阅读说明：本技术 一种民用无人机系统被动式探测方法 (Passive detection method for civil unmanned aerial vehicle system ) 是由 刘林 袁金兰 于 2021-01-07 设计创作，主要内容包括：本发明公开了一种民用无人机系统被动式探测方法,包括射频接收机、无线电追踪技术、信号处理技术、4线接收器、时频分析技术、显示器、摄像头和CPU,在需要探测的区域内安装4线接收器,并将四线接收器分别连接射频接收机；本发明一种民用无人机系统被动式探测方法采用4线接收器进行增加无线电接收的范围,并通过射频接收器进行接收无线电,保证无线电的截取,通过信号处理技术进行信号处理,保证信号的识别,通过时频分析技术进行生成三维时频图像,并通过机器学习算法进行识别捕捉,方便对无人机进行探测追踪,通过CPU进行生成无人机组列,方便无人机的分类,通过无线电追踪技术进行定位控制人员位置,方便人员位置的定位。(The invention discloses a passive detection method of a civil unmanned aerial vehicle system, which comprises a radio frequency receiver, a radio tracking technology, a signal processing technology, a 4-line receiver, a time-frequency analysis technology, a display, a camera and a CPU, wherein the 4-line receiver is arranged in an area needing to be detected, and the four-line receiver is respectively connected with the radio frequency receiver; the passive detection method of the civil unmanned aerial vehicle system adopts the 4-line receiver to increase the radio receiving range, receives radio through the radio frequency receiver, ensures interception of the radio, processes signals through a signal processing technology, ensures identification of the signals, generates three-dimensional time-frequency images through a time-frequency analysis technology, identifies and captures through a machine learning algorithm, is convenient for detecting and tracking the unmanned aerial vehicle, generates unmanned aerial vehicle arrays through a CPU (central processing unit), is convenient for classifying the unmanned aerial vehicles, positions of control personnel through the radio tracking technology, and is convenient for positioning the personnel positions.)

1. A passive detection method for a civil unmanned aerial vehicle system is characterized by comprising the following steps: the system comprises a radio frequency receiver, a radio tracking technology, a signal processing technology, a 4-line receiver, a time frequency analysis technology, a display, a camera and a CPU.

2. The passive detection method of the civil unmanned aerial vehicle system according to claim 1, characterized in that: the passive detection method comprises the following steps:

(1) installing 4-wire receivers in an area needing to be detected, and respectively connecting the four-wire receivers with a radio frequency receiver;

(2) when a radio signal appears, the 4-wire receiver receives the radio signal, and the radio frequency receiver receives data and preprocesses the radio frequency signal;

(3) the preprocessed signals are subjected to signal processing through a signal processing technology to obtain processed signals;

(4) the time-frequency analysis technology generates a three-dimensional time-frequency image from the processed signal, displays data through a display, and the CPU counts the data change of the three-dimensional time-frequency image;

(5) the method comprises the following steps that a CPU extracts different feature points of a three-dimensional time-frequency image, constructs feature vectors, automatically identifies and captures the extracted feature vectors by adopting a machine learning algorithm, captures and calibrates the position of an unmanned aerial vehicle according to three-dimensional time-frequency image information and a radio signal, and a camera shoots according to the capture position;

(6) according to the difference of three-dimensional time-frequency image data generated by different unmanned aerial vehicles, a CPU automatically generates a plurality of unmanned aerial vehicle lists in different ranges, and prompts are given to different unmanned aerial vehicle lists through a display;

(7) according to data received by radio, the transmitting terminal is tracked remotely by radio tracking technology, the CPU receives a real-time position map through a network, marks the real-time position map according to tracking position information, and finally displays the position of the transmitting terminal through a display.

3. The passive detection method of the civil unmanned aerial vehicle system according to claim 2, characterized in that: the three-dimensional time-frequency image display color displayed by the display and the display color displayed by the unmanned aerial vehicle array are independently displayed and can not simultaneously display the same color, and the display color of the display can be independently adjusted.

4. The passive detection method of the civil unmanned aerial vehicle system according to claim 1, characterized in that: the unmanned aerial vehicle array can be manually adjusted.

5. The passive detection method of the civil unmanned aerial vehicle system according to claim 1, characterized in that: the 4-wire receiver can be selectively assembled according to actual conditions.

Technical Field

The invention relates to the technical field of civil unmanned aerial vehicles, in particular to a passive detection method of a civil unmanned aerial vehicle system.

Background

Unmanned planes, abbreviated as "drones" in english and "UAVs" in short, are unmanned planes operated by radio remote control devices and self-contained program control devices, or operated autonomously, either completely or intermittently, by an on-board computer, and are often more suitable for tasks that are too "fool, dirty, or dangerous" than unmanned planes, which can be classified into military and civilian applications, depending on the field of application. For military use, unmanned aerial vehicles are divided into reconnaissance aircraft and target drone, and for civil use, unmanned aerial vehicles + industrial application are really just needed for unmanned aerial vehicles; at present, the unmanned aerial vehicle is applied to the fields of aerial photography, agriculture, plant protection, miniature self-timer, express transportation, disaster relief, wild animal observation, infectious disease monitoring, surveying and mapping, news reporting, power inspection, disaster relief, film and television shooting, romantic manufacturing and the like, the application of the unmanned aerial vehicle is greatly expanded, and developed countries actively expand industrial application and develop unmanned aerial vehicle technology.

However, the existing civil unmanned aerial vehicle often appears in some places where the unmanned aerial vehicle cannot be found, such as airports and other areas, and the problem that the aircraft cannot normally land or other problems is caused.

Disclosure of Invention

The invention aims to overcome the defects of the prior art, provides a passive detection method of a civil unmanned aerial vehicle system, has the advantages of multiple detection and tracking, unmanned aerial vehicle grouping and classification and personnel position positioning, and solves the problems in the prior art.

In order to achieve the purpose, the invention provides the following technical scheme: a passive detection method of a civil unmanned aerial vehicle system comprises a radio frequency receiver, a radio tracking technology, a signal processing technology, a 4-line receiver, a time-frequency analysis technology, a display, a camera and a CPU.

The passive detection method comprises the following steps:

(1) installing 4-wire receivers in an area needing to be detected, and respectively connecting the four-wire receivers with a radio frequency receiver;

(2) when a radio signal appears, the 4-wire receiver receives the radio signal, and the radio frequency receiver receives data and preprocesses the radio frequency signal;

(3) the preprocessed signals are subjected to signal processing through a signal processing technology to obtain processed signals;

(4) the time-frequency analysis technology generates a three-dimensional time-frequency image from the processed signal, displays data through a display, and the CPU counts the data change of the three-dimensional time-frequency image;

(5) the method comprises the following steps that a CPU extracts different feature points of a three-dimensional time-frequency image, constructs feature vectors, automatically identifies and captures the extracted feature vectors by adopting a machine learning algorithm, captures and calibrates the position of an unmanned aerial vehicle according to three-dimensional time-frequency image information and a radio signal, and a camera shoots according to the capture position;

(6) according to the difference of three-dimensional time-frequency image data generated by different unmanned aerial vehicles, a CPU automatically generates a plurality of unmanned aerial vehicle lists in different ranges, and prompts are given to different unmanned aerial vehicle lists through a display;

(7) according to data received by radio, the transmitting terminal is tracked remotely by radio tracking technology, the CPU receives a real-time position map through a network, marks the real-time position map according to tracking position information, and finally displays the position of the transmitting terminal through a display.

Preferably, the three-dimensional time-frequency image display color displayed by the display and the display color of the unmanned aerial vehicle array are independently displayed and cannot simultaneously generate the same color, and the display color of the display can be independently adjusted.

Preferably, the drone trains are manually adjustable.

Preferably, the 4-wire receiver can be selectively assembled according to actual conditions.

The parts not involved in the invention are the same as or can be realized by the prior art.

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

the utility model provides a civilian unmanned aerial vehicle system passive type detection method adopts 4 line receivers to increase the scope that the radio received, and receive the radio through the radio frequency receiver, guarantee the intercepting of radio, carry out signal processing through signal processing technique, guarantee the discernment of signal, generate three-dimensional time frequency image through time frequency analysis technique, and discern the seizure through machine learning algorithm, conveniently survey and track unmanned aerial vehicle, generate unmanned aerial vehicle group through CPU, make things convenient for unmanned aerial vehicle's classification, carry out positioning control personnel position through the radio tracking technique, make things convenient for the location of personnel position.

Detailed Description

The present invention will be further described with reference to specific embodiments, which will become apparent from the following description, but are intended to be exemplary only, and not limiting as to the scope of the invention, it will be understood by those skilled in the art that changes in detail and modifications of form and detail may be made therein without departing from the spirit and scope of the invention, and that such changes and modifications are within the scope of the invention.

Example 1

A passive detection method of a civil unmanned aerial vehicle system comprises a radio frequency receiver, a radio tracking technology, a signal processing technology, a 4-line receiver, a time-frequency analysis technology, a display, a camera and a CPU;

the passive detection method comprises the following steps:

(1) installing 4-wire receivers in an area needing to be detected, and respectively connecting the four-wire receivers with a radio frequency receiver;

(2) when a radio signal appears, the 4-wire receiver receives the radio signal, and the radio frequency receiver receives data and preprocesses the radio frequency signal;

(3) the preprocessed signals are subjected to signal processing through a signal processing technology to obtain processed signals;

(4) the time-frequency analysis technology generates a three-dimensional time-frequency image from the processed signal, displays data through a display, and the CPU counts the data change of the three-dimensional time-frequency image;

(5) the method comprises the following steps that a CPU extracts different feature points of a three-dimensional time-frequency image, constructs feature vectors, automatically identifies and captures the extracted feature vectors by adopting a machine learning algorithm, captures and calibrates the position of an unmanned aerial vehicle according to three-dimensional time-frequency image information and a radio signal, and a camera shoots according to the capture position;

(6) according to the fact that three-dimensional time-frequency image data generated by different unmanned aerial vehicles are different, a CPU automatically generates a plurality of unmanned aerial vehicle arrays in different ranges, the unmanned aerial vehicle arrays can be manually adjusted, prompts are given to different unmanned aerial vehicle arrays through a display, the display color of the three-dimensional time-frequency image displayed by the display and the display color of the unmanned aerial vehicle arrays are independently displayed, the same color cannot be generated at the same time, and the display color of the display can be automatically adjusted;

(7) according to data received by radio, the transmitting terminal is tracked remotely by radio tracking technology, the CPU receives a real-time position map through a network, marks the real-time position map according to tracking position information, and finally displays the position of the transmitting terminal through a display.

According to above step, adopt 4 line receivers to increase the scope that the radio received, and receive the radio through radio frequency receiver, guarantee the intercepting of radio, carry out signal processing through signal processing technique, guarantee the discernment of signal, generate three-dimensional time frequency image through time frequency analysis technique, and discern the seizure through machine learning algorithm, conveniently survey the pursuit to unmanned aerial vehicle, generate unmanned aerial vehicle group through CPU and list, make things convenient for unmanned aerial vehicle's classification, carry out positioning control personnel position through radio tracking technique, make things convenient for the location of personnel position.

Example 2

A passive detection method of a civil unmanned aerial vehicle system comprises a radio frequency receiver, a radio tracking technology, a signal processing technology, a 4-line receiver, a time-frequency analysis technology, a display, a camera and a CPU;

the passive detection method comprises the following steps:

(1) when a radio signal appears, the radio frequency receiver receives the radio signal and preprocesses the radio signal;

(2) the preprocessed signals are subjected to signal processing through a signal processing technology to obtain processed signals;

(3) the time-frequency analysis technology generates a three-dimensional time-frequency image from the processed signal, displays data through a display, and the CPU counts the data change of the three-dimensional time-frequency image;

(4) the method comprises the following steps that a CPU extracts different feature points of a three-dimensional time-frequency image, constructs feature vectors, automatically identifies and captures the extracted feature vectors by adopting a machine learning algorithm, captures and calibrates the position of an unmanned aerial vehicle according to three-dimensional time-frequency image information and a radio signal, and a camera shoots according to the capture position;

(5) according to the fact that three-dimensional time-frequency image data generated by different unmanned aerial vehicles are different, a CPU automatically generates a plurality of unmanned aerial vehicle arrays in different ranges, the unmanned aerial vehicle arrays can be manually adjusted, prompts are given to different unmanned aerial vehicle arrays through a display, the display color of the three-dimensional time-frequency image displayed by the display and the display color of the unmanned aerial vehicle arrays are independently displayed, the same color cannot be generated at the same time, and the display color of the display can be automatically adjusted;

(6) according to data received by radio, the transmitting terminal is tracked remotely by radio tracking technology, the CPU receives a real-time position map through a network, marks the real-time position map according to tracking position information, and finally displays the position of the transmitting terminal through a display.

According to above step, receive the radio through radio frequency receiver, guarantee the intercepting of radio, carry out signal processing through signal processing technology, guarantee the discernment of signal, generate three-dimensional time-frequency image through time-frequency analysis technique, and discern the seizure through machine learning algorithm, conveniently survey the pursuit to unmanned aerial vehicle, generate unmanned aerial vehicle group through CPU and list, make things convenient for unmanned aerial vehicle's classification, carry out positioning control personnel position through radio tracking technique, make things convenient for the location of personnel's position.

To sum up: the invention relates to a passive detection method of a civil unmanned aerial vehicle system, which is characterized in that a 4-wire receiver is arranged in an area to be detected, the four-wire receiver is respectively connected with a radio frequency receiver, when radio signals appear, the 4-wire receiver receives the radio signals, the radio frequency receiver receives data and preprocesses the radio frequency signals, the preprocessed signals are processed by a signal processing technology to obtain processed signals, a time frequency analysis technology generates three-dimensional time frequency images from the processed signals, the data are displayed by a display, a CPU counts the data change of the three-dimensional time frequency images, extracts different characteristic points of the three-dimensional time frequency images, constructs characteristic vectors, automatically identifies and captures the extracted characteristic vectors by adopting a machine learning algorithm, and captures and calibrates the position of an unmanned aerial vehicle according to the three-dimensional time frequency image information and the radio signals, the camera shoots according to a capture position, the CPU automatically generates a plurality of unmanned aerial vehicle arrays in different ranges according to different three-dimensional time-frequency image data generated by different unmanned aerial vehicles, prompts are given to the different unmanned aerial vehicle arrays through the display, a transmitting end is remotely tracked through a radio tracking technology according to data received by radio, the CPU receives a real-time position map through a network, marks the real-time position map according to tracking position information, and finally displays the position of the transmitting end through the display; the steps ensure that the method has the advantages of multiple detection and tracking, unmanned aerial vehicle grouping and classification and personnel position positioning.

While there have been shown and described what are at present considered to be the fundamental principles of the invention and its essential features and advantages, it will be understood by those skilled in the art that the invention is not limited by the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.