CN116753778A - Unmanned aerial vehicle countering system and method based on information fusion and task distribution - Google Patents

Abstract

The application relates to an unmanned aerial vehicle countering system and method based on information fusion and task allocation, comprising heterogeneous detection equipment, control equipment and countering treatment equipment, wherein the heterogeneous detection equipment is used for detecting a target and sending detection information to the control equipment; the control equipment generates control instruction information according to the detection information and sends the control instruction information to the countering processing equipment; and the countering processing equipment counteres the unmanned aerial vehicle target according to the control instruction information. According to the application, the target detection is carried out through heterogeneous detection equipment (radar, photoelectricity and detection), the detected target information is numbered, compared and fused through establishing a threat target database, threat levels of the targets are judged by utilizing task allocation software, and the treatment priority and proper treatment modes are provided, so that the targets are treated through various treatment means (interference suppression, navigation decoy, laser and unmanned aerial vehicle equipment for patrol).

Description

Unmanned aerial vehicle countering system and method based on information fusion and task distribution

The present application claims priority from China patent office, application No. 2023102302857, application name "unmanned aerial vehicle countering system and method based on information fusion and task distribution", filed on 10/03/2023, the entire contents of which are incorporated herein by reference.

Technical Field

The application belongs to the technical field of unmanned aerial vehicles, and particularly relates to an unmanned aerial vehicle countering system and method based on information fusion and task allocation.

Background

In local military operations in certain areas of the world, the use of drones and clusters of drones has led to a new dimension in war. Up to now, unmanned aerial vehicles are adopted in wars to play an important role in reconnaissance monitoring, target guiding, damage interception, cognitive war and psychological war, and the countermeasures against unmanned aerial vehicles are obviously insufficient. Aiming at the current situation of the reactive command control of the unmanned aerial vehicle, the unmanned aerial vehicle is limited by the information technology, the communication technology and the operational theory level of the development year, and has the defects and defects that the air defense command control equipment system has weak command level multi-system operational capability, the communication network is not robust enough, the motorized communication is difficult to ensure, the recombination is not flexible, the respective air conditions are ensured in a scattered way, the unified air information system is not formed, and the like. At present, the air defense command control system can conduct information arrangement on conventional air targets, such as fighters, bombers and the like, and the discrete unmanned aerial vehicle is similar to the conventional air targets and basically has corresponding auxiliary decision making and command control capability, but has command control loopholes and defects when dealing with small unmanned aerial vehicles and clusters. In view of the demand of command control capability, there are defects of insufficient flexibility, poor capability of real-time control and the like of a command control system facing an unmanned aerial vehicle in a combat time, so that a corresponding effective countercontrol mechanism for the unmanned aerial vehicle is needed to be provided.

Disclosure of Invention

In order to overcome the problems in the prior art, the application provides an unmanned aerial vehicle countering system and method based on information fusion and task allocation, which are used for solving the problems in the prior art.

An unmanned aerial vehicle countering system based on information fusion and task allocation comprises a heterogeneous detection device, a control device and a countering treatment device,

the heterogeneous detection equipment is used for detecting targets of the unmanned aerial vehicle and sending corresponding target information to the control equipment;

the control equipment generates control instruction information according to the target information and sends the control instruction information to the countering processing equipment;

and the countering processing equipment counteres the unmanned aerial vehicle target according to the control instruction information.

Aspects and any possible implementation as described above, further providing an implementation, the heterogeneous detection device includes an unmanned aerial vehicle signal detection device, a photoelectric detection device, and/or a radar detection device, the unmanned aerial vehicle signal detection device being configured to detect a substantially coarse azimuth, pitch, and/or link signal characteristic of the unmanned aerial vehicle target; the photoelectric detection device is used for detecting the fine azimuth and pitching, distance and/or image information of the unmanned aerial vehicle target; the radar detection device is used for detecting the coarse azimuth and pitching, speed and/or distance of the target.

In aspects and any possible implementation manner as described above, there is further provided an implementation manner, where the photodetection device includes an infrared detection module, a visible light detection module, and/or a laser ranging module.

Aspects and any of the possible implementations as described above, further provide an implementation in which the control device includes a threat goal fusion database and a treatment task allocation software, and the two are interconnected inside the control device.

Aspects and any possible implementation as described above, further providing an implementation, the countering treatment apparatus includes a drone signal interference suppression device, a navigation decoy device, a laser damage device, and/or a drone cruising device.

Aspects and any possible implementation manner as described above, further provide an implementation manner, the unmanned aerial vehicle device includes a plurality of unmanned aerial vehicle ground stations that patrol and fly, unmanned aerial vehicle that patrol and fly connects and patrol and fly the unmanned aerial vehicle ground station, patrol and fly the unmanned aerial vehicle and carry out the aerial reaction to the unmanned aerial vehicle target.

Aspects and any of the possible implementations as described above, further provide an implementation, the navigation decoy device including decoy a GPS navigation signal, a galileo navigation signal, a GLONASS navigation signal, or a beidou navigation signal of the unmanned aerial vehicle target.

In the aspect and any possible implementation manner described above, there is further provided an implementation manner, where the radar detection apparatus includes two operation modes of tracking while searching and tracking while scanning.

Aspects and any possible implementation as described above, further providing an implementation, the drone signal interference suppression device includes uplink suppression interference, downlink suppression interference, inter-machine link suppression interference, and/or navigation link suppression interference on the drone target.

The application also provides a countering method of the unmanned aerial vehicle countering system based on information fusion and task allocation, wherein the method is realized by adopting the system and comprises the following steps:

s1, numbering unmanned aerial vehicle targets detected by a heterogeneous detection device, and writing target information corresponding to the unmanned aerial vehicle targets into a threat target fusion database of control equipment corresponding to the numbering;

s2, according to the target information, guiding other heterogeneous detection equipment to search an area where the unmanned aerial vehicle target is located, comparing and fusing the detected new target information, confirming whether the unmanned aerial vehicle target is an existing target in a threat target fusion database, if so, writing the new target information into a corresponding target number of the threat target fusion database, if so, giving a new number to the unmanned aerial vehicle target, and writing the target information of the unmanned aerial vehicle target into the corresponding target number of the threat target fusion database;

s3, according to the target information in the threat target fusion database, when the number of targets detected by the heterogeneous detection equipment is consistent, and the fine level azimuth and the pitching information in the threat target fusion database are within the coarse level azimuth and the pitching, merging the target information of the threat target fusion database to the same number; when the number of targets detected by the heterogeneous detection equipment is inconsistent, directly giving the coarse first-level target information of the threat target fusion database to the number of the fine first-level threat target fusion database;

s4, after the threat target fusion database fuses the target information, covering the azimuth and pitch information of the fine level target with the azimuth and pitch information of the coarse level target;

s5, generating control instruction information according to the information of the threat target fusion database in the S4, and transmitting the control instruction information to an unmanned aerial vehicle signal interference suppression device, a navigation decoy device, a laser damage device and/or a patrol unmanned aerial vehicle device, wherein the unmanned aerial vehicle targets are counteracted by the devices according to the instruction information.

The beneficial effects of the application are that

Compared with the prior art, the application has the following beneficial effects:

according to the application, the target detection is carried out through heterogeneous detection equipment (radar, photoelectricity and detection), the detected target information is numbered, compared and fused through establishing a threat target database, threat levels of the targets are judged by utilizing task allocation software, and the treatment priority and proper treatment modes are provided, so that the targets are treated through various treatment means (interference suppression, navigation decoy, laser and unmanned aerial vehicle equipment for patrol). Compared with the prior art, the system and the method have the advantages that the threat target information processing flow is simple and convenient to judge, the threat level of the target is determined by means of comparison and sequencing instead of manual hard regulation, the treatment means of the target are flexible and various, and the system and the method have multi-target capability and autonomous operation capability.

Drawings

Fig. 1 is a block diagram of a system architecture of the present application.

Wherein, in the figure: 1. the unmanned aerial vehicle signal detection device; 2. a photoelectric detection device; 3. a radar detection device; 4. threat target fusion database; 5. handling task allocation software; 6. the unmanned aerial vehicle signal interference suppression device; 7. navigation decoy means; 8. a laser damaging device; 9. unmanned aerial vehicle device patrols and flies.

Detailed Description

For a better understanding of the present application, the present disclosure includes, but is not limited to, the following detailed description, and similar techniques and methods should be considered as falling within the scope of the present protection. In order to make the technical problems, technical solutions and advantages to be solved more apparent, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.

It should be understood that the described embodiments of the application are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

As shown in fig. 1, the application provides an unmanned aerial vehicle countering system based on information fusion and task allocation, which comprises a heterogeneous detection device, a control device and a countering treatment device,

the heterogeneous detection equipment is used for detecting an unmanned aerial vehicle target and sending detection information to the control equipment;

the control equipment generates control instruction information according to the detection information and sends the control instruction information to the countering processing equipment;

and the countering processing equipment counteres the unmanned aerial vehicle target according to the control instruction information.

The heterogeneous detection equipment comprises an unmanned aerial vehicle signal detection device 1, a photoelectric detection device 2 and a radar detection device 3, wherein the unmanned aerial vehicle signal detection device 1 is used for detecting rough azimuth, pitching and/or link signal characteristics of an unmanned aerial vehicle target; the photoelectric detection device 2 is used for detecting the fine azimuth and pitching, distance and/or image information of the unmanned aerial vehicle target; the radar detection means 3 are for detecting coarse azimuth and pitch, speed and/or distance of the target.

Further, the control device comprises a threat objective fusion database 4 and a treatment task allocation software 5; the countering treatment equipment comprises an unmanned aerial vehicle signal interference suppression device 6, a navigation decoy device 7, a laser damage device 8 and/or a fly-by-the-fly unmanned aerial vehicle device 9, wherein all or part of the devices can be used, and part or all of the devices are selected according to actual needs.

The detection information of heterogeneous detection equipment such as an unmanned aerial vehicle signal detection device 1, a photoelectric detection device 2, a radar detection device 3 and the like is transmitted to control equipment provided with a threat target fusion database and treatment task allocation software through a cable or a wireless module, and the control equipment is realized by adopting a computer; the threat target fusion database 4 and the treatment task allocation software 5 realize interconnection and intercommunication of data in the computer; the control instruction information formed by the treatment task allocation software 5 is transmitted to multidimensional counteraction treatment equipment such as an interference suppression device 6, a navigation decoy device 7, a laser damage device 8, a fly-by-the-air unmanned aerial vehicle device 9 and the like through a cable or a wireless module, and the operation of the devices is controlled and guided.

Further, the unmanned aerial vehicle signal detection device 1 can detect unmanned aerial vehicle links and obtain rough azimuth, pitching and/or link signal characteristics of unmanned aerial vehicle targets. The photoelectric detection device 2 comprises an infrared detection module, a visible light detection module and a laser ranging module, and can be used for detecting visible light images, infrared image detection and laser ranging of unmanned aerial vehicle targets and obtaining fine azimuth and pitching, distance and/or image information of the unmanned aerial vehicle targets. The radar detection device 3 comprises two working modes of tracking while searching (TAS) and scanning while Tracking (TWS), and can obtain the coarse azimuth and pitch, speed, distance and/or movement track of the unmanned aerial vehicle target.

Further, the threat target fusion database numbers, fuses and judges target information of the unmanned aerial vehicle targets detected by each heterogeneous detection device, and specifically comprises the following steps: firstly numbering the detected unmanned aerial vehicle targets according to the discovery sequence; secondly, carrying out data fusion processing on corresponding target information obtained by heterogeneous detection equipment, and carrying out information fusion and number combination on target information of the same unmanned aerial vehicle target; thirdly, identifying and judging the type and the model of the unmanned aerial vehicle target through an embedded target identification algorithm based on multidimensional feature fusion; and finally, storing information such as target positions, speeds, tracks, link signal characteristics, types, models and the like of all unmanned aerial vehicles under corresponding numbers in a threat target fusion database. The treatment task allocation software 5 embeds a plurality of algorithms to realize threat discrimination based on threat target fusion database information and single-target or multi-target treatment task allocation based on target characteristics and threat levels.

Further, threat discrimination based on threat target fusion database information comprises threat discrimination based on unmanned aerial vehicle target track prediction and threat discrimination based on unmanned aerial vehicle target model. Firstly, threat level rough sequencing is carried out on unmanned aerial vehicle targets by threat discrimination based on target models, the threat level rough sequencing is carried out on the unmanned aerial vehicle targets through a preset unmanned aerial vehicle threat level experience database, the threat level rough sequencing is matched with unmanned aerial vehicle target models in a threat target fusion database, unmanned aerial vehicle experience threat levels of corresponding models in the preset unmanned aerial vehicle threat level experience database are endowed to all unmanned aerial vehicle targets in the threat target fusion database and marked, and rough sequencing on the threat levels of the unmanned aerial vehicle targets is completed. The threat level experience database of the unmanned aerial vehicle is pre-written with dangerous level experience values of unmanned aerial vehicles of various types. Threat level fine sequencing is carried out on the unmanned aerial vehicle targets with the same threat level by threat discrimination based on unmanned aerial vehicle target track prediction, specifically, the arrival order of the unmanned aerial vehicle targets in the threat target fusion database is predicted according to the track information such as the position, the flight speed, the flight direction and the like of the unmanned aerial vehicle targets in the threat target fusion database, and the threat levels of the targets are sequenced and marked according to the rule that the threat levels are higher when the arrival time is earlier, namely, the threat level fine sequencing is carried out on the unmanned aerial vehicle targets.

Further, the single-target or multi-target treatment task allocation based on the target characteristics and the threat level comprises task allocation based on the target characteristics and task allocation based on the threat level, and the task allocation based on the threat level comprises arranging the treatment sequence by the treatment task allocation software 5 according to the principle of preferentially treating the targets of the unmanned aerial vehicle with the higher risk level; task allocation based on target characteristics comprises the step that the processing task allocation software 5 allocates processing modes for unmanned aerial vehicle targets by utilizing a spatial crowdsourcing optimal task allocation algorithm based on tree decomposition and/or a task allocation algorithm based on a contract net algorithm embedded in the processing task allocation software 5 according to information such as unmanned aerial vehicle target link signal characteristics, types, models, threat levels and the like of threat target fusion databases.

Further, the unmanned aerial vehicle signal interference suppression device 6 includes the suppression interference to the uplink, downlink, inter-machine link and navigation link of unmanned aerial vehicle target, makes unmanned aerial vehicle target unable to receive the control signal that its remote controller of configuration sent, unable passback image data, unable inter-machine communication and/or unable receipt navigation signal, and then makes unmanned aerial vehicle target out of control. The navigation decoy device 7 comprises forward decoy and generation decoy of GPS, galileo, GLONASS and Beidou navigation signals, and misdirects the unmanned aerial vehicle target navigation system by sending false navigation positioning signals so that the unmanned aerial vehicle target deviates from a preset route in subsequent flight. The laser damage device 8 continuously irradiates the photoelectric sensor arranged on the unmanned aerial vehicle target by using continuous laser signals, so that the photoelectric sensor is damaged, and the unmanned aerial vehicle target is dazzled and blinded. The unmanned aerial vehicle device 9 is including patrolling unmanned aerial vehicle ground station, a plurality of unmanned aerial vehicle that patrols, it connects to patrol unmanned aerial vehicle ground station to fly unmanned aerial vehicle through wireless communication module, patrol unmanned aerial vehicle and fly, strike unmanned aerial vehicle target under patrolling unmanned aerial vehicle ground station's guide and/or control and follow, accompany, strike, reach the structure or the function damage to unmanned aerial vehicle target, cause unmanned aerial vehicle target gesture unstability to fall.

The application also provides a countering method of the unmanned aerial vehicle countering system based on information fusion and task allocation, the system of the application is realized by the method, and the method comprises the following steps:

s1, numbering unmanned aerial vehicle targets detected by a heterogeneous detection device, and writing target information corresponding to the unmanned aerial vehicle targets into a threat target fusion database of control equipment corresponding to the numbering;

s2, according to the target information, guiding other heterogeneous detection equipment to search an area where the unmanned aerial vehicle target is located, comparing and fusing the detected new target information, confirming whether the unmanned aerial vehicle target is an existing target in a threat target fusion database, if so, writing the new target information into a corresponding target number of the threat target fusion database, if so, giving a new number to the unmanned aerial vehicle target, and writing the target information of the unmanned aerial vehicle target into the corresponding target number of the threat target fusion database;

s3, according to the target information in the threat target fusion database, when the number of targets detected by the heterogeneous detection equipment is consistent, and the fine level azimuth and the pitching information in the threat target fusion database are within the coarse level azimuth and the pitching, merging the target information of the threat target fusion database to the same number; when the number of targets detected by the heterogeneous detection equipment is inconsistent, directly giving the coarse first-level target information of the threat target fusion database to the number of the fine first-level threat target fusion database;

s4, after the threat target fusion database fuses the target information, covering the azimuth and pitch information of the fine level target with the azimuth and pitch information of the coarse level target;

s5, generating control instruction information according to the information of the threat target fusion database in the S4, and transmitting the control instruction information to an unmanned aerial vehicle signal interference suppression device, a navigation decoy device, a laser damage device and/or a patrol unmanned aerial vehicle device, wherein the unmanned aerial vehicle targets are counteracted by the devices according to the instruction information.

Specifically, the unmanned aerial vehicle signal detection device 1, the radar detection device 3 and the photoelectric detection device 2 in the heterogeneous detection equipment can work simultaneously as required, or two of the unmanned aerial vehicle signal detection devices can work simultaneously or one unmanned aerial vehicle signal detection device and the radar detection device can work singly, and the unmanned aerial vehicle signal detection device, the radar detection device 3 and the photoelectric detection device can be started according to actual requirements. The unmanned aerial vehicle signal detection device 1, the radar detection device 3 and the photoelectric detection device 2 can obtain azimuth and pitching information of an unmanned aerial vehicle target, and detection accuracy of the three devices sequentially comprises the photoelectric detection device 2, the radar detection device 3 and the unmanned aerial vehicle signal detection device 1 from high to low. The above-mentioned various heterogeneous detection devices independently operate, after any detection device detects the unmanned aerial vehicle target, the target information corresponding to the detected unmanned aerial vehicle target is written into the threat target fusion database,

the specific process of the reaction method of the application is as follows:

numbering the unmanned aerial vehicle targets, and writing target information corresponding to the unmanned aerial vehicle targets into a threat target fusion database corresponding to the target numbers;

secondly, according to the target information of the unmanned aerial vehicle, guiding other detection equipment to search an area where the target of the unmanned aerial vehicle is located, endowing new numbers to new targets of the unmanned aerial vehicle detected in the area, and writing the detected corresponding new target information into a threat target fusion database with corresponding numbers;

thirdly, writing all target information in a threat target fusion database in the first step and the second step for data fusion, wherein the number of targets detected by each heterogeneous detection device obtained in the current two steps is consistent, and when the fine level azimuth and pitching information and the coarse level azimuth and pitching information of two or three unmanned aerial vehicle targets in the threat target fusion database are not contradictory, the two or three unmanned aerial vehicle targets are considered to be the same target, then the information of the two or three unmanned aerial vehicle targets is merged into one target number in the threat target fusion database, and when merging, the azimuth and pitching information with highest precision are reserved for overlapped information (namely azimuth and pitching information) of the two or three unmanned aerial vehicle targets, and when non-overlapped information is fully reserved, finally the information of the two unmanned aerial vehicle targets with different numbers is merged into the unmanned aerial vehicle target information with the same number in the threat target fusion database, so that information fusion is completed, the data of the information of unmanned aerial vehicle signal detection devices 1, photoelectric detection devices 3 and radar detection devices 2 are realized, and the target positioning error is reduced; when the number of targets detected by the heterogeneous detection devices obtained in the first step is inconsistent with that of targets detected in the second step, in a threat target fusion database, target information except azimuth and pitching in the target information of the unmanned aerial vehicle is detected by the unmanned aerial vehicle signal detection device 1 or/and the radar detection device 3 and is directly endowed to the information of corresponding labels of the targets of the unmanned aerial vehicle detected by the photoelectric detection device 2; in the threat target fusion database, the characteristic information except azimuth and pitching in the number b is copied to the number a, so that the characteristic information is simultaneously the characteristic information of the unmanned aerial vehicle target of the number a.

Fourthly, judging the type and the model of the unmanned aerial vehicle target through a target recognition algorithm based on multidimensional feature fusion embedded in the threat target fusion database, and storing information such as the type and the model of the unmanned aerial vehicle under the corresponding number of the unmanned aerial vehicle target in the threat target fusion database;

step five, calling an embedded unmanned aerial vehicle threat level experience database through the treatment task allocation software 5, matching the model of the unmanned aerial vehicle target in the threat target fusion database established in the step four, and endowing the threat target fusion database with the experience threat level of the unmanned aerial vehicle of the corresponding model in the threat level experience database with each unmanned aerial vehicle target, so as to finish rough sequencing of threat levels of the unmanned aerial vehicle targets;

sixthly, predicting the arrival order of all unmanned aerial vehicle targets in the threat target fusion database according to the position, the flight speed, the flight direction and other flight path information of all unmanned aerial vehicle targets in the threat target fusion database established in the fifth step through the treatment task allocation software 5, and sequencing all the target threat levels according to the rule that the earlier the arrival time is, the higher the threat level is, so as to finish the fine sequencing of the threat level on the unmanned aerial vehicle targets;

seventh, according to the information of the position, the speed, the flight path, the link signal characteristics, the type, the model, the threat level and the like of the unmanned aerial vehicle target of the threat target fusion database established in the sixth step, the treatment task allocation software 5 generates corresponding treatment means of each unmanned aerial vehicle target according to a task allocation algorithm, generates control command signals, and respectively transmits the control command signals to the unmanned aerial vehicle signal interference suppression device 6, the navigation decoy device 7, the laser damage device 8 and/or the patrol unmanned aerial vehicle device 9, and each treatment device carries out interference or damage countermeasures on the unmanned aerial vehicle target according to the corresponding commands.

After being started, the unmanned aerial vehicle signal interference suppression device 6 releases suppression interference signals, so that an unmanned aerial vehicle target cannot receive control signals sent by a matched remote controller, cannot return image data, cannot carry out inter-machine communication and/or cannot receive navigation signals, and further the unmanned aerial vehicle target is out of control; the navigation decoy device 7 sends false navigation positioning signals after being started, misguides the unmanned aerial vehicle target navigation system, and enables the unmanned aerial vehicle target to deviate from a preset route; after the laser damage device 8 is started, the continuous laser signal is utilized to continuously irradiate the photoelectric sensor of the unmanned aerial vehicle target, so that the photoelectric sensor is damaged, and the dazzling and blinding of the unmanned aerial vehicle target are achieved; the unmanned aerial vehicle device 9 is started and then follows, flies with and impacts the unmanned aerial vehicle target, so that structural or functional damage to the unmanned aerial vehicle target is achieved, and the unmanned aerial vehicle target is enabled to fall in an instable posture.

An example is provided below to illustrate in detail:

example 1

The anti-unmanned aerial vehicle fusion detection system comprises an unmanned aerial vehicle signal detection device, a radar detection device and a photoelectric detection device. When the system is started to work, the system is electrified and unfolded, parameters are configured after self-detection, and an unmanned aerial vehicle signal detection device, a radar detection device and a photoelectric detection device are started to conduct omnidirectional search. When the system alarms, the alarm targets are numbered according to the discovery time, such as a, b, c, d … … and the like, and the alarm target sequences are input into a threat target fusion database, and when the threat target fusion database receives a first threat target signal, the threat levels of targets in the threat target fusion database are initialized and then are input.

If the signal type of the unmanned aerial vehicle target is a radio signal, the azimuth and frequency characteristic information of the unmanned aerial vehicle target is recorded. When the radar detection device 2 detects information of the unmanned aerial vehicle target, identity judgment is carried out on the unmanned aerial vehicle target in a threat target fusion database, and reset numbers are executed, such as merging and splitting operations, the merging judgment standards are that the number of the unmanned aerial vehicle targets detected by the radar detection device is consistent with the number of unmanned aerial vehicles detected by the unmanned aerial vehicle signal detection device 1, and the azimuth of the unmanned aerial vehicle targets detected by the radar detection device 2 is consistent with the azimuth detected by the unmanned aerial vehicle signal detection device 1 within an error allowable range. The splitting judgment standard is that the number of unmanned aerial vehicle targets detected by the radar detection device 2 is larger than the number of unmanned aerial vehicles detected by the unmanned aerial vehicle signal detection device 1 in the same azimuth within the error allowable range, and at the moment, the frequency signals detected by the radio of the unmanned aerial vehicle signal detection device 1 are split into a plurality of frequency signals which are respectively fused under the serial numbers of the radar detection targets. At this time, the threat target fusion database includes information such as radio detection frequency points, distance of radar, flight path, azimuth angle, pitch angle, etc. under the target number.

And according to the distance information of the radar in the threat target fusion database, if the distance exceeds the photoelectric maximum action range, the radar starts a TAS mode and updates the radar detection information of the target in real time. If the distance is within the photoelectric action range, the photoelectric detection device is turned to photoelectrically acquire image information of the target, and the radar enters a TAS mode to keep tracking of the target of the unmanned aerial vehicle. All information detected by the radar detection device and the photoelectric detection device is updated to a threat target fusion database, threat level judgment is carried out by threat target judgment and treatment software, and the sequence of each target in the threat target fusion database is updated.

If the unmanned aerial vehicle target has no radio information, only radar detection information is available, the radar enters a TAS mode, and information such as target direction angle, speed, distance and the like is recorded. And judging whether to start photoelectric tracking according to the distance information. If the distance is within the photoelectric action range, the photoelectric detection device is turned to acquire the image information of the target, and the radar enters a TAS mode to keep tracking of the target. And updating all information detected by the photoelectric detection device into a threat target fusion database.

If the target radio and radar information of the unmanned aerial vehicle are not available, only photoelectric detection information exists, information such as the target direction angle, the size and the image of the unmanned aerial vehicle is recorded in a threat target fusion database.

The method comprises the steps of integrating and updating all information of radio detection, radar detection and photoelectric detection in a threat target fusion database in real time, comparing and judging threat levels of targets in real time by treatment task allocation software, selecting corresponding countermeasures according to the information in the database, generating control instructions aiming at targets of all unmanned aerial vehicles, and commanding all other treatment devices to treat the targets.

If only a single unmanned aerial vehicle target exists in the threat target fusion database, if the unmanned aerial vehicle target has radio signal characteristics, the interference suppression device 6 is utilized to treat, if the unmanned aerial vehicle target does not have radio signals, the navigation decoy device 7 is started to treat, after the first round of treatment, the efficiency evaluation is started, if the unmanned aerial vehicle target is not successfully treated, the inspection unmanned aerial vehicle device 9 and the laser damage device 8 are selected to treat for multiple rounds according to the distance information and the track information.

If a plurality of unmanned aerial vehicle targets exist in the threat target fusion database, a task allocation algorithm is selected in treatment task allocation software, corresponding treatment unmanned aerial vehicle targets are allocated for various treatment means automatically, efficiency evaluation is carried out after treatment is completed, if effective interference and damage are not completed, the unmanned aerial vehicle targets are continuously controlled, and tasks are continuously executed or recovered and closed after the unmanned aerial vehicle targets are controlled.

While the foregoing description illustrates and describes the preferred embodiments of the present application, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as limited to other embodiments, and is capable of numerous other combinations, modifications and environments and is capable of changes or modifications within the scope of the inventive concept as expressed herein, either as a result of the foregoing teachings or as a result of the knowledge or technology of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the application are intended to be within the scope of the appended claims.

Claims (10)

1. An unmanned aerial vehicle countering system based on information fusion and task allocation is characterized by comprising heterogeneous detection equipment, control equipment and countering treatment equipment,

the heterogeneous detection equipment is used for detecting targets of the unmanned aerial vehicle and sending corresponding target information to the control equipment;

the control equipment generates control instruction information according to the target information and sends the control instruction information to the countering processing equipment;

and the countering processing equipment counteres the unmanned aerial vehicle target according to the control instruction information.

2. The unmanned aerial vehicle reaction system based on information fusion and task allocation of claim 1, wherein the heterogeneous detection device comprises unmanned aerial vehicle signal detection means for detecting a substantially coarse azimuth, pitch, and/or link signal characteristics of the unmanned aerial vehicle target, photoelectric detection means, and/or radar detection means; the photoelectric detection device is used for detecting the fine azimuth and pitching, distance and/or image information of the unmanned aerial vehicle target; the radar detection device is used for detecting the coarse azimuth and pitching, speed and/or distance of the target.

3. The unmanned aerial vehicle reaction system based on information fusion and task allocation according to claim 2, wherein the photoelectric detection device comprises an infrared detection module, a visible light detection module and/or a laser ranging module.

4. The unmanned aerial vehicle reaction system based on information fusion and task allocation according to any of claims 1 or 2, wherein the control device comprises threat objective fusion database and handling task allocation software, and both are interconnected inside the control device.

5. The unmanned aerial vehicle countering system based on information fusion and task allocation according to claim 1, wherein the countering treatment equipment comprises an unmanned aerial vehicle signal interference suppression device, a navigation decoy device, a laser damage device and/or a cruise unmanned aerial vehicle device.

6. The unmanned aerial vehicle reaction system based on information fusion and task allocation of claim 5, wherein the unmanned aerial vehicle device comprises a ground station of the unmanned aerial vehicle and a plurality of unmanned aerial vehicles, wherein the unmanned aerial vehicles are connected with the ground station of the unmanned aerial vehicle, and the unmanned aerial vehicle can carry out air reaction to the unmanned aerial vehicle target.

7. The unmanned aerial vehicle reaction system based on information fusion and task allocation of claim 5, wherein the navigation decoy device comprises decoy of a GPS navigation signal, galileo navigation signal, GLONASS navigation signal, or beidou navigation signal of an unmanned aerial vehicle target.

8. The unmanned aerial vehicle reaction system based on information fusion and task allocation according to claim 2, wherein the radar detection device comprises two working modes of tracking, searching and scanning and tracking.

9. The unmanned aerial vehicle reaction system based on information fusion and task allocation of claim 5, wherein the unmanned aerial vehicle signal interference suppression device comprises uplink suppression interference, downlink suppression interference, inter-aerial link suppression interference, and/or navigation link suppression interference on the unmanned aerial vehicle target.

10. A method for countering a countering system of an unmanned aerial vehicle based on information fusion and task allocation, characterized in that the method is implemented by the system according to any one of claims 1 to 9, comprising the steps of:

s1, numbering unmanned aerial vehicle targets detected by a heterogeneous detection device, and writing target information corresponding to the unmanned aerial vehicle targets into a threat target fusion database of control equipment corresponding to the numbering;

s2, according to the target information, guiding other heterogeneous detection equipment to search an area where the unmanned aerial vehicle target is located, comparing and fusing the detected new target information, confirming whether the unmanned aerial vehicle target is an existing target in a threat target fusion database, if so, writing the new target information into a corresponding target number of the threat target fusion database, if so, giving a new number to the unmanned aerial vehicle target, and writing the target information of the unmanned aerial vehicle target into the corresponding target number of the threat target fusion database;

s3, according to the target information in the threat target fusion database, when the number of targets detected by the heterogeneous detection equipment is consistent, and the fine level azimuth and the pitching information in the threat target fusion database are within the coarse level azimuth and the pitching, merging the target information of the threat target fusion database to the same number; when the number of targets detected by the heterogeneous detection equipment is inconsistent, directly giving the coarse first-level target information of the threat target fusion database to the number of the fine first-level threat target fusion database;

s4, after the threat target fusion database fuses the target information, covering the azimuth and pitch information of the fine level target with the azimuth and pitch information of the coarse level target;

s5, generating control instruction information according to the information of the threat target fusion database in the S4, and transmitting the control instruction information to an unmanned aerial vehicle signal interference suppression device, a navigation decoy device, a laser damage device and/or a patrol unmanned aerial vehicle device, wherein the unmanned aerial vehicle targets are counteracted by the devices according to the instruction information.