A method for anti-drone monitoring and scheduling with adaptive frequency band identification

Abstract

The application discloses an anti-unmanned aerial vehicle monitoring and scheduling method with self-adaptive frequency band identification, relates to the technical field of anti-unmanned aerial vehicle monitoring and scheduling, and is used for solving the problem of poor frequency band identification and interference optimization; the application constructs a closed-loop mechanism of radar echo analysis, frequency band effectiveness evaluation and monitoring and scheduling linkage, extracts the frequency band effectiveness features of an unmanned aerial vehicle target through multi-frequency band monitoring data, dynamically identifies and recommends a tracking frequency band and a candidate countermeasure frequency band, and generates a scheduling reference scheme in combination with spectrum occupation and protected frequency band information, so as to provide a quantitative basis for frequency band selection and power configuration of an interference device; meanwhile, the frequency band weight and identification rules are continuously optimized based on monitoring operation feedback, fine discrimination of unmanned aerial vehicle signals and external electromagnetic interference sources is realized, and the unmanned aerial vehicle band identification accuracy, the reliability of the scheduling reference and the operation stability of the system in a complex electromagnetic environment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anti-UAV monitoring and scheduling, and more particularly to an anti-UAV monitoring and scheduling method with adaptive frequency band identification. BACKGROUND

[0002] In the scenarios of low-altitude safety protection and important area control, for small UAV targets of "black flight" or "disguised as legal", multi-frequency radar and jamming equipment are often deployed in coordination to realize defense coverage by combining spectrum detection and directional suppression. Existing anti-UAV systems mostly use fixed frequency scanning and manually configured jamming parameters, which cannot fully perceive the response differences of different frequency bands to targets, and lack real-time discrimination mechanisms for the adaptability of dynamic target frequency bands, resulting in waste of frequency band resources, low jamming efficiency, and even possible damage to legal business frequency bands, bringing additional jamming risks.

[0003] In addition, the existing scheme does not fully consider the influence of external electromagnetic interference sources of the monitoring target UAV, resulting in inaccurate jamming identification, further weakening the precision countermeasures capability of the system. The scheduling reference scheme is often based on static capabilities and fixed priority rules of equipment, and cannot dynamically adjust the frequency band selection, ignoring the changes in the electromagnetic environment and the fluctuations in the state of the jamming equipment. Especially in the multi-site coordination or high-density target scenarios, there is a lack of fine frequency band identification and echo evaluation mechanisms, resulting in unbalanced resource allocation, jamming object identification errors and execution lag, etc., which seriously affect the response speed and control effect of the system. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the following scheme is proposed to solve the problem of frequency band identification and jamming optimization.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0006] An anti-UAV monitoring and scheduling method with adaptive frequency band identification, comprising the following steps:

[0007] Deploying multi-frequency radar detection devices and edge monitoring terminals in the protection area, synchronizing the radar and anti-UAV jamming equipment according to a unified time reference, rotating the configuration of the receiving channels in the candidate frequency band, performing spectrum listening on the airspace electromagnetic signals and receiving target UAV echoes or radiation signals, collecting electromagnetic wave signals and possible external electromagnetic interference signals of the target UAV by the edge monitoring terminal, monitoring the working frequency band, transmission power and countermeasure mode of the anti-UAV jamming equipment and generating transmission records;

[0008] Target detection and association are performed on target echo data in the monitoring data, echoes of suspected unmanned aerial vehicles in each candidate frequency band are summarized by target, and frequency band performance characteristics are calculated according to the number of detections, stability and motion characteristic matching degree, so as to optimize the candidate frequency band, mark the low-efficiency and risk;

[0009] Combined with the frequency band performance characteristics, local spectrum occupation and protected frequency band information, an adaptive frequency band identification result is generated for the target unmanned aerial vehicle, the adaptive frequency band identification result includes a recommended tracking frequency band set and a candidate countermeasure frequency band set, the adaptive frequency band identification result is compared with the transmission record to form a monitoring data frame containing the correspondence between the transmission configuration of the anti-unmanned aerial vehicle jamming device and the candidate countermeasure frequency band;

[0010] The superior management platform receives the monitoring data frame, evaluates the monitoring and countermeasure capability of the monitoring station with coverage capability according to the adaptive frequency band identification result, the position and available sub-frequency band range of the anti-unmanned aerial vehicle jamming device at each monitoring station, generates a scheduling reference scheme by avoiding the risk frequency band within the recommended tracking frequency band set and the candidate countermeasure frequency band set, and outputs the scheduling reference scheme in the form of scheduling suggestion;

[0011] During the operation of the monitoring system, the multi-frequency band radar collects target echoes within the recommended tracking frequency band set, associates the echo characteristics with the corresponding frequency band configuration, generates a frequency band configuration category label according to a preset rule, and updates the frequency band performance characteristics, the adaptive frequency band identification rule and the scheduling reference scheme generation rule.

[0012] Further, the multi-frequency band radar detection device sequentially configures the receiving channel within the candidate frequency band set containing at least three sub-frequency bands according to a preset rotation sequence or a pseudo-random hopping sequence, and collects monitoring data, records the unified timestamp, candidate sub-frequency band identifier and receiving parameter associated with each receiving configuration and its corresponding monitoring data, the edge monitoring terminal periodically collects the working frequency band, transmission power and countermeasure mode of the anti-unmanned aerial vehicle jamming device and marks the timestamp using the same time reference as the multi-frequency band radar detection device, and the monitoring data and the transmission record are stored in a unified time axis indexing manner.

[0013] Further, the frequency band performance characteristics at least include the effective detection number, the continuous effective detection time length, the change of echo amplitude and Doppler parameter within a preset detection period, and the matching degree with the target trajectory estimation result of the same target on each candidate sub-frequency band;

[0014] The sub-frequency band with the effective detection number and the continuous effective detection time length greater than or equal to the preset threshold and the matching degree within the preset range is marked as an optimal frequency band;

[0015] The candidate sub-frequency band with the effective detection number or the change not satisfying the optimal judgment condition is marked as a low-efficiency frequency band;

[0016] The sub-band overlapping with the protected service frequency band or satisfying the predefined interference characteristic condition is marked as a risk frequency band.

[0017] Further, the adaptive frequency band identification result includes a recommended tracking frequency band set and a candidate countermeasure frequency band set for a single target, the recommended tracking frequency band set being composed of candidate sub-bands marked as preferred frequency bands and satisfying the effective detection number and trajectory matching degree proportion threshold in a continuous detection window;

[0018] The candidate countermeasure frequency band set is obtained by excluding the candidate sub-bands overlapping with the protected service frequency band and the candidate sub-bands marked as risk frequency bands from the recommended tracking sub-band set after comparing the recommended tracking sub-band set with the local frequency spectrum occupation and protected frequency band information.

[0019] Further, the monitoring data frame at least includes the target UAV identification, the site identification, the recommended tracking frequency band set and the candidate countermeasure frequency band set in the adaptive frequency band identification result, the current working frequency band, the transmission power and the countermeasure mode of the anti-UAV interference device, and the correspondence relationship field of the current working frequency band relative to the candidate countermeasure frequency band set and the risk frequency band marking;

[0020] The correspondence relationship field is used to indicate three states of the interference device transmission configuration belonging to the candidate countermeasure frequency band, deviating from the candidate countermeasure frequency band or falling into the risk frequency band.

[0021] Further, when the superior management platform generates the scheduling reference scheme, it includes:

[0022] According to the target identification, the adaptive frequency band identification result and the site identification in the monitoring data frame, the correspondence relationship between the target UAV and the candidate anti-UAV interference device is established.

[0023] The geographic position, coverage area, available sub-band set and maximum power generation of each candidate anti-UAV interference device are obtained.

[0024] From the candidate anti-UAV interference devices with coverage capability, at least one anti-UAV interference device is selected for each target UAV, and the recommended working sub-band is determined from the candidate countermeasure frequency band set corresponding to the anti-UAV interference device, and the working sub-band of each anti-UAV interference device in the same period is limited to a single sub-band.

[0025] Further, when the superior management platform determines the working sub-band in the scheduling reference scheme, the spectrum safety check is performed on the candidate working sub-band, including:

[0026] The frequency relationship between the candidate working sub-band and the protected service frequency band is searched, and the corresponding candidate working sub-band is excluded when overlapping;

[0027] The field strength estimation value of the candidate working sub-band in the preset area is calculated according to the interference device position, antenna pattern and transmission power parameters, the field strength estimation value is compared with the preset field strength threshold, and the candidate working sub-band exceeding the field strength threshold is not used;

[0028] Conflict detection is performed on the configurations of the monitoring stations in adjacent areas which are allocated the same candidate working sub-band, and the working sub-band configuration of part of the monitoring stations is deleted or adjusted to a different working sub-band when there is an overlapping coverage area.

[0029] Further, during the operation of the monitoring system, the target echo sequence in the recommended tracking sub-band set and the actual transmission working sub-band and transmission power of the anti-UAV interference device of each target UAV and its corresponding anti-UAV interference device are collected.

[0030] The association record of the working sub-band configuration and the echo response is established according to a unified time reference, and each working sub-band configuration is marked as an effective configuration, an inefficient configuration or a risk configuration according to a preset determination condition;

[0031] The preset determination condition includes a comprehensive judgment on the echo amplitude change, the detection state change, the target trajectory offset condition and whether it falls into the risk frequency band mark in a continuous detection period.

[0032] Further, the superior management platform updates the frequency band performance characteristics and the adaptive frequency band identification rule according to the effective configuration, the inefficient configuration and the risk configuration mark of the working sub-band configuration, including:

[0033] The priority of the working sub-band marked as an effective configuration at least twice is improved in the preferred frequency band;

[0034] The priority of the working sub-band marked as an inefficient configuration at least twice is reduced or marked as an inefficient frequency band;

[0035] The working sub-band marked as a risk configuration at least twice is added to the risk frequency band list or deleted from the candidate countermeasure frequency band set.

[0036] Further, when updating the adaptive frequency band identification rule and the scheduling reference scheme generation rule, the superior management platform respectively maintains independent rule sets and parameter sets for different regional electromagnetic environment conditions and different types of target UAVs, and selects the corresponding rule set and parameter set according to the regional information and the target UAV type information of the target UAV when generating the adaptive frequency band identification result and the scheduling reference scheme.

[0037] The anti-UAV monitoring and scheduling method with adaptive frequency band identification has the following technical effects and advantages:

[0038] The present application realizes efficient monitoring and accurate countermeasures of the unmanned aerial vehicle target in a complex electromagnetic environment by constructing a closed-loop control mechanism of frequency band performance feature extraction, adaptive frequency band identification and interference device scheduling linkage. By fusing radar echo data and interference device transmission records, the advantages and disadvantages of the frequency band are dynamically marked based on the multi-band target detection characteristics, the frequency band performance feature map with environment perception capability is constructed, the interference failure or damage to protected services caused by the use of fixed frequency bands is avoided, the recommended tracking frequency band and candidate countermeasure frequency band set with dynamic adjustability are formed by means of the joint comparison mechanism of candidate frequency bands and risk frequency bands, the optimal matching between frequency band identification and device capability is realized, the scheduling reference scheme is intelligently generated according to the target position, device capability and spectrum safety constraints, and the frequency band configuration priority and risk label are updated in combination with echo tracking feedback, so that the linkage adaptive optimization of the three stages of identification, scheduling and feedback is realized, and the spectrum utilization efficiency, regulation and control accuracy and task success rate of the anti-unmanned aerial vehicle system in a dynamic complex scene are improved. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A flowchart of an anti-unmanned aerial vehicle monitoring and scheduling method with adaptive frequency band identification. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0041] In order to achieve the above-mentioned purpose, Figure 1 A structural diagram of an anti-unmanned aerial vehicle monitoring and scheduling method with adaptive frequency band identification is given, which specifically includes the following steps.

[0042] A multi-band radar detection device and an edge monitoring terminal are deployed in a protection area, the radar and the anti-unmanned aerial vehicle interference device are synchronized according to a unified time reference, the receiving channels are configured in the candidate frequency bands in turn, the airspace electromagnetic signals are frequency spectrum monitored and the target unmanned aerial vehicle echo or radiation signals are received, the electromagnetic wave signals and possible external electromagnetic interference signals of the target unmanned aerial vehicle are collected by the edge monitoring terminal, the working frequency band, transmission power and countermeasure mode of the anti-unmanned aerial vehicle interference device are monitored and the transmission record is generated;

[0043] Target detection and association are performed on the target echo data in the monitoring data, the echoes of suspected unmanned aerial vehicles in each candidate frequency band are summarized according to the target, and the frequency band performance features are calculated according to the detection times, stability and motion feature matching degree, so as to mark the candidate frequency bands as optimal, inefficient and risk.

[0044] Generate adaptive frequency band identification results for the target UAV based on the frequency band performance characteristics, local spectrum occupation, and protected frequency band information, which include a recommended tracking frequency band set and a candidate countermeasure frequency band set. Compare the adaptive frequency band identification results with the transmission records to form a monitoring data frame containing the corresponding relationship between the anti-UAV jamming device transmission configuration and the candidate countermeasure frequency band.

[0045] The superior management platform receives the monitoring data frame, evaluates the monitoring and countermeasure capabilities of the monitoring sites with coverage capabilities based on the adaptive frequency band identification results, the locations of the anti-UAV jamming devices at each monitoring site, and the available sub-band range, generates a scheduling reference scheme by avoiding risk frequency bands within the recommended tracking frequency band set and the candidate countermeasure frequency band set, and outputs it in the form of a scheduling suggestion.

[0046] During the operation of the monitoring system, the multi-band radar collects target echoes within the recommended tracking frequency band set, associates echo characteristics with corresponding frequency band configurations, generates frequency band configuration category labels according to pre-set rules, and updates the frequency band performance characteristics, adaptive frequency band identification rules, and scheduling reference scheme generation rules.

[0047] Step 1: Deploy multi-band radar detection devices and edge monitoring terminals in the protected area, synchronize the radar and anti-UAV jamming devices according to a unified time reference, and alternate the configuration of receiving channels within the candidate frequency band to perform spectrum monitoring on airspace electromagnetic signals and receive target UAV echoes or radiation signals. The edge monitoring terminal collects electromagnetic wave signals and possible external electromagnetic interference signals of the target UAV, monitors the working frequency band, transmission power, and countermeasure mode of the anti-UAV jamming device, and generates transmission records. The specific implementation is as follows:

[0048] In the protected area, multiple multi-band radar detection devices are arranged along key directions. Each multi-band radar detection device includes a radio frequency transmitting unit, a radio frequency receiving unit, a signal processing unit, and a time synchronization unit. Corresponding edge monitoring terminals are arranged near each multi-band radar detection device. The edge monitoring terminal interacts with the multi-band radar detection device and the anti-UAV jamming device at the site through wired or wireless communication interfaces.

[0049] The time synchronization unit obtains a unified time reference from a satellite time receiver or a high-precision network time device and distributes time information to the multi-band radar detection devices and edge monitoring terminals, so that the transmission control, echo sampling of the multi-band radar detection devices, and state acquisition process of the edge monitoring terminals are all timed using the same time reference.

[0050] The candidate frequency band set is pre-configured as at least three non-overlapping sub-frequency bands in the system configuration stage, each sub-frequency band is identified by a center frequency and a bandwidth parameter, and is stored in the configuration data of the multi-frequency band radar detection device and the upper management platform, to ensure consistency of the candidate frequency band set for each site.

[0051] During operation, the multi-frequency band radar detection device generates a transmission sequence according to the stored candidate frequency band set and the rotation control strategy. The rotation control strategy can be a sequential rotation sequence or a pseudo-random hopping sequence. The sequential rotation sequence selects sub-frequency bands in sequence according to the order of the candidate sub-frequency bands in the configuration table for transmission. The pseudo-random hopping sequence generates a non-repeating or less-repeating selection sequence within the index range of the candidate sub-frequency bands using a deterministic pseudo-random number algorithm. The algorithm uses fixed initial parameters to obtain a determined hopping sequence for each device under the same configuration.

[0052] When performing transmission, the multi-frequency band radar detection device transmits a set of detection pulses or modulated signals on the currently selected sub-frequency band, and collects the echo signal on the corresponding receiving channel. The signal processing unit records the timestamp, the frequency band identifier of the used sub-frequency band, the transmission power, the wave form parameter, and the start and end time of the echo sampling for each transmission behavior and its echo collection behavior. The above information is associated with the echo data and stored in the local data buffer in the form of record entries, so that any echo sample can be traced back to the corresponding transmission behavior through the timestamp and the frequency band identifier.

[0053] The edge monitoring terminal establishes a data channel with the anti-UAV interference device at the same site through a serial port or an Ethernet interface, and periodically reads the current working frequency band, transmission power, and countermeasure mode information reported by the interference device. The current working frequency band is represented by the same frequency band identifier or frequency parameter as the candidate sub-frequency band, the transmission power is represented by an absolute value, and the countermeasure mode is represented by a pre-defined mode code.

[0054] The countermeasure mode code is pre-defined in the system, including but not limited to navigation interference mode, remote control link interference mode, image transmission link interference mode, and comprehensive interference mode. Each mode corresponds to a set of fixed signal modulation types, bandwidth settings, and power control strategies. The code table is stored in the anti-UAV interference device and the edge monitoring terminal, facilitating recording and analysis in the form of discrete fields in the monitoring data frame.

[0055] When receiving the above state data, the edge monitoring terminal calls the time synchronization module consistent with the multi-frequency band radar detection device to obtain a unified timestamp, binds the collected interference device working frequency band, transmission power, and countermeasure mode with the corresponding timestamp and device identifier, forms a transmission record entry, and stores it in chronological order.

[0056] Both echo data record and emission record are organized in a unified time axis index manner, that is, through unified timestamp and frequency band identification, radar emission and echo behavior, emission behavior of interference device and subsequent identification and scheduling process can be correspondingly associated under the same time reference, thereby providing consistent data basis for subsequent frequency band effectiveness calculation, adaptive frequency band identification and scheduling reference scheme generation.

[0057] Step 2, target detection and association of target echo data in monitoring data, the echo of suspected unmanned aerial vehicle in each candidate frequency band is summarized by target, and the frequency band effectiveness characteristics are calculated according to the detection times, stability and motion characteristic matching degree, and the candidate frequency bands are optimized, inefficient and risk marked, and the specific implementation is as follows:

[0058] After the synchronization acquisition of the multi-frequency band radar detection device and the edge monitoring terminal is completed, the echo data stored according to the unified time axis and the candidate sub-frequency band identification are subjected to multi-frequency band target detection and association. Firstly, the echo data on each candidate sub-frequency band is subjected to pulse compression processing and constant false alarm detection processing respectively to obtain initial echo detection units at different time, different distance units and Doppler units. Then, through distance gate, velocity gate and azimuth gate constraints, the echo detection units which are continuous in time, adjacent in space and meet the unmanned aerial vehicle motion model constraints in motion parameter change are associated to form a multi-time, multi-frequency band trajectory set of suspected unmanned aerial vehicle targets.

[0059] For each established suspected unmanned aerial vehicle target, the detection result sequence thereof on each candidate sub-frequency band is recorded, wherein each record at least contains timestamp, distance, radial velocity, Doppler frequency shift and echo amplitude information, and maintains one-to-one correspondence with the candidate sub-frequency band identification, so that the observation data of the same target on different candidate sub-frequency bands can be distinguished and summarized.

[0060] After obtaining the multi-frequency band observation data divided by target, the frequency band effectiveness characteristics are calculated for each candidate sub-frequency band for each suspected unmanned aerial vehicle target. The effective detection times are determined by the detection times of the detection meeting the detection threshold and successfully associated to the target trajectory on the candidate sub-frequency band. The continuous effective detection time length is determined by the time length of the continuous existence of effective detection in the adjacent detection period on the unified time axis. The time length is calculated in the manner of the number of detection periods multiplied by the time length of a single detection period. The stability degree of echo amplitude and Doppler parameter is determined by the change range and change frequency of echo amplitude and Doppler frequency shift of all effective detection points on the candidate sub-frequency band within the target observation period, wherein the change range refers to the difference between the maximum value and the minimum value, and the change frequency refers to the proportion of the number of times exceeding the preset deviation threshold to the total effective detection times. When the change range is smaller and the change frequency proportion does not exceed the preset proportion threshold, it is determined that the echo of the candidate sub-frequency band on the target is stable.

[0061] The trajectory matching degree is determined by the deviation of the detection points on the candidate sub-band from the target trajectory estimated based on all the frequency bands. The deviation is measured by counting whether the detection points fall within a pre-set trajectory envelope. When the proportion of the detection points falling within the trajectory envelope to the total number of effective detection points on the candidate sub-band is not less than a matching proportion threshold, it is determined that the trajectory matching degree of the candidate sub-band on the target meets the requirements.

[0062] It should be noted that the above threshold parameters are calibrated during the system deployment stage according to radar system parameters, typical unmanned aerial vehicle radar scattering characteristics and environmental noise levels, and are stored in the upper management platform and the multi-band radar detection device, so as to ensure that each site adopts consistent determination standards.

[0063] In an embodiment, the effective detection frequency threshold is set to be between 5 and 20 according to the detection period. When the detection period is 100 milliseconds, the corresponding continuous detection time threshold is 0.5 seconds to 2 seconds. The continuous effective detection time is obtained by counting the number of periods in which effective detection results appear continuously in adjacent detection periods. When the number of periods exceeds the pre-set period number, it is considered that a stable echo is formed on the candidate sub-band. In the evaluation of echo amplitude and Doppler parameter variation, the system calculates the difference between the maximum and minimum values of the echo amplitude according to a predetermined time window, and counts the proportion of the number of detections exceeding the deviation threshold to the total number of effective detections. When the proportion is less than 1% and the amplitude variation range does not exceed the pre-set amplitude fluctuation range, it is determined that the echo variation of the candidate sub-band is stable. The trajectory matching proportion threshold can be set to be between 60% and 80% according to the size of the protection area. When the proportion of the detection points satisfying the trajectory envelope constraint reaches or exceeds the proportion, it is considered that the candidate sub-band is basically consistent with the comprehensive estimated trajectory on the spatial motion trajectory. Through the setting of the above numerical range, the frequency band effectiveness characteristics can maintain a certain robustness in a complex noise background, and the number of selected frequency bands will not be too small due to too strict conditions.

[0064] After obtaining the effective detection frequency, continuous effective detection time, echo stability and trajectory matching degree of each suspected unmanned aerial vehicle target on each candidate sub-band, the candidate sub-bands are classified and labeled.

[0065] For the candidate sub-band that meets the following conditions simultaneously: the number of valid detections is greater than or equal to the threshold of the number of valid detections, the continuous valid detection duration is greater than or equal to the threshold of the continuous duration, the echo amplitude and Doppler parameter stability degree meet the stability threshold condition, and the trajectory matching degree is greater than or equal to the matching proportion threshold, mark it as the preferred frequency band corresponding to the target, and use it to form a candidate set of recommended tracking frequency band set; for the candidate sub-band that does not meet the preferred conditions in terms of the number of valid detections or the continuous valid detection duration, or the stability degree and the trajectory matching degree, but does not trigger the risk judgment condition, mark it as an inefficient frequency band, and do not preferentially use it for subsequent countermeasures frequency band selection; for the candidate sub-band that has a frequency overlap relationship with the protected service frequency band, or the candidate sub-band that meets the pre-defined interference feature condition in terms of abnormally high power, abnormally wide band occupation, continuous interference characteristics, etc. in the monitoring process, mark it as a risk frequency band. The marking result is stored in the frequency band performance feature set together with the preferred frequency band and the inefficient frequency band marking, and provides a clear classification basis for subsequent generation of adaptive frequency band identification results, construction of recommended tracking frequency band set and candidate countermeasures frequency band set.

[0066] Step 3, combine the frequency band performance feature, local spectrum occupation and protected frequency band information to generate an adaptive frequency band identification result for the target UAV. The adaptive frequency band identification result includes a recommended tracking frequency band set and a candidate countermeasures frequency band set. Compare the adaptive frequency band identification result with the transmission record to form a monitoring data frame containing the correspondence between the anti-UAV interference device transmission configuration and the candidate countermeasures frequency band. The specific implementation is as follows:

[0067] The pre-defined interference feature condition is set according to historical spectrum measurement results and monitoring requirements in the system configuration stage, including at least one or more of the following cases: in the sub-band where no legal service is planned in the target area, continuously detect a wideband continuous signal higher than the preset threshold of background noise; in a short time window, the sub-band is detected as a signal emitted by multiple devices simultaneously and having an abnormal duty cycle; high-power radiation is observed in a direction that does not match the system registered device. Statistically judge the power change record of each sub-band over time. When the corresponding condition of any sub-band meets the pre-set number of times threshold for a number of consecutive observation periods, mark the sub-band as a risk frequency band, and write the marking into the frequency band performance feature set.

[0068] In an embodiment, the candidate frequency band set is cyclically scanned at time intervals of tens of milliseconds to one second, and the instantaneous power, average power and service occupation identification of each sub-band are recorded in time series. For sub-bands without planned legal services, when the average power is higher than the background noise threshold in consecutive observation periods, and the instantaneous power curve presents the characteristics of approximate flatness or periodic switching, the sub-band is marked as a suspected illegal emission frequency band. For sub-bands with registered legal services, when there is long-time high occupation during non-service working period, or obvious wideband noise envelope is superimposed on the basis of normal service work, the sub-band is marked as a sub-band with additional interference risk. The risk frequency band marking is written in the frequency band performance feature set in the form of a field, and the field content includes risk type, risk occurrence times and the latest occurrence time, which is used for filtering and tracking in subsequent scheduling reference scheme generation.

[0069] After completing the generation of frequency band performance features and the marking of preferred frequency bands, low-efficiency frequency bands and risk frequency bands, the upper management platform or the edge monitoring terminal obtains local spectrum occupation information and protected frequency band information from the preconfigured configuration.

[0070] The local spectrum occupation information is obtained by the spectrum monitoring receiver deployed at the site or by the multi-frequency band radar idle period scanning, and contains the actual in-use state, occupation time proportion, average or maximum service signal power and other indicators of each frequency band within a predetermined time window.

[0071] The protected frequency band information is a specific service frequency band list preconfigured according to the national or industry frequency allocation table and management regulations, including the corresponding center frequency and allowed bandwidth range of civil air traffic control, radio navigation, public communication, important special communication, etc. For each suspected unmanned aerial vehicle target, the candidate sub-band marked as a preferred frequency band is extracted from the frequency band performance feature set corresponding to the target, and the preferred frequency band that meets the effective detection times threshold and the trajectory matching degree threshold within the continuous detection window is selected. These preferred frequency bands that meet the conditions form the recommended tracking frequency band set of the target. Each sub-band in the recommended tracking frequency band set still retains the center frequency, bandwidth and statistical characteristics associated with the target, which are used for tracking and evaluation.

[0072] After obtaining the recommended tracking frequency band set, a candidate countermeasure frequency band set is generated based on the local spectrum occupation information and the protected frequency band information.

[0073] Specifically, for each sub-band in the recommended tracking frequency band set, first determine whether there is an overlap relationship between the sub-band and the frequency range of any protected service frequency band in the protected frequency band information. If the center frequency or the effective bandwidth range falls within the protected service frequency band range, the sub-band is excluded from the candidate countermeasure frequency band set. Then, according to the local spectrum occupation information, determine whether the sub-band is long-term high-occupied by legal services within a predetermined time window. If the occupation ratio exceeds the configured threshold, the sub-band is not included in the candidate countermeasure frequency band set. At the same time, check whether the sub-band has been marked as a risk frequency band in the frequency band performance characteristics. If it has been marked as a risk frequency band, the sub-band is excluded.

[0074] The subset of the recommended tracking frequency band set that is not excluded and not marked as a risk frequency band constitutes the candidate countermeasure frequency band set corresponding to the target. Through the above steps, the adaptive frequency band identification result is explicitly expressed as two sets corresponding to a single target, i.e., the recommended tracking frequency band set and the candidate countermeasure frequency band set. The element source, screening condition and constraint rule of the two sets are set in advance in the configuration parameters and threshold values, and are uniformly stored in the system to ensure consistency and repeatability when different sites are executed.

[0075] After completing the generation of the adaptive frequency band identification result, the edge monitoring terminal compares the result with the aforementioned transmission records using a unified time reference to construct a monitoring data frame. Specifically:

[0076] For the transmission record of each jamming device within a predetermined time window, read the current working frequency band, transmission power and countermeasure mode in the record, and obtain the corresponding site identifier according to the site configuration. For each transmission record, in turn, determine whether the current working frequency band belongs to any sub-band in the candidate countermeasure frequency band set corresponding to the target. If it does, mark the record as belonging to the candidate countermeasure frequency band in the corresponding relationship field.

[0077] If it does not belong to the candidate countermeasure frequency band set, further determine whether the working frequency band belongs to the risk frequency band of the target or the risk frequency band list maintained by the system. If it does, mark the corresponding relationship field as falling into the risk frequency band.

[0078] If neither belongs to the candidate countermeasure frequency band set nor to the risk frequency band, mark the corresponding relationship field as deviating from the candidate countermeasure frequency band.

[0079] The edge monitoring terminal combines the above-mentioned corresponding relationship field with the target identifier, site identifier, recommended tracking frequency band set and candidate countermeasure frequency band set in the adaptive frequency band identification result, current working frequency band, transmission power and countermeasure mode according to a predetermined data structure to form a monitoring data frame, and reports it to the superior management platform through a secure communication link.

[0080] For example, during a large city marathon event, multi-band radar detection devices and edge monitoring terminals are deployed at the start and finish points and key road intersection of the racecourse, and the candidate frequency band set is configured as four sub-bands. During the race, a low-altitude small unmanned aerial vehicle appears in the sky of a certain section of the racecourse. The multi-band radar detects suspected target echoes on multiple sub-bands. Through frequency band effectiveness feature calculation, it is found that on two of the sub-bands: the effective detection times remain continuously, the echo amplitude and Doppler parameter changes are stable and consistent with the target trajectory, and are marked as preferred frequency bands; another sub-band is scattered and unstable, and is marked as an inefficient frequency band; and another sub-band partially overlaps with the local private network frequency band, and is marked as a risk frequency band. Accordingly, the system forms the recommended tracking frequency band set of the unmanned aerial vehicle target from the two preferred sub-bands, and includes one of the preferred sub-bands in the candidate countermeasure frequency band set after excluding the risk frequency band, and only selects the jamming frequency band in this small range to provide clear basis and avoid affecting the event communication and command private network.

[0081] Step 4, the upper management platform receives the monitoring data frame, evaluates the monitoring and countermeasure ability of the monitoring sites with coverage ability according to the adaptive frequency band identification result, the location of the anti-unmanned aerial vehicle jamming device at each monitoring site and the available sub-band range, generates a scheduling reference scheme in the recommended tracking frequency band set and the candidate countermeasure frequency band set range to avoid risk frequency bands, and outputs in the form of scheduling suggestions, and the specific implementation is:

[0082] The upper management platform includes a data receiving module, a target and device association module, a scheduling calculation module and a spectrum security verification module. The data receiving module continuously receives the monitoring data frame reported by each edge monitoring terminal. The monitoring data frame includes at least the target identifier, the site identifier, the recommended tracking frequency band set and the candidate countermeasure frequency band set in the adaptive frequency band identification result, the current working frequency band of the jamming device, the transmission power, the countermeasure mode, and the corresponding relationship field of the current working frequency band relative to the candidate countermeasure frequency band set and the risk frequency band marker. The target and device association module groups the sites in the same protection area and having detection or jamming capability for the same target into a candidate site set according to the target identifier and the site identifier, and reads the device identifier, geographic location, coverage area parameters (including working height range, azimuth coverage range, distance coverage range), available sub-band set and corresponding maximum power parameter of the jamming device in each candidate site from the system configuration library to form a candidate jamming device description table for the target.

[0083] The scheduling calculation module selects the devices participating in interference for each target and determines the working sub-bands and transmission parameters of the devices based on the adaptive frequency band identification result provided by the candidate interference device description table and the monitoring data frame. For each target, the candidate countermeasure frequency band set given by the adaptive frequency band identification result is regarded as the selectable frequency band range. The scheduling calculation module first selects the devices whose geographic positions and coverage areas can cover the current or predicted position of the target from the candidate interference devices, and only the interference devices meeting the coverage condition are regarded as selectable devices.

[0084] In an embodiment, first, based on the position and flight direction of the target UAV, the upper limit of the theoretical field strength contribution of each interference device at the target position is calculated in combination with the coverage area geometric model of each interference device. Only the devices that can form effective field strength near the target and will not form over-limit field strength in the protected area are retained as candidate devices. Subsequently, the candidate devices are sorted according to the threat level of the target. For a target with a higher threat level, devices with a shorter distance and a larger power margin are preferentially selected. A working sub-band is selected from the intersection of the candidate countermeasure frequency band set and the available sub-band set of the device. The sub-band that is frequently marked as an effective configuration is placed in the priority order. For the case where multiple devices jointly work for the same target, the recommended working sub-bands of multiple devices are cross-checked according to the distance between the devices and the coverage overlap area, so as to avoid the combination configuration that may exceed the threshold after field strength superposition in the same coverage overlap area.

[0085] Subsequently, for each selectable interference device, the available sub-band set thereof is obtained, and the intersection of the available sub-band set and the candidate countermeasure frequency band set of the target is calculated to obtain the available working sub-band set of the device under the target task. If the available working sub-band set of a certain interference device related to the target is empty, the device is not included in the scheduling object of the target.

[0086] If the available working sub-band set is not empty, a single working sub-band is selected from the available working sub-band set in a preset priority order (for example, the sub-band marked as the preferred frequency band is preferentially selected, and the sub-band with more unused frequency resources is secondly selected). The working transmission power of the device in the task period is determined in combination with the maximum power generation parameter of the device, the preset task type and the protection requirement, so that each interference device uses only one explicitly specified working sub-band and a corresponding set of transmission parameters in the same period, and a preliminary scheduling reference scheme is obtained.

[0087] The spectrum safety checking module performs spectrum safety and inter-site conflict checking on each working sub-band involved in the preliminary scheduling reference scheme.

[0088] For each selected working sub-band, first check whether there is an overlap relationship between its frequency range and the frequency range in the protected service frequency band information, if there is an overlap, remove the sub-band from the selectable set of the corresponding device and reselect other sub-band, if there is no other available sub-band, cancel the scheduling of the device on the target;

[0089] Then, according to the geographical position of the interference device, the antenna pattern and the adopted transmission power parameters, the field strength estimation value of the working sub-band at the boundary of the preset protection area is calculated by using the segmented estimation method: specifically, according to the distance of the device to the boundary of the protection area, the antenna directional gain and the free space propagation loss or the known propagation model, the transmission power is attenuated on the propagation path to obtain the received power at the boundary, and then the received power is converted into the field strength estimation value according to the corresponding relationship between the received power and the electric field strength in electromagnetics, and compared with the preset field strength threshold value, when the estimated field strength exceeds the field strength threshold value, it is judged that the configuration has interference risk, the sub-band is deleted from the configuration of the device and other sub-band is tried to be selected; if there is no suitable sub-band, the device is not enabled to participate in the task.

[0090] For the sites located in adjacent or overlapping coverage areas, if they are assigned the same working sub-band in the preliminary scheduling reference scheme, the field strength estimation in the superposition area of the coverage area is checked, and when the superposition field strength may exceed the field strength threshold value, the working sub-band of one of the sites is adjusted to a different sub-band in the candidate countermeasure frequency band set, or the scheduling of the site is cancelled, so that there is no configuration in the final scheduling reference scheme that produces uncontrolled superimposed interference to the same target or the same area.

[0091] After completing the spectrum safety verification and conflict adjustment, the upper management platform issues the final scheduling reference scheme to the corresponding edge monitoring terminal and anti-UAV interference device in the form of containing target identification, participating interference device identification, corresponding working sub-band of each interference device, transmission power and countermeasure mode, and the edge monitoring terminal configures the interference device according to the scheduling reference scheme to ensure that the scheduling execution process is consistent with the aforementioned adaptive frequency band identification result, spectrum constraint condition and risk frequency band marking.

[0092] Therefore, after receiving the scheduling reference scheme issued by the upper management platform, the edge monitoring terminal writes the working sub-band, transmission power and countermeasure mode in the scheduling reference scheme that matches the local interference device identification into the configuration register or control command buffer of the interference device through the local control interface, triggers the interference device to switch or start transmission according to the specified parameters; the actual working frequency band, transmission power and countermeasure mode of the interference device continue to be fed back to the edge monitoring terminal through the state reporting channel, which is used for consistency checking with the scheduling reference scheme and forming subsequent monitoring data frames.

[0093] For example, in an anti-UAV system deployed in the vicinity of an airport, the superior management platform receives multiple site uploaded monitoring data frames and finds that a suspicious UAV is flying low along the outside of the approach route. The adaptive frequency band identification result for the target gives a recommended tracking frequency band set and a candidate countermeasure frequency band set, while marking the risk frequency bands overlapping with the airport navigation station and approach radar services. The platform selects two jamming devices that can cover the UAV's location according to the site location and coverage area, and from their respective available sub-band sets, only selects a single working sub-band that belongs to the candidate countermeasure frequency band set and is not in the risk frequency band, and configures the transmission power according to the device capability. For the case where adjacent sites are about to use the same sub-band, the superposition field strength is estimated for verification. For configurations that may affect navigation facilities, automatic adjustment is made to different sub-bands. The final scheduling reference scheme only implements interference on the UAV in the selected safe frequency band, meeting the countermeasure requirements without occupying and interfering with the existing navigation and communication frequency bands of the airport.

[0094] Step 5: During the operation of the monitoring system, the multi-band radar collects target echoes in the recommended tracking frequency band set, associates echo characteristics with corresponding frequency band configurations, generates frequency band configuration category labels according to pre-set rules, and updates frequency band performance characteristics, adaptive frequency band identification rules, and scheduling reference scheme generation rules. The specific implementation is as follows:

[0095] After the superior management platform generates and outputs the scheduling reference scheme, when the scheduling reference scheme is adopted by the air defense command system, the on-duty personnel, or other control units and used to configure anti-UAV jamming devices, the multi-band radar detection device continues to collect echoes and track the target in the recommended tracking frequency band set corresponding to the scheduling reference scheme. Under the unified time reference, the superior management platform time-aligns and identifies the target identification, the proposed interference device identification, the working sub-band and the transmission power parameters of each interference device recorded in the scheduling reference scheme, the actual working sub-band and the transmission power state of the interference device reported by the edge monitoring terminal, and the target echo data reported by the multi-band radar detection device, forms frequency band configuration records with target identification, working sub-band, transmission power parameters, and scheduling start and end time as key values, and adds echo amplitude changes, effective detection state changes, and target trajectory changes in the recommended tracking frequency band set within the corresponding time interval to each frequency band configuration record for subsequent classification and judgment.

[0096] The target trajectory change includes whether it is continuously and stably tracked, whether it has a stable height change or a direction deviation, whether it enters a predefined safe area or executes a return trajectory, and whether it completely loses valid echoes within a preset time window after the configuration takes effect.

[0097] The superior management platform pre-configures the frequency band configuration category determination rule in the rule base. For each frequency band configuration record, the configuration category label is generated according to the associated echo characteristics and risk information within the corresponding evaluation time window.

[0098] Specifically, when the frequency band configuration specified in the scheduling reference scheme is adopted and takes effect, the proportion of the effective detection times of the target on the recommended tracking frequency band set in the total number of detection periods in the continuous detection periods is not less than the preset effective detection proportion threshold, and the target trajectory characteristics meet one or more of the pre-defined effective response conditions (for example, the target appears a sustained downward trend in the height direction, deviates to the safe area or forced landing area in the horizontal position, and appears a sustained decreasing trend in the speed, etc., and these behavior patterns are solidified in the rule base in the form of explicit condition combination in the system deployment stage), and no risk frequency band label or electromagnetic interference alarm related to the current working sub-frequency band is triggered within the time window, the superior management platform marks the frequency band configuration record as an effective configuration.

[0099] When the frequency band configuration is adopted and takes effect, the effective detection times of the target on the recommended tracking frequency band set within the monitoring time window are less than the effective detection proportion threshold, or although a certain detection time is maintained, the target trajectory does not appear a change meeting the above-mentioned effective response conditions, and no risk event related to the current working sub-frequency band is detected within the time window, the superior management platform marks the frequency band configuration record as an inefficient configuration. Correspondingly, when the current working sub-frequency band belongs to the pre-maintained risk frequency band list during the effective period of the frequency band configuration, or one or more of the following conditions is detected through the spectrum monitoring result: abnormal power lifting appears in the non-target direction, obvious interference characteristics appear in the protected business frequency band, or the superimposed field strength estimation value of multiple sites on the same sub-frequency band exceeds the preset field strength threshold, the superior management platform marks the frequency band configuration record as a risk configuration. The detection period number, the evaluation time window length, the effective detection proportion threshold, the trajectory deviation threshold, the field strength threshold and the risk event triggering condition in the above-mentioned determination rule are set according to the multi-frequency band radar performance parameters, the anti- unmanned aerial vehicle task requirements and the electromagnetic environment constraints in the system deployment and calibration stage, and are stored in the rule base in the form of fixed configuration. In the running process, the rule base is strictly executed, and does not depend on the temporary experience judgment of the on-site personnel.

[0100] After obtaining the effective configuration, inefficient configuration and risk configuration labels of the frequency band configuration, the superior management platform updates the frequency band performance characteristics, adaptive frequency band identification rules and scheduling reference scheme generation rules periodically based on the cross-task accumulated frequency band configuration records, to form an adaptive optimization mechanism with memory. Specifically, for a working sub-frequency band that is recorded as an effective configuration in different tasks and reaches the minimum record number parameter and is not labeled as a risk configuration, the superior management platform increases its preferred weight in the frequency band performance characteristics corresponding to the sub-frequency band, keeps or promotes it as a preferred frequency band, and gives it a higher selection order when generating the recommended tracking frequency band set and the candidate countermeasure frequency band set subsequently;

[0101] For a working sub-frequency band that is labeled as an inefficient configuration in the historical records and reaches the minimum record number parameter and does not meet the preferred condition, the superior management platform reduces its priority in the frequency band performance characteristics, adjusts it as an inefficient frequency band or degrades it from the candidate countermeasure frequency band set; for a working sub-frequency band that is labeled as a risk configuration in the historical records and reaches the minimum record number parameter, the superior management platform adds the sub-frequency band to the risk frequency band list or deletes it from the candidate countermeasure frequency band set corresponding to the related target type, so that the subsequent scheduling reference scheme no longer recommends using the sub-frequency band.

[0102] The minimum record number parameter is given a determined value in the system configuration, for example, set to two or three, to control the triggering condition of the rule update action and avoid frequent fluctuations in frequency band priority or risk labeling due to single accidental events.

[0103] In the above updating process, the superior management platform maintains independent frequency band performance characteristic sets, adaptive frequency band identification rule sets and scheduling reference scheme generation rule sets for different regional electromagnetic environment conditions and different types of unmanned aerial vehicle targets, and selects the corresponding rule set for application according to the target region information and target type information when a new task arrives, so that the frequency band identification and scheduling reference generation better adapt to regional differences and target characteristics.

[0104] In an embodiment, the superior management platform establishes an independent task database for each protection region, which includes a frequency band configuration record table, a frequency band performance characteristic table and a rule version table. The frequency band configuration record table takes the task identifier and the target identifier as the primary key, records the configuration state and the corresponding configuration category label of each working sub-frequency band within the task duration; the frequency band performance characteristic table takes the sub-frequency band identifier and the region identifier as the primary key, records the cumulative number of effective configurations, the cumulative number of inefficient configurations and the cumulative number of risk configurations of the sub-frequency band in the region;

[0105] The system performs rule updating operation according to preset updating period, which can be set to perform immediately after task ends, or perform batch updating by hour level or day level, and in each updating, the statistical result in the frequency band performance feature table is compared with the minimum record number parameter to determine whether to adjust the preferred state and risk marking state of each sub-frequency band, and the time and version number of this updating are recorded in the rule version table, so as to trace back to the historical configuration when abnormal situation occurs.

[0106] The above multiple determination conditions are realized by configuring the minimum record number parameter, which is given a certain value in system configuration, for example, set to two or three times, when a sub-frequency band is marked by the same category in the historical record to reach the certain number, the corresponding adjustment action is triggered, the superior management platform maintains independent frequency band performance feature set, adaptive frequency band identification rule set and scheduling reference scheme generation rule set for different regional electromagnetic environment conditions and different types of unmanned aerial vehicle targets in the updating process, and when a new task comes, the corresponding rule set is selected and applied according to the target region information and target type information.

[0107] Different regional electromagnetic environment conditions are distinguished by the regional configuration table in the superior management platform, the regional configuration table allocates a unique regional identifier for each protection region, and records the protected frequency band list, resident legal business type and typical noise level parameter in the region; different types of unmanned aerial vehicle targets are distinguished by the target type identifier output by the target identification module, which can be determined by rules or models according to target size, speed range, flight height and known control link system.

[0108] When updating the frequency band performance feature and the adaptive frequency band identification rule, the superior management platform maintains the corresponding rule set by taking the above regional identifier and target type identifier as index key, so that different priority and risk marking configuration can be formed for the same sub-frequency band in different regions or different target types.

[0109] The present application realizes efficient monitoring and accurate countermeasures of the unmanned aerial vehicle target in a complex electromagnetic environment by constructing a closed-loop control mechanism of frequency band performance feature extraction, adaptive frequency band identification and interference device scheduling linkage. By fusing radar echo data and interference device transmission records, dynamically marking the pros and cons of the frequency band based on multi-band target detection characteristics, constructing a frequency band performance feature map with environment perception capability, avoiding interference failure or accidental injury to protected services caused by the use of fixed frequency bands, forming a recommended tracking frequency band and candidate countermeasure frequency band set with dynamic adjustability by means of candidate frequency band and risk frequency band joint comparison mechanism, realizing the optimal matching between frequency band identification and device capability, intelligently generating a scheduling reference scheme according to the target position, device capability and spectrum safety constraints, and updating the frequency band configuration priority and risk label in combination with echo tracking feedback, realizing the linkage adaptive optimization of the three stages of identification, scheduling and feedback, and improving the spectrum utilization efficiency, regulation accuracy and task success rate of the anti-unmanned aerial vehicle system in a dynamic complex scene.

[0110] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product.

[0111] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0112] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0113] The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0114] Finally, the above is only a preferred embodiment of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A counter-drone monitoring and scheduling method with adaptive frequency band identification, characterized in that: The specific steps include: Multi-band radar detection devices and edge monitoring terminals are deployed in the protected area. The radar and anti-drone jamming equipment are synchronized according to a unified time reference. The receiving channels are configured in rotation within the candidate frequency bands to monitor the electromagnetic signals in the airspace and receive the echo or radiation signals of the target drone. The edge monitoring terminal collects the electromagnetic wave signals of the target drone and possible external electromagnetic interference signals, monitors the operating frequency band, transmission power and countermeasure mode of the anti-drone jamming equipment and generates transmission records. Target detection and association are performed on the target echo data in the monitoring data. The echoes of suspected UAVs in each candidate frequency band are summarized according to the target. The frequency band performance characteristics are calculated based on the number of detections, stability and motion feature matching degree. Candidate frequency bands are selected, inefficient and risky are marked. Combining frequency band performance characteristics, local spectrum occupancy, and protected frequency band information, an adaptive frequency band identification result is generated for the target UAV. The adaptive frequency band identification result includes a recommended set of tracking frequency bands and a set of candidate countermeasure frequency bands. The adaptive frequency band identification result is compared with the transmission record to form a monitoring data frame containing the correspondence between the transmission configuration of anti-UAV jamming equipment and the candidate countermeasure frequency bands. The upper-level management platform receives monitoring data frames, evaluates the monitoring and countermeasure capabilities of monitoring stations with coverage capabilities based on the adaptive frequency band identification results, the location of anti-drone jamming equipment at each monitoring station and the available sub-frequency band range, generates a scheduling reference scheme by avoiding risky frequency bands within the recommended tracking frequency band set and candidate countermeasure frequency band set, and outputs it in the form of scheduling suggestions. During the operation of the monitoring system, the multi-band radar collects target echoes within the recommended set of tracking frequency bands, associates the echo characteristics with the corresponding frequency band configuration, generates frequency band configuration category labels according to preset rules, and updates the frequency band performance characteristics, adaptive frequency band identification rules, and scheduling reference scheme generation rules. The frequency band performance characteristics include at least the number of effective detections of the same target in each candidate sub-frequency band, the duration of continuous effective detection, the changes in echo amplitude and Doppler parameters during the preset detection period, and the matching with the target trajectory estimation results; Sub-bands with a number of valid detections and a duration of continuous valid detections that are greater than or equal to a preset threshold and whose matching degree is within a preset range are designated as preferred frequency bands. Candidate sub-bands whose effective detection counts or changes do not meet the preferred selection criteria are marked as inefficient bands. Sub-bands that overlap with protected service frequency bands or meet predefined interference characteristics are marked as risk bands.

2. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 1, characterized in that: The multi-band radar detection device sequentially configures the receiving channel and collects monitoring data within a candidate frequency band set containing at least three sub-bands according to a preset rotation sequence or pseudo-random jump sequence. It records the unified timestamp, candidate sub-band identifier, and receiving parameters associated with each receiving configuration and its corresponding monitoring data. The edge monitoring terminal periodically collects the operating frequency band, transmission power, and countermeasure mode of the anti-UAV jamming equipment and marks the timestamp using the same time reference as the multi-band radar detection device. The monitoring data and transmission records are stored in a unified time axis indexing method.

3. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 2, characterized in that: The adaptive frequency band identification results include a set of recommended tracking frequency bands and a set of candidate countermeasure frequency bands for a single target. The set of recommended tracking frequency bands consists of candidate sub-frequency bands that are marked as preferred frequency bands and meet the thresholds of effective detection times and trajectory matching degree ratio within a continuous detection window. The candidate countermeasure frequency band set is obtained by comparing the recommended tracking sub-frequency band set with the local spectrum occupancy and protected frequency band information, and then removing candidate sub-frequency bands that overlap with protected service frequency bands and candidate sub-frequency bands marked as risky frequency bands.

4. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 3, characterized in that: The monitoring data frame includes at least the target UAV identifier, site identifier, recommended tracking frequency band set and candidate countermeasure frequency band set from the adaptive frequency band identification results, the current operating frequency band, transmission power and countermeasure mode of the anti-UAV jamming device, and the correspondence field between the current operating frequency band and the candidate countermeasure frequency band set and the risk frequency band marker; The correspondence field is used to indicate three states of the jamming device's transmission configuration: belonging to the candidate countermeasure frequency band, deviating from the candidate countermeasure frequency band, or falling into the risk frequency band.

5. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 4, characterized in that: When the superior management platform generates a scheduling reference scheme, it includes: Establish the correspondence between the target UAV and the candidate anti-UAV jamming devices based on the target identifier, adaptive frequency band identification results and site identifier in the monitoring data frame; Obtain the geographical location, coverage area, available sub-frequency band set, and maximum power generation parameters of each candidate anti-drone jamming device; For each target drone, select at least one anti-drone jamming device from the candidate anti-drone jamming devices with coverage capability, and determine the recommended working sub-frequency band from the candidate countermeasure frequency band set corresponding to the drone jamming device. Limit the working sub-frequency band of each anti-drone jamming device to a single sub-frequency band in the same time period.

6. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 5, characterized in that: When the upper-level management platform determines the working sub-frequency bands in the scheduling reference scheme, it performs spectrum security verification on the candidate working sub-frequency bands, including: Search for the frequency relationship between candidate working sub-bands and protected service frequency bands, and remove the corresponding candidate working sub-bands when they overlap; The field strength of candidate working sub-bands within a preset area is estimated based on the location of the interfering equipment, antenna pattern, and transmit power parameters. The estimated field strength is then compared with a preset field strength threshold. Candidate working sub-bands that exceed the field strength threshold are not adopted. Conflict detection is performed on the configurations of monitoring stations located in adjacent areas that are assigned the same candidate working sub-frequency bands. When there is overlap in coverage areas, the working sub-frequency band configurations of some monitoring stations are deleted or adjusted to different working sub-frequency bands.

7. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 6, characterized in that: During the operation of the monitoring system, target echo sequences within the recommended tracking sub-band set, as well as the actual operating sub-band and transmission power of the anti-drone jamming equipment, are collected for each target drone and its corresponding anti-drone jamming equipment. Establish a correlation record between the configuration of the working sub-band and the echo response according to a unified time reference, and mark each working sub-band configuration as an effective configuration, inefficient configuration or risky configuration according to preset judgment conditions. The preset judgment criteria include a comprehensive judgment of changes in echo amplitude, changes in detection status, target trajectory deviation, and whether the target falls within the risk frequency band marker within a continuous detection period.

8. The anti-drone monitoring and scheduling method with adaptive frequency band identification according to claim 7, characterized in that: The upper-level management platform updates the frequency band performance characteristics and adaptive frequency band identification rules based on the effective, inefficient, and risky configurations of the working sub-frequency bands, including: Increase the priority of working sub-bands that have been marked as valid configurations at least twice in the preferred bands; Reduce the priority of or mark as an inefficient frequency band any working sub-band that has been marked as an inefficient configuration at least twice. For working sub-bands that have been marked as risky configurations at least twice, add them to the risky band list or remove them from the candidate countermeasure band set.

9. A method for anti-UAV monitoring and scheduling with adaptive frequency band identification according to claim 8, characterized in that: When updating the adaptive frequency band identification rules and scheduling reference scheme generation rules, the superior management platform maintains independent rule sets and parameter sets for different regional electromagnetic environment conditions and different types of target UAVs. When generating adaptive frequency band identification results and scheduling reference schemes, the platform selects the corresponding rule sets and parameter sets for application based on the target UAV's regional information and target UAV type information.

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