阅读说明：本技术 基于多源信息的合作与非合作无人机识别方法及系统 (Cooperative and non-cooperative unmanned aerial vehicle identification method and system based on multi-source information ) 是由 罗文三 陈爽 夏鹏辉 于 2019-09-17 设计创作，主要内容包括：本发明提出一种基于多源信息的合作与非合作无人机识别方法及系统,所述方法包括：合作无人机飞行时,实时向无人机监控中心发送主动上报信息；无人机监控中心接收所述主动上报信息并存储；通过雷达探测设备实时获取合作无人机与非合作无人机的位置信息；通过频谱探测设备实时获取合作无人机与非合作无人机的位置、类型、频谱特征信息；将雷达探测设备获取到的信息与频谱探测设备获取到的信息关联,并形成综合探测目标信息；将综合探测目标信息与合作无人机的主动上报信息进行比对,识别出合作无人机与非合作无人机。本发明综合了多源信息对合作无人机与非合作无人机进行识别,可快速、准确识别出合作无人机与非合作无人机。(The invention provides a cooperative and non-cooperative unmanned aerial vehicle identification method and system based on multi-source information, wherein the method comprises the following steps: when the cooperative unmanned aerial vehicle flies, actively reporting information is sent to an unmanned aerial vehicle monitoring center in real time; the unmanned aerial vehicle monitoring center receives and stores the active reported information; acquiring position information of a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle in real time through radar detection equipment; acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through frequency spectrum detection equipment; associating the information acquired by the radar detection equipment with the information acquired by the frequency spectrum detection equipment, and forming comprehensive detection target information; and comparing the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, and identifying the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle. The invention integrates multi-source information to identify the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle, and can quickly and accurately identify the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle.)

1. A cooperative and non-cooperative unmanned aerial vehicle identification method based on multi-source information is characterized by comprising the following steps:

s1, when the cooperative unmanned aerial vehicle flies, active report information is sent to the unmanned aerial vehicle monitoring center in real time;

s2, the unmanned aerial vehicle monitoring center receives and stores active reported information of each cooperative unmanned aerial vehicle in real time;

s3, acquiring the position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through radar detection equipment;

s4, acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through frequency spectrum detection equipment;

s5, correlating the information acquired by the radar detection device with the information acquired by the frequency spectrum detection device according to the position information, forming comprehensive detection target information, and if the correlation is successful, turning to the step S6;

and S6, comparing the frequency spectrum characteristics and the position information in the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, if the comparison conditions are met, determining the cooperative unmanned aerial vehicle, otherwise, determining the cooperative unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

2. The multi-source information-based cooperative and non-cooperative unmanned aerial vehicle identification method according to claim 1, wherein the step S1 is preceded by:

presetting various error thresholds including a radar distance detection threshold, an azimuth detection threshold, a radar pitch detection threshold, a frequency spectrum azimuth threshold, a center frequency error threshold and a bandwidth error threshold.

3. The method for identifying cooperative and non-cooperative unmanned aerial vehicles based on multi-source information according to claim 1, wherein in step S1, the actively reporting information includes: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth.

4. The method for identifying cooperative and non-cooperative unmanned aerial vehicles based on multi-source information according to claim 2, wherein in step S5, the associating the information acquired by the radar detection device and the information acquired by the spectrum detection device according to the location information specifically comprises: and if the difference value of the azimuth angle in the radar detection information and the azimuth angle in the frequency spectrum detection information is smaller than the frequency spectrum azimuth threshold value, the correlation is carried out.

5. The method for identifying cooperative and non-cooperative unmanned aerial vehicles based on multi-source information according to claim 2, wherein in step S6, the comparison condition is: in the comprehensive detection target information and the active reporting information, the central frequency difference value of the comprehensive detection target information and the active reporting information is smaller than the central frequency error threshold value, the bandwidth difference value is smaller than the bandwidth error threshold value, the distance difference value is smaller than the radar distance detection threshold value, the azimuth angle difference value is smaller than the azimuth detection threshold value, and the pitch angle difference value is smaller than the radar pitch detection threshold value;

and when all comparison conditions are met, determining that the unmanned aerial vehicle is a cooperative unmanned aerial vehicle, otherwise, determining that the unmanned aerial vehicle is a non-cooperative unmanned aerial vehicle.

6. A cooperative and non-cooperative unmanned aerial vehicle identification system based on multi-source information is characterized by comprising an unmanned aerial vehicle monitoring center, and a cooperative unmanned aerial vehicle, a radar detection device and a frequency spectrum detection device which are respectively in communication connection with the unmanned aerial vehicle monitoring center;

the cooperative unmanned aerial vehicle is used for sending active report information to an unmanned aerial vehicle monitoring center in real time;

the radar detection equipment is used for acquiring the position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the frequency spectrum detection device is used for acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the unmanned aerial vehicle monitoring center is used for correlating the information acquired by the radar detection equipment and the radar detection equipment through positions to form comprehensive detection target information, comparing the frequency spectrum characteristics and the position information in the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, and identifying the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle.

7. The multi-source information-based cooperative and uncooperative drone identification system of claim 6, wherein the active reporting information of cooperative drones includes: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth.

8. The multi-source information-based cooperative and non-cooperative unmanned aerial vehicle identification system of claim 6, wherein the unmanned aerial vehicle monitoring center specifically comprises:

a correlation module: calculating a difference value between an azimuth angle in the radar detection information and an azimuth angle in the frequency spectrum detection information, if the difference value is smaller than a preset frequency spectrum azimuth threshold value, associating the radar detection information and the frequency spectrum detection information to form comprehensive detection target information;

an identification module: and respectively calculating the difference values of the center frequency, the bandwidth, the distance, the azimuth angle and the pitch angle in the comprehensive detection target information and the active reported information, if all the difference values are smaller than respective preset threshold values, determining the unmanned aerial vehicle as a cooperative unmanned aerial vehicle, and otherwise, determining the unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

Technical Field

The invention relates to the field of anti-unmanned aerial vehicles, in particular to a method and a system for identifying a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle.

Background

In recent years, the application of various civil consumption-level unmanned aerial vehicles is increased explosively, and convenience is brought to production and life. Meanwhile, the aircrafts have the characteristics of low flying height, low speed, small radar reflection area (so-called 'low-speed small' aircraft target), difficulty in finding on the ground and the like, so that related departments are difficult to control the unmanned aerial vehicle; meanwhile, the police industry and some special industries are increasingly widely applied to unmanned aerial vehicles, so that cooperative unmanned aerial vehicles (targets of all people) and non-cooperative unmanned aerial vehicles ('black flies' or enemies) appear in a surveillance airspace at the same time, how to control the cooperative unmanned aerial vehicles and the non-cooperative unmanned aerial vehicles becomes a problem to be solved urgently, and identification of the cooperative unmanned aerial vehicles and the non-cooperative unmanned aerial vehicles is the basis for realizing control.

Generally speaking, a system for managing and controlling a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle is called an unmanned aerial vehicle management and control system, and the unmanned aerial vehicle management and control system generally comprises a radar, a spectrum detection device, a command control center and unmanned aerial vehicle counter-braking equipment. The radar mainly detects the position of an air target; the frequency spectrum detection equipment mainly detects the radio characteristic information of an air target; the command control center completes comprehensive processing of data and sends disposal instructions to the threatening non-cooperative unmanned aerial vehicles, and the disposal equipment disposes the unmanned aerial vehicles according to the position, frequency and other information of the unmanned aerial vehicles sent by the command control center. The identification of cooperative unmanned aerial vehicles and non-cooperative unmanned aerial vehicles is the basis for commanding unmanned aerial vehicles of our parties and controlling unmanned aerial vehicles flying black, and the knowledge of the positions and frequency characteristics of unmanned aerial vehicles of our parties is also the basis for reducing accidental injuries.

However, in the prior art, hardware and sensor design is mostly improved for identification of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle and unmanned aerial vehicle management and control, the system architecture is complex, and practical application is difficult.

Disclosure of Invention

The invention provides a cooperative and non-cooperative unmanned aerial vehicle identification method and system based on multi-source information, which are used for identifying a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle.

The invention provides a cooperative and non-cooperative unmanned aerial vehicle identification method based on multi-source information, which comprises the following steps:

s1, when the cooperative unmanned aerial vehicle flies, active report information is sent to the unmanned aerial vehicle monitoring center in real time;

s2, the unmanned aerial vehicle monitoring center receives and stores active reported information of each cooperative unmanned aerial vehicle in real time;

s3, acquiring the position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through radar detection equipment;

s4, acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through frequency spectrum detection equipment;

s5, correlating the information acquired by the radar detection device with the information acquired by the frequency spectrum detection device according to the position information, forming comprehensive detection target information, and if the correlation is successful, turning to the step S6;

and S6, comparing the frequency spectrum characteristics and the position information in the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, if the comparison conditions are met, determining the cooperative unmanned aerial vehicle, otherwise, determining the cooperative unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

Preferably, step S1 is preceded by: setting various error thresholds including a radar distance detection threshold, an azimuth detection threshold, a radar pitch detection threshold, a frequency spectrum azimuth threshold, a center frequency error threshold and a bandwidth error threshold.

Preferably, in step S1, the actively reporting information includes: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth.

Preferably, in step S5, the associating the information acquired by the radar detection device with the information acquired by the spectrum detection device according to the location information specifically includes: and if the difference value of the azimuth angle in the radar detection information and the azimuth angle in the frequency spectrum detection information is smaller than the frequency spectrum azimuth threshold value, the correlation is carried out.

Preferably, in step S6, the alignment condition includes: in the comprehensive detection target information and the active reporting information, the central frequency difference value of the comprehensive detection target information and the active reporting information is smaller than the central frequency error threshold value, the bandwidth difference value is smaller than the bandwidth error threshold value, the distance difference value is smaller than the radar distance detection threshold value, the azimuth angle difference value is smaller than the azimuth detection threshold value, and the pitch angle difference value is smaller than the radar pitch detection threshold value; and when all comparison conditions are met, determining that the unmanned aerial vehicle is a cooperative unmanned aerial vehicle, otherwise, determining that the unmanned aerial vehicle is a non-cooperative unmanned aerial vehicle.

In a second aspect of the invention, a cooperative and non-cooperative unmanned aerial vehicle identification system based on multi-source information is provided, and the system comprises an unmanned aerial vehicle monitoring center, and a cooperative unmanned aerial vehicle, a radar detection device and a frequency spectrum detection device which are respectively in communication connection with the unmanned aerial vehicle monitoring center;

the cooperative unmanned aerial vehicle is used for sending active report information to an unmanned aerial vehicle monitoring center in real time;

the radar detection equipment is used for acquiring the position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the frequency spectrum detection device is used for acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the unmanned aerial vehicle monitoring center is used for correlating the information acquired by the radar detection equipment and the radar detection equipment through positions to form comprehensive detection target information, comparing the frequency spectrum characteristics and the position information in the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, and identifying the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle.

Preferably, the active reporting information of the cooperative drone includes: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth.

Preferably, the unmanned aerial vehicle monitoring center specifically includes:

a correlation module: calculating a difference value between an azimuth angle in the radar detection information and an azimuth angle in the spectrum detection information, and if the difference value is smaller than a preset spectrum azimuth threshold value, associating the difference value to form comprehensive detection target information;

an identification module: and respectively calculating the difference values of the center frequency, the bandwidth, the distance, the azimuth angle and the pitch angle in the comprehensive detection target information and the active reported information, if all the difference values are smaller than respective preset threshold values, determining the unmanned aerial vehicle as a cooperative unmanned aerial vehicle, and otherwise, determining the unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

The invention has the beneficial effects that:

the method is simple, efficient, high in accuracy and low in false alarm rate, lays a good foundation for unmanned aerial vehicle management and control, simultaneously tracks the position and frequency characteristics of the unmanned aerial vehicle of the same party in real time, and reduces 'accidental injury'.

Drawings

In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the technical description of the present invention will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.

Fig. 1 is a schematic view of an identification process of a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle provided by the invention;

fig. 2 is a topological diagram of a recognition system for cooperative drones and non-cooperative drones provided by the invention.

Detailed Description

The invention provides a method and a system for identifying a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle based on multi-source information, wherein the multi-source information comprises information actively reported by the unmanned aerial vehicle, radar detection information and frequency spectrum detection information.

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, a flow diagram of a method for identifying a cooperative drone and a non-cooperative drone based on multi-source information is shown, the method including:

initializing relevant parameters, and presetting various error thresholds including a radar distance detection threshold, an azimuth detection threshold, a radar pitch detection threshold, a frequency spectrum azimuth threshold, a center frequency error threshold and a bandwidth error threshold. The radar distance detection threshold value Ard is 40m, the azimuth detection threshold value Aro is 1 degree, the radar pitch detection threshold value Are 1 degree, the spectrum azimuth threshold value Apo is 5 degrees, the center frequency error is generally set to the bandwidth, and the bandwidth-dependent error threshold value Afr is 2 Mhz.

S1, when the cooperative unmanned aerial vehicle flies, active report information is sent to the unmanned aerial vehicle monitoring center in real time;

the actively reporting information comprises: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the identity information of the cooperative unmanned aerial vehicle comprises an unmanned aerial vehicle registration number, a model and the like, and the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth. On concrete the realization, the box that installs additional on accessible flyer APP or the cooperation unmanned aerial vehicle sends information to unmanned aerial vehicle monitoring center, and this box of installing additional has functions such as real-time tracking unmanned aerial vehicle position, frequency spectrum information and with unmanned aerial vehicle monitoring center wireless communication. Table 1 shows an example of active information reporting of a part of cooperative drones:

table 1 cooperative unmanned aerial vehicle actively reports information

S2, the unmanned aerial vehicle monitoring center receives and stores the information actively reported by each cooperative unmanned aerial vehicle in real time;

s3, acquiring the position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through radar detection equipment; examples of radar detection information acquired by the radar detection device are shown in table 2:

TABLE 2 Radar Probe information

Track number	Distance (rice)	Azimuth (degree)	Pitch angle (degree)
				1001	510	30.5	5.2
1002	620	61	10.7
				1003	930	91	15.2

S4, acquiring the position, type and frequency spectrum characteristic information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time through frequency spectrum detection equipment; examples of the spectrum sensing information acquired by the spectrum sensing device are shown in table 3:

TABLE 3 Spectrum Probe information

S5, correlating the information acquired by the radar detection device with the information acquired by the frequency spectrum detection device according to the position information, forming comprehensive detection target information, and if the correlation is successful, turning to the step S6;

further, the associating the information acquired by the radar detection device with the information acquired by the spectrum detection device according to the location information specifically includes: and if the difference value of the azimuth angle in the radar detection information and the azimuth angle in the frequency spectrum detection information is smaller than the frequency spectrum azimuth threshold value, the correlation is carried out. If the difference between the azimuth angles of the unmanned aerial vehicle with the track number of 1001 in table 2 and the unmanned aerial vehicle in 2001 in table 3 is less than 5 degrees, the two can be associated, the information is integrated to form table 4, and table 4 is the integrated detection target information obtained by associating table 2 and table 3:

TABLE 4 Integrated detection target information

And S6, comparing the frequency spectrum characteristics and the position information in the comprehensive detection target information with the active reported information of the cooperative unmanned aerial vehicle, if the comparison conditions are met, determining the cooperative unmanned aerial vehicle, otherwise, determining the cooperative unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

The alignment conditions comprise: in the detection target information and the active report information, the central frequency difference value of the detection target information and the active report information is smaller than the central frequency error threshold value, the bandwidth difference value is smaller than the bandwidth error threshold value, the distance difference value is smaller than the radar distance detection threshold value, the azimuth angle difference value is smaller than the azimuth detection threshold value, and the pitch angle difference value is smaller than the radar pitch detection threshold value; and when all comparison conditions are met, determining that the unmanned aerial vehicle is a cooperative unmanned aerial vehicle, otherwise, determining that the unmanned aerial vehicle is a non-cooperative unmanned aerial vehicle. If the comparison is successful, setting the unmanned aerial vehicle as a cooperative target, and sending the attribute information of the unmanned aerial vehicle to the outside by the unmanned aerial vehicle monitoring center; if the comparison fails, the unmanned aerial vehicle is set as a flight cooperation target, and the unmanned aerial vehicle monitoring center sends the attribute information of the unmanned aerial vehicle outwards.

Table 5 shows the comparison result between the comprehensive detection target information in table 4 and the active report information in table 1 in this embodiment:

TABLE 5 comparison of the comprehensive detection target information and the active report information

In table 5, each difference is smaller than the preset error threshold, and all comparison conditions are met, it is determined that the track identifier is 001 and the target of the radar detection drone (track number is 1001) and the spectrum detection target (track number is 2001) associated therewith is the cooperative drone.

Referring to fig. 2, the present invention further provides a cooperative and non-cooperative unmanned aerial vehicle identification system based on multi-source information, the system includes an unmanned aerial vehicle monitoring center 200, and a cooperative unmanned aerial vehicle 210, a radar detection device 220, and a spectrum detection device 230, which are respectively in communication connection with the unmanned aerial vehicle monitoring center;

the cooperative unmanned aerial vehicle 210 is configured to send active report information to an unmanned aerial vehicle monitoring center in real time;

the radar detection device 220 is configured to obtain position information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the spectrum detection device 230 is configured to obtain the position, type, and spectrum feature information of the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle in real time;

the unmanned aerial vehicle monitoring center 200 is configured to associate information acquired by the radar detection device 220 and the radar detection device 230 with each other through a position to form comprehensive detection target information, compare frequency spectrum characteristics and position information in the comprehensive detection target information with active reported information of the cooperative unmanned aerial vehicle 210, and identify a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle.

Further, the actively reporting information of the cooperative drone includes: identity information, position information and frequency characteristic information of the cooperative unmanned aerial vehicle; the position information comprises a distance, an azimuth angle and a pitch angle; the frequency characteristic information includes a center frequency and a bandwidth.

Further, the unmanned aerial vehicle monitoring center 200 specifically includes:

a correlation module: calculating a difference value between an azimuth angle in the radar detection information and an azimuth angle in the spectrum detection information, and if the difference value is smaller than a preset spectrum azimuth threshold value, associating the difference value to form comprehensive detection target information;

an identification module: and respectively calculating the difference values of the center frequency, the bandwidth, the distance, the azimuth angle and the pitch angle in the comprehensive detection target information and the active reported information, if all the difference values are smaller than respective preset threshold values, determining the unmanned aerial vehicle as a cooperative unmanned aerial vehicle, and otherwise, determining the unmanned aerial vehicle as a non-cooperative unmanned aerial vehicle.

The invention provides a method for identifying a cooperative unmanned aerial vehicle and a non-cooperative unmanned aerial vehicle based on multi-source information, which integrates information actively reported by the unmanned aerial vehicle, radar detection information and frequency spectrum detection information and can quickly and accurately identify the cooperative unmanned aerial vehicle and the non-cooperative unmanned aerial vehicle.

It can be clearly understood by those skilled in the art that for convenience and brevity of description, in the foregoing embodiments, descriptions of various embodiments have respective emphasis, and details or description which are not described in detail in a certain embodiment may be referred to in the related descriptions of other embodiments, and are not repeated herein.

Although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.