supply system.

[0022] This system, which enables real-time spectrum monitoring based on UAVs and fixed monitoring stations, is characterized by the following features: A processor is configured to execute computer-executable instructions; The memory stores one or more computer-executable instructions, which, when executed by the processor, implement the various steps of the above-described method for achieving all-time spectrum monitoring based on a nested UAV and a fixed monitoring station.

[0023] The processor for achieving real-time spectrum monitoring based on UAVs and fixed monitoring stations is characterized in that the processor is configured to execute computer-executable instructions, which, when executed by the processor, implement the various steps of the aforementioned method for achieving real-time spectrum monitoring based on UAVs and fixed monitoring stations.

[0024] The main feature of this computer-readable storage medium is that it stores a computer program that can be executed by a processor to implement the various steps of the above-described method for achieving all-time spectrum monitoring based on a nested UAV and a fixed monitoring station.

[0025] This invention employs a method, system, device, processor, and computer-readable storage medium for real-time spectrum monitoring based on a drone nest and a fixed monitoring station. A single fixed monitoring station can only measure the direction of incoming waves and cannot achieve area positioning. However, by using the drone's multi-point direction-finding results along its entire trajectory, combined with signal level distribution and the fixed station's direction-finding results, reliable positioning results can be provided. High-frequency signals have high attenuation and weak diffraction ability, making them difficult to detect by fixed monitoring stations in dense urban environments. Drones, after takeoff, encounter almost no obstructions and have a high probability of approaching surrounding signal sources along their predetermined trajectory, thus making it easier to capture weak high-frequency signals. Compared to the high investment required for fixed monitoring stations, the drone nest monitoring system offers better cost-effectiveness. Through pre-planned trajectory, it can operate normally even in environments where control signals are interfered with, requiring no human intervention. Usage and maintenance costs are controllable, significantly improving utilization compared to traditional drone monitoring. The entire monitoring process is automated, requiring no manual intervention in equipment and software, only confirmation after testing. Furthermore, the collaborative work of the two systems enables the collection of all signal information, making management more scientific and accurate. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the system for achieving real-time spectrum monitoring based on a nested UAV and a fixed monitoring station, according to the present invention.

[0027] Figure 2 This is a flowchart of the method for achieving real-time spectrum monitoring based on a drone nest and a fixed monitoring station according to the present invention. Detailed Implementation

[0028] To more clearly describe the technical content of the present invention, the following description is provided in conjunction with specific embodiments.

[0029] The method for achieving real-time spectrum monitoring based on a drone nest and a fixed monitoring station according to the present invention includes the following steps: (1) The full-time spectrum monitoring task is sent to the monitoring receiver through the control terminal of the fixed monitoring station; (2) After receiving the task, the monitoring receiver of the fixed monitoring station automatically starts the panoramic scanning mode according to the task parameters, continuously scans the frequency band of the monitoring target, and transmits the spectrum data back to the control terminal in real time. (3) The control terminal of the fixed monitoring station extracts the signal frequency from the received spectrum data, and the direction-finding receiver measures the parameters of the extracted signal; (4) The control terminal of the fixed monitoring station stores the signal parameters that do not match the known signal library into the unknown signal library, restores the equipment status, and repeats step (2) in a loop. (5) Set time interval, the UAV nest receives data from the unknown signal library and sends it to the compact monitoring and direction finding device on the UAV platform to generate a direction finding task list; (6) The UAV starts up and travels along the preset trajectory. The compact monitoring and orientation-finding equipment performs monitoring and orientation-finding tasks according to the orientation-finding task list cycle, and records the measurement results and time and location information. (7) The UAV returns to the nest and automatically completes charging and heat dissipation preparation. The compact monitoring and direction finding equipment automatically connects to the wireless network hotspot of the UAV nest and transmits the locally stored test data back to the control terminal, waiting for the next time interval. (8) The control terminal will summarize the monitoring and direction finding results returned to the unknown signal database, update the signal positioning data, wait for manual confirmation of the signal's ownership, mark it, and transfer it to the known signal database to realize the monitoring closed loop.

[0030] The task parameters in step (2) include the service frequency band to be monitored, execution duration, and abnormal signal alarm method.

[0031] Specifically, step (3) includes the following steps: (3.1) The control terminal of the fixed monitoring station starts the signal detection function, automatically analyzes and processes the received spectrum data, and extracts the signal frequency by means of background template or level threshold comparison. (3.2) The direction-finding receiver performs parameter measurements on the extracted signal.

[0032] The measurement parameters in step (3.2) include center frequency, bandwidth, modulation mode, direction of arrival, appearance time, disappearance time, and matching results with the known signal library.

[0033] Specifically, step (5) includes the following steps: At set time intervals, fixed monitoring stations transmit data from the unknown signal database to the UAV nest. The UAV nest then sends the data from the unknown signal database to the compact monitoring and direction-finding device on the UAV platform, generating a direction-finding task list based on the signal parameters of the unknown signal database.

[0034] The minimum time interval in step (5) is the total time required for the UAV to take off, execute the predetermined flight path, return, and automatically recharge.

[0035] Specifically, step (6) includes the following steps: (6.1) The UAV starts up and leaves the UAV nest to take off. After reaching the predetermined altitude, the UAV will be monitored and the direction finding equipment will perform the direction finding tasks according to the direction finding task list periodically, record the measurement results and time and location information, and store the data locally. (6.2) The UAV travels along the preset trajectory and the flight trajectory is adjusted according to the actual situation.

[0036] The system for real-time spectrum monitoring based on UAV nests and fixed monitoring stations of the present invention is characterized in that the system includes a fixed monitoring station and a UAV nest monitoring system. The aforementioned UAV nest monitoring system includes a UAV platform, a compact monitoring and direction-finding system, and a UAV nest. The drone nest is placed in an open area near the fixed monitoring station, connected to the network and power supply system of the fixed monitoring station, and connected to the network module via a network cable. The compact monitoring and direction finding system is installed on the drone platform, connected to the drone's power supply, and wirelessly connected to the drone nest.

[0037] The fixed monitoring station includes a control terminal, a network and power supply system, a monitoring receiver and its antenna feed system, and a direction-finding receiver and its antenna feed system. The network and power supply system is connected to the UAV nest of the UAV monitoring system. The control terminal is connected to the network and power supply system. The monitoring receiver and its antenna feed system are connected to the network and power supply system. The direction-finding receiver and its antenna feed system are also connected.

[0038] The system for all-weather spectrum monitoring based on a drone nest and a fixed monitoring station, as described in this invention, is characterized in that the system comprises: A processor is configured to execute computer-executable instructions; The memory stores one or more computer-executable instructions, which, when executed by the processor, implement the various steps of the above-described method for achieving all-time spectrum monitoring based on a nested UAV and a fixed monitoring station.

[0039] The processor of the present invention for realizing all-time spectrum monitoring based on a nested UAV and a fixed monitoring station is characterized in that the processor is configured to execute computer-executable instructions, and when the computer-executable instructions are executed by the processor, the various steps of the above-mentioned method for realizing all-time spectrum monitoring based on a nested UAV and a fixed monitoring station are implemented.

[0040] The main feature of the computer-readable storage medium of the present invention is that it stores a computer program thereon, which can be executed by a processor to implement the various steps of the above-described method for achieving all-time spectrum monitoring based on a nested UAV and a fixed monitoring station.

[0041] In a specific embodiment of the present invention, the monitoring system consists of the following components: Figure 1 As shown, the system comprises two parts: a fixed monitoring station and a UAV monitoring system housed within a drone nest. The fixed monitoring station includes a monitoring receiver and antenna feed system, a direction-finding receiver and antenna feed system, a control terminal, a network, and a power supply system. The UAV monitoring system housed a UAV platform, a compact monitoring and direction-finding system, and a UAV nest. The UAV nest is located in an open area near the monitoring station's equipment room, powered by the fixed monitoring station's power supply system, and connected to the site's switch via a network cable. The compact monitoring and direction-finding system is installed on the UAV platform, powered by the UAV's power supply, and can achieve wireless connectivity via the nest's network hotspot to receive mission information and transmit data back. Figure 1 In the middle, the module above the power supply system is the network module, which is responsible for network data transmission, also known as the site switch.

[0042] Based on the above system, the implementation steps for full-time spectrum monitoring are as follows: 1. Based on the needs of radio management, formulate monitoring tasks and send full-time spectrum monitoring tasks to the monitoring receiver through the control terminal of the fixed monitoring station. The task parameters include the service frequency band to be monitored, execution duration, and abnormal signal alarm methods.

[0043] 2. After receiving the task, the fixed monitoring station receiver automatically starts the panoramic scanning mode according to the task parameters, continuously scans the frequency band of the monitoring target, and transmits the spectrum data back to the control terminal in real time.

[0044] 3. The fixed monitoring station control terminal activates the signal detection function, automatically analyzes and processes the received spectrum data, and extracts the signal frequency through background template or level threshold comparison. Then, it controls the direction-finding receiver to measure the parameters of the extracted signal. The measured parameters include center frequency, bandwidth, modulation scheme, direction of arrival, appearance time, disappearance time, and matching results with a known signal database.

[0045] 4. The fixed station control terminal stores the signal parameters that do not match the known signal library into the unknown signal library and restores the equipment status to the state in step 2. The task is executed cyclically.

[0046] 5. After the set time interval, data from the unknown signal database is transmitted to the UAV's nest via the monitoring station's wired network. The nest then sends the data to the compact monitoring and direction-finding device on the UAV platform via a network hotspot. Based on the signal parameters in the signal database, a direction-finding task list is generated. The minimum time interval is the total time required for the UAV to take off, execute the predetermined flight path, return, and automatically recharge. Considering equipment lifespan and maintenance, the actual cycle should be no less than 12 hours.

[0047] 6. After the mission data is loaded, the UAV starts up, leaves the nest, and takes off. The takeoff altitude is generally no higher than 120 meters. Upon reaching the predetermined altitude, the UAV uses the direction-finding equipment to perform direction-finding tasks according to the mission list, recording measurement results, time, and location information, and storing the data locally. The UAV follows a preset trajectory. A typical trajectory involves the UAV traveling two kilometers in a straight line due north, then circling clockwise before returning. The flight path for different flight durations and speeds can be adjusted according to actual conditions. If there are taller buildings obstructing the path, adjustments will be necessary.

[0048] 7. After the drone returns to the nest, it automatically completes charging and heat dissipation preparation. The compact monitoring and direction finding equipment automatically connects to the nest's wireless network hotspot and transmits the locally stored test data back to the control terminal. After completion, it waits for the next time interval.

[0049] 8. The returned monitoring and direction finding results will be summarized in the unknown signal database, the signal positioning data will be updated, and the signal attribution will be awaited by manual confirmation. After labeling, the signal will be transferred to the known signal database to achieve a closed-loop monitoring system.

[0050] This invention addresses the issues of automation and reliability in the real-time monitoring process, enabling long-term detection, measurement, and location of unknown signals within a specific radio frequency band. Leveraging the powerful monitoring and data analysis capabilities of fixed monitoring stations, combined with the automatic takeoff path planning of a drone monitoring system and the superior direction-finding and positioning effects resulting from unobstructed aerial signals, it achieves automatic identification and measurement of frequency band signals. This solution utilizes the fully automated path planning capabilities of drones combined with drone nests and the improved monitoring and direction-finding quality resulting from integration with fixed stations.

[0051] The core of this invention is frequency resource management in radio monitoring. It combines monitoring equipment carried by drones with monitoring equipment from fixed monitoring stations, leveraging the strengths of each to achieve long-term automatic monitoring. The technical approach involves the fixed station performing spectrum scanning and signal detection, transmitting the measurement results to the drone monitoring system for aerial signal direction finding and positioning, and then summarizing the results to improve the signal database, thus achieving automatic signal management. The two systems still only overlap on the drone itself. This invention does not involve communication between drones and their nests or between drones and base stations. Instead, it considers data transmission within the nest's network hotspot to avoid potential communication interference and instability. The core issue remains the automation of frequency band monitoring.

[0052] This invention relates more to the application of drones, but the core is not the drone itself, but the monitoring system it carries and its coordinated application with fixed station monitoring systems.

[0053] For the specific implementation scheme of this embodiment, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0054] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0055] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0056] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0057] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0058] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The corresponding program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0059] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0060] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0061] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0062] This invention employs a method, system, device, processor, and computer-readable storage medium for real-time spectrum monitoring based on a drone nest and a fixed monitoring station. A single fixed monitoring station can only measure the direction of incoming waves and cannot achieve area positioning. However, by using the drone's multi-point direction-finding results along its entire trajectory, combined with signal level distribution and the fixed station's direction-finding results, reliable positioning results can be provided. High-frequency signals have high attenuation and weak diffraction ability, making them difficult to detect by fixed monitoring stations in dense urban environments. Drones, after takeoff, encounter almost no obstructions and have a high probability of approaching surrounding signal sources along their predetermined trajectory, thus making it easier to capture weak high-frequency signals. Compared to the high investment required for fixed monitoring stations, the drone nest monitoring system offers better cost-effectiveness. Through pre-planned trajectory, it can operate normally even in environments where control signals are interfered with, requiring no human intervention. Usage and maintenance costs are controllable, significantly improving utilization compared to traditional drone monitoring. The entire monitoring process is automated, requiring no manual intervention in equipment and software, only confirmation after testing. Furthermore, the collaborative work of the two systems enables the collection of all signal information, making management more scientific and accurate.

[0063] In this specification, the invention has been described with reference to specific embodiments thereof. However, it will be apparent that various modifications and variations can be made without departing from the spirit and scope of the invention. Therefore, the specification and drawings should be considered illustrative rather than restrictive.

Claims

1. A method for implementing full-time spectrum monitoring based on a nest unmanned aerial vehicle and a fixed monitoring station, characterized in that, The method comprises the following steps: (1) issuing a full-time spectrum monitoring task to the monitoring receiver through the control terminal of the fixed monitoring station; (2) after the monitoring receiver of the fixed monitoring station receives the task, automatically starting the panoramic scanning mode according to the task parameters, continuously scanning the monitoring target frequency band, and real-time returning the spectrum data to the control terminal; (3) the control terminal of the fixed monitoring station extracts the signal frequency from the received spectrum data, and the direction-finding receiver measures the parameters of the extracted signal; (4) the control terminal of the fixed monitoring station stores the signal parameters that are not matched with the known signal library into the unknown signal library, and restores the equipment state, and circulates step (2); (5) setting a time interval, the unmanned aircraft nest receives the data of the unknown signal library and sends it to the compact monitoring direction-finding equipment on the unmanned aircraft platform to generate a direction-finding task list; (6) the unmanned aircraft starts and travels according to the preset trajectory, and the compact monitoring direction-finding equipment periodically performs monitoring direction-finding tasks according to the direction-finding task list, records the measurement results and time position information; (7) the unmanned aircraft returns to the nest, automatically completes charging and heat dissipation preparation, and the compact monitoring direction-finding equipment automatically connects the wireless network hotspot of the unmanned aircraft nest to return the locally stored test data to the control terminal, and waits for the next time interval; (8) the control terminal collects the returned monitoring and direction-finding results into the unknown signal library, updates the signal positioning data, waits for manual confirmation of the signal ownership, and after labeling, transfers to the known signal library to realize monitoring closed loop; The step (3) specifically comprises the following steps: (3.1) the control terminal of the fixed monitoring station starts the signal detection function, automatically analyzes and processes the received spectrum data, and extracts the signal frequency through background template or level threshold comparison; (3.2) the direction-finding receiver measures the parameters of the extracted signal; The step (5) specifically comprises the following steps: Setting a time interval, the fixed monitoring station transmits the data of the unknown signal library to the unmanned aircraft nest, the unmanned aircraft nest sends the data of the unknown signal library to the compact monitoring direction-finding equipment on the unmanned aircraft platform, and generates a direction-finding task list according to the signal parameters of the unknown signal library. 2.The method of claim 1, wherein, The task parameters in step (2) include the business frequency band to be monitored, the execution time, and the abnormal signal alarm mode. 3.The method of claim 1, wherein, The measurement parameters in step (3.2) include the center frequency, bandwidth, modulation mode, incoming wave direction, appearance time, disappearance time, and matching results with the known signal library. 4.The method of claim 1, wherein, The minimum value of the time interval in step (5) is the total time required for the unmanned aircraft to take off, fly according to the predetermined trajectory, return and automatically charge. 5.The method of claim 1, wherein, The step (6) specifically comprises the following steps: (6.1) the unmanned aircraft starts and leaves the unmanned aircraft nest to ascend to a predetermined height, and the compact monitoring direction-finding equipment periodically performs monitoring direction-finding tasks according to the direction-finding task list, records the measurement results and time position information, and stores the data locally; (6.2) the unmanned aircraft travels according to the preset trajectory, and adjusts the flight trajectory of the unmanned aircraft according to the actual situation.

6. A system for implementing full-time spectrum monitoring based on the method of claim 1, wherein the system comprises a fixed monitoring station and a swarm of drones. The system comprises a fixed monitoring station and a nest unmanned aircraft monitoring system, The drone nest unmanned aerial vehicle monitoring system comprises an unmanned aerial vehicle platform, a compact monitoring direction finding system, an unmanned aerial vehicle nest, The unmanned aerial vehicle nest is arranged on an open site near a fixed monitoring station, connected with a network and power supply system of the fixed monitoring station, and connected with a network module through a network cable. 7.The system for full-time frequency spectrum monitoring based on the nest drone and the fixed monitoring station according to claim 6, characterized in that, The fixed monitoring station comprises a control terminal, a network and power supply system, a monitoring receiver and its antenna feeder system, and a direction finding receiver and its antenna feeder system.

8. An apparatus for implementing full-time spectrum monitoring based on a nest drone and a fixed monitoring station, characterized in that, The device comprises: a processor configured to execute computer executable instructions; a memory storing one or more computer executable instructions, which, when executed by the processor, implement each step of the method for implementing full-time spectrum monitoring based on a drone nest unmanned aerial vehicle and a fixed monitoring station according to any one of claims 1 to 5. 9.A processor for implementing all-time frequency spectrum monitoring based on a nest unmanned aerial vehicle (UAV) and a fixed monitoring station, characterized in that, The processor is configured to execute computer executable instructions, which, when executed by the processor, implement each step of the method for implementing full-time spectrum monitoring based on a drone nest unmanned aerial vehicle and a fixed monitoring station according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer program stored thereon can be executed by the processor to implement each step of the method for implementing full-time spectrum monitoring based on a drone nest unmanned aerial vehicle and a fixed monitoring station according to any one of claims 1 to 5.

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