KR102335765B1 - Method and apparatus for detecting unmanned aerial vehicle based on radio measurement - Google Patents

Abstract

The present invention is designed to detect an unmanned aerial vehicle based on radio wave measurement. An operation method of a device which detects the unmanned aerial vehicle includes the steps of: generating an image representing a real-time spectrogram; determining at least one region based on a pattern of values of pixels included in the image; and detecting a direction of the unmanned aerial vehicle based on received signals corresponding to the at least one area. Therefore, the unmanned aerial vehicle (UAV) can be detected more effectively.

Description

METHOD AND APPARATUS FOR DETECTING UNMANNED AERIAL VEHICLE BASED ON RADIO MEASUREMENT

The present invention relates to detecting an unmanned aerial vehicle (UAV), and more particularly to a method and apparatus for detecting an unmanned aerial vehicle based on radio wave measurement.

An unmanned aerial vehicle refers to an air vehicle operated based on remote control without a pilot on board the aircraft. Unmanned aerial vehicles (UAVs) are often called drones, and are also a future growth engine that is attracting attention in recent years. The use and use of unmanned aerial vehicles is rapidly increasing worldwide. As a social issue accompanying this, problems such as crime, terrorism, and invasion of privacy using unmanned aerial vehicles are also occurring.

Anti-drone technology is being researched to solve various problems caused by unmanned aerial vehicles, and the market in the anti-drone field is gradually expanding along with the drone industry. In particular, securing an anti-drone solution for protecting major national facilities such as airports, ports, and power plants is emerging as very important nationally. Anti-drone technology is largely divided into detection technology and neutralization technology. Here, the detection technology may be implemented based on technologies such as radar, radio signal detection, electro-optical/infra-red (EO/IR), and acoustic detection.

The present invention is to provide a method and apparatus for effectively detecting an unmanned aerial vehicle (UAV).

An object of the present invention is to provide a method and apparatus for detecting an unmanned aerial vehicle using a signal generated from the unmanned aerial vehicle.

An object of the present invention is to provide a method and apparatus for detecting the presence and direction of an unmanned aerial vehicle based on a real-time spectrogram for a given band.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. will be able

According to an embodiment of the present invention, a method of operating an apparatus for detecting an unmanned aerial vehicle includes generating an image representing a real-time spectrogram, and determining at least one region based on a pattern of values of pixels included in the image. and finding a direction of the unmanned aerial vehicle based on the received signals corresponding to the at least one area.

According to an embodiment of the present invention, an apparatus for detecting an unmanned aerial vehicle includes a signal receiver for receiving signals, a real-time signal processor for generating a real-time spectrum for the received signals, and a processor connected to the real-time signal processor can do. The processor generates an image based on the real-time spectrogram, determines at least one region based on a pattern of values of pixels included in the image, and determines at least one region based on received signals corresponding to the at least one region. The direction of the unmanned aerial vehicle may be detected.

According to the present invention, an unmanned aerial vehicle (UAV) can be detected more effectively.

The effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art to which the present invention belongs from the following description. will be.

1 illustrates a concept for detection of an unmanned aerial vehicle (UAV) according to an embodiment of the present invention.
2 illustrates a configuration of an apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention.
3 illustrates an example of a procedure for detecting an unmanned aerial vehicle according to an embodiment of the present invention.
4A illustrates an example of signal area selection for detecting an unmanned aerial vehicle according to an embodiment of the present invention.
4B illustrates an example of a spectrum for a signal used to detect an unmanned aerial vehicle according to an embodiment of the present invention.
4C illustrates an example of bin power for a signal used to detect an unmanned aerial vehicle according to an embodiment of the present invention.
5 illustrates an example of a procedure for generating a spectrogram image according to an embodiment of the present invention.
6 illustrates an example of a procedure for determining a signal region based on a spectrogram image according to an embodiment of the present invention.
7A and 7B illustrate examples of signal regions selected in a spectrogram image according to an embodiment of the present invention.
8 illustrates an example of a procedure for detecting a direction of an unmanned aerial vehicle according to an embodiment of the present invention.
9A and 9B illustrate a principle of determining an incident angle using an array antenna according to an embodiment of the present invention.

The following is merely illustrative of the principles of the invention. Therefore, those skilled in the art can devise various devices that, although not explicitly described or shown herein, embody the principles of the invention and are included in the spirit and scope of the invention. In addition, it should be understood that all conditional terms and examples listed herein are, in principle, expressly intended only for the purpose of understanding the inventive concept and are not limited to the specifically enumerated embodiments and states as such. .

The above-described objects, features and advantages will become more apparent through the following detailed description in relation to the accompanying drawings, and accordingly, those of ordinary skill in the art to which the invention pertains will be able to easily practice the technical idea of the invention. .

In the specification and claims, terms such as "first," "second," "third," and "fourth," are used, if any, to distinguish between like elements and, if not necessarily, in a specific sequence. or to describe the order of occurrence. It will be understood that the terms so used are interchangeable under appropriate circumstances to enable the embodiments of the invention described herein to operate, for example, in sequences other than those shown or described herein. Likewise, where methods are described herein as comprising a series of steps, the order of those steps presented herein is not necessarily the order in which those steps may be performed, and any described steps may be omitted and/or Any other steps not described may be added to the method.

Also, terms such as "left", "right", "front", "behind", "top", "bottom", "above", "below" in the specification and claims are used for descriptive purposes, It is not necessarily intended to describe an invariant relative position. It will be understood that the terms so used are interchangeable under appropriate circumstances to enable the embodiments of the invention described herein to operate otherwise than, for example, as shown or described herein. As used herein, the term “connected” is defined as being directly or indirectly connected in an electrical or non-electrical manner. Objects described herein as being "adjacent" to one another may be in physical contact with one another, in proximity to one another, or in the same general scope or area as appropriate for the context in which the phrase is used. The presence of the phrase “in one embodiment” herein refers to the same, but not necessarily, embodiment.

In addition, in the specification and claims, references to 'connected', 'connecting', 'fastened', 'fastening', 'coupled', 'coupled', etc., and various variations of these expressions, refer to other elements directly It is used in the sense of being connected or indirectly connected through other components.

In addition, the suffixes "module" and "part" for components used in this specification are given or used in consideration of ease of writing the specification, and do not have a meaning or role distinct from each other by themselves.

In addition, the terms used herein are for the purpose of describing the embodiments and are not intended to limit the present invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, 'comprise' and/or 'comprising' means that a referenced component, step, operation and/or element is the presence of one or more other components, steps, operations and/or elements. or addition is not excluded.

In addition, in the description of the invention, if it is determined that a detailed description of a known technology related to the invention may unnecessarily obscure the gist of the invention, the detailed description thereof will be omitted. Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Hereinafter, the present invention proposes a technique for detecting an unmanned aerial vehicle (UAV) based on radio wave measurement. In particular, the present invention relates to a technology for detecting the appearance and direction of an unmanned aerial vehicle using a signal transmitted and received between an unmanned aerial vehicle and a controller of the unmanned aerial vehicle. Specifically, the present invention relates to a technique for detecting a drone signal band based on image processing, a technique for extracting a direction finding area from a detected band, a technique for detecting a direction for a signal with a short signal period, and the like. In the following description, the unmanned aerial vehicle may be referred to as a 'drone'.

Drones mainly use the 400 MHz band, 900 MHz band, 2.4 GHz band, and 5.8 GHz band, which are ISM (industry-science-medical) bands. In the case of an industrial drone, control/communication of the drone is sometimes performed using mobile communication. Various services such as wireless fidelity (Wi-Fi), Bluetooth, remote control, amateur radio, long term evolution (LTE), and 5th generation (5G) are used together in the frequency at which the drone operates. In addition, in order for multiple users to share a frequency, technologies such as carrier sense multiple access (CSMA), frequency hopping, orthogonal frequency division multiple access (OFDMA) may be applied. Due to this, the signal duration may be shortened.

As a radio wave detection technology, one of the anti-drone technologies, the radio wave measurement-based technology detects the drone by detecting the drone control/response signal and video signal, which are signals between the drone and the operator, and the direction of the drone and the operator. and a method of estimating the location. A drone detection technology based on radio wave measurement is shown in FIG. 1 below.

1 illustrates a concept for detection of an unmanned aerial vehicle (UAV) according to an embodiment of the present invention. Referring to FIG. 1 , the drone 122 may fly according to a control signal transmitted by the controller 124 . Also, the drone 122 may transmit a signal including an image captured by the camera to the controller 124 . In this case, according to various embodiments, the detection device 110 may detect the drone 122 using a signal (eg, a control signal, an image signal, etc.) transmitted and received between the drone 122 and the controller 124 . have. Here, the detection device 110 includes an antenna for receiving a signal, and the antenna may include one of a circular array antenna and a planar array antenna.

As shown in FIG. 1, the drone detection technology based on radio wave measurement consists of a component technology for detecting a signal and a component technology for estimating at least one of the presence, direction, and location of a drone based on the detected signal. The method of estimating the direction/position of a drone using radio signals including drone control and image information has the advantage of virtually no performance degradation among various drone detection technologies when it is difficult to secure visibility due to dark night, fog, or rain. .

When the drone is operated in an unlicensed band, various communication devices coexist, and thus various signals may be mixed. According to these band characteristics, the control/video signal for the drone may have a short duration and be transmitted while changing the frequency. In particular, since the design of the control/video signal of the drone is a factor that determines the performance of the drone, different protocols are applied for each manufacturer. Therefore, in order to detect a drone signal, it is necessary to acquire a wide broadband spectrum so as to detect a changed frequency, and to selectively use only a region determined to be a drone signal in the broadband spectrum. Through this, it is expected that the search and detection speed of drone signals will be improved.

Accordingly, the apparatus according to various embodiments selects a band of a signal using a real-time spectrogram and extracts a signal for direction detection from the selected band. Specifically, the proposed technique is a technique for performing direction detection using a signal of a short period, and the apparatus according to various embodiments may perform operations such as generating a real-time spectrogram, selecting a signal region, and detecting a direction.

2 illustrates a configuration of an apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention. FIG. 2 may be understood as a structure of the detection device 110 of FIG. 1 .

Referring to FIG. 2 , the device includes an antenna device 210 , a signal receiving unit 220 , a communication unit 230 , a real-time signal processing unit 240 , and a processor 250 .

The antenna device 210 includes at least one antenna. For example, the antenna device may be an array antenna including a plurality of antenna elements.

The signal receiver 220 processes the RF signal. The signal receiving unit 220 may process the received signal in a form that can be processed by the real-time signal processing unit. Here, the signal may be provided from a separate receiving device or may be received through an antenna or array antenna 210 physically connected to the signal receiving unit 220 . To this end, the signal receiver 220 includes an amplifier for amplifying a signal level, a filter for passing a signal of a band to be measured, an oscillator and mixer for frequency downconversion, and an analog signal converter (ADC) for converting an analog signal into a digital signal. to digital converter).

The communication unit 230 allows the device to transmit and receive signals with other devices. The communication unit 230 provides a wired or wireless interface, and performs a function for transmitting and receiving data according to a corresponding communication protocol. For example, the communication unit 230 may transmit or receive a signal for setting and controlling a device, a signal informing a result of detection of an unmanned aerial vehicle, and the like. The communication unit 230 may be referred to as a 'transmitter', 'receiver', or 'transceiver'.

The real-time signal processing unit 240 generates a real-time spectrogram by processing the digital signal transmitted from the signal receiving unit 220 in real time. In order to process signals in real time, the processing operations must be performed quickly to accurately process all signal elements within the frequency band of interest. Specifically, the real-time signal processing unit 240 samples the input signal quickly enough to satisfy the Nyquist criterion. The Nyquist criterion includes the condition that the sampling frequency exceeds twice the bandwidth of interest. In addition, the real-time signal processing unit 240 continuously and rapidly performs all calculations so that the output of the analysis can follow the change in the input signal. To this end, a fast Fourier transform (FFT) operation may be performed on the corresponding unit signal for a time shorter than the length (eg, acquisition time) of one unit signal (eg, frame) extracted from the time axis. To this end, the real-time signal processing unit 240 may include at least one of a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a graphics processing unit (GPU), a digital signal processor (DSP), and a high-performance processor. .

The processor 250 controls the overall functionality of the device. The processor 250 may analyze radio wave data provided from the signal receiver 220 and the real-time signal processor 240 . The processor 250 may transmit and/or receive data with another device through the communication unit 230 . In addition, it is possible to detect unmanned aerial vehicles based on real-time spectrograms. That is, the processor 250 may control the device to detect the unmanned aerial vehicle according to various embodiments to be described later.

An unmanned aerial vehicle may be detected according to various embodiments by the device configured as shown in FIG. 2 . 2 illustrates the structure of a single device, an unmanned aerial vehicle may be detected by collaboration of two or more devices according to another embodiment. For example, one of the two or more devices may perform a function of analyzing a radio signal, and the other may detect the existence and direction/position of the unmanned aerial vehicle based on the analysis result of the radio signal. In addition, a function of collecting radio signals may be performed by a separate device. Hereinafter, procedures according to various embodiments are described as being performed by one device, but may be understood to be performed by a plurality of devices.

3 illustrates an example of a procedure for detecting an unmanned aerial vehicle according to an embodiment of the present invention. 3 illustrates an operation method of a device (eg, the detection device 110 of FIG. 1 ).

Referring to FIG. 3 , in step S301 , the device generates a real-time spectrogram. The device acquires received signals having a predetermined bandwidth in a range including a band in which an unmanned aerial vehicle can be operated, and generates a real-time spectrogram of the received signals within a set frequency band. According to an embodiment, the spectrogram may be expressed in an image format. In this case, after generating the real-time spectrogram for subsequent signal analysis, the device may store information on the received signals in a storage space (eg, a buffer memory) without discarding the information.

In step S303, the device determines a signal region to be used for detection. Here, the signal region is specified by a signal band and a time interval. That is, one axis of the image representing the spectrogram represents frequency and the other axis represents time, and the signal region occupies a certain frequency section and time section. In this case, one or a plurality of signal regions may be determined. The device may determine the at least one signal region based on the pattern of pixel values represented in the image. According to an embodiment, the device may determine at least one signal region from the image representing the spectrogram by using the trained artificial intelligence model.

In step S305, the device performs detection of the unmanned aerial vehicle. Here, the detection includes at least one of determining the presence or absence, checking a location, and checking a direction. The device may perform detection using signals received in a time interval and a frequency interval specified by the determined at least one signal region. To this end, when generating the real-time spectrogram in step S301, the device stores information about the received signal (eg, digitized IQ data of the received signal, time domain received signal value, etc.) in a storage space (eg, buffer memory). can Accordingly, the device may read information on the received signals corresponding to the determined at least one signal region, analyze the received signals, and determine the direction of the unmanned aerial vehicle based on the analysis result. For example, the device may perform detection based on at least one of an arrangement of at least one signal region, a size of the at least one signal region, a signal reception strength, and a signal reception angle.

As described with reference to FIG. 3 , an unmanned aerial vehicle may be detected based on a real-time spectrogram. In general, a signal transmitted or received from an unmanned aerial vehicle has a short duration and a frequency change characteristic. In order to perform direction detection based on a signal related to an unmanned aerial vehicle having characteristics such as a short duration and a changing frequency, the present invention uses a real-time spectrogram. To detect a signal related to the unmanned aerial vehicle, the device may generate a spectrogram using the uninterrupted real-time spectrum. That is, in the drone detection and direction finding system according to various embodiments of the present disclosure, the synchronized multi-channel receiver may generate real-time spectrograms and simultaneously generate FFT data for direction detection of the multi-channel receiver. This is to synchronize data for selecting a direction finding band and direction finding data because signals are not continuously maintained in the same band.

As described with reference to FIG. 3 , at least one signal region may be selected based on an image representing a real-time spectrogram, and the unmanned aerial vehicle may be detected using signals within the selected at least one signal region. Through this, since only some signals other than the signals included in the entire band and all time sections of the received signal are used, unnecessary operation may be excluded.

An example of the at least one signal region selected based on the image is illustrated in FIG. 4A below. 4A illustrates an example of signal area selection for detecting an unmanned aerial vehicle according to an embodiment of the present invention. 4A illustrates a real-time spectrogram 410 of a signal collected in a WiFi band of 2.4 GHz, wherein the horizontal axis represents frequency and the vertical axis represents time. Referring to FIG. 4A , the spectrogram 410 represents a signal magnitude at each point specified by a combination of frequency and time as a color value or a shade value. Accordingly, a region in which a signal is expected to exist may be detected based on pixel values of the image representing the spectrogram 410 . In the case of FIG. 4A , nine signal regions 411 to 419 of different sizes were detected. In this case, according to an embodiment, in order to increase the detection accuracy of the signal regions, preprocessing may be performed on the image.

An example of a frequency spectrum and bin power at a point 402 at a frequency of 2411.46 MHz and a time of 5.1444 ms in the spectrogram shown in FIG. 4A is shown in FIGS. 4B and 4C below. 4B illustrates an example of a spectrum for a signal used to detect an unmanned aerial vehicle according to an embodiment of the present invention. Referring to FIG. 4B , in the frequency spectrum at the point 402 at time 5.1444 ms, it is confirmed that a signal having a relatively large magnitude is detected in the band belonging to the region 415 . 4C illustrates an example of empty power for a signal used to detect an unmanned aerial vehicle according to an embodiment of the present invention. Referring to FIG. 4C , it is confirmed that a signal having a relatively large size is detected in the time interval belonging to the region 415 from the empty power at the point 402 having a frequency of 2411.46 MHz.

Detection of a general unmanned aerial vehicle is performed when a signal with a magnitude greater than or equal to a set threshold level is generated. However, since the detection algorithm requires a large amount of computation, it can be a great burden to process all consecutive signals. Accordingly, in the case of a continuously existing signal, a method of processing sampled data may be adopted. However, when the unmanned aerial vehicle uses frequency hopping and OFDM, it is required that the detection execution time be very short. Therefore, the present invention extracts a signal band for a signal with a short duration, does not perform an operation for detection on all data within the extracted band, and performs detection only on a representative signal region or channel within the band, It can respond quickly to signals related to aircraft. Accordingly, direction detection accuracy for the unmanned aerial vehicle may be improved, and direction detection may be performed quickly.

5 illustrates an example of a procedure for generating a spectrogram image according to an embodiment of the present invention. 5 illustrates an operation method of a device (eg, the detection device 110 of FIG. 1 ).

Referring to FIG. 5 , in step S501 , the device converts a time domain reception signal into a frequency domain signal. For example, the device may convert a signal received through an antenna into I/Q data to determine the signal strength for each frequency, and perform a windowing operation, an FFT operation, and the like. At this time, in order to secure real-time, the device may quickly sample the input signal enough to satisfy the Nyquist criterion (eg, the sampling frequency exceeds twice the bandwidth of interest).

In step S503, the device determines a power value for each frequency. The device may calculate a power value for each frequency based on the frequency domain signal. According to an embodiment, the device may determine a power value for each frequency bin by grouping values included in the result of the FFT operation in units of frequency bins and combining power values in units of groups. Here, the frequency bin means a frequency range occupied by one pixel in the spectrogram image.

In step S505, the device generates an image in which a power value is expressed using a pixel value. In other words, the device generates a spectrogram in the form of an image, that is, a spectrogram image. Spectrogram images can be generated in real time with radio wave measurements. Specifically, the device may periodically generate the spectrogram image according to a predetermined time interval (eg, the length of a time section represented by one spectrogram image). Alternatively, the device may continuously update the spectrogram image by stepwise removing the past part and adding the new part stepwise over time.

6 illustrates an example of a procedure for determining a signal region based on a spectrogram image according to an embodiment of the present invention. 6 illustrates an operation method of a device (eg, the detection device 110 of FIG. 1 ).

Referring to FIG. 6 , in step S601 , the device performs image pre-processing. The device performs image-level correction on the spectrogram image. For example, preprocessing may include noise reduction operations (e.g. filtering, moving average, blurring, etc.), boundary value suppression operations (e.g. changing values below a threshold to minimum values, adjusting values close to a threshold upward or downward, etc.) may include at least one of That is, in order to more effectively select a signal region in the real-time spectrogram, filter processing for noise reduction, processing of setting a very low-level lower limit that occurs in FFT processing, and setting an upper limit on a value above a certain level at the lower limit At least one image processing algorithm among processing and continuous processing of pixels of a specific number or less may be applied. That is, the device generates a secondary image from the spectrogram image through pre-processing. Here, setting the lower limit means changing all pixel values lower than the lower limit to the lower threshold, and setting the upper limit means changing all pixel values higher than the upper limit to the upper threshold. In addition, the setting of the lower limit can be understood as an adjustment of the level to increase the accuracy of distinguishing the boundary between the signal and the noise, and the setting of the upper limit can detect a weak drone signal far away due to a strong signal close to the receiver It can be understood to improve the detection performance of the weak drone signal by doing it to prevent the performance degradation.

In step S603, the device converts the pixel values into binary values. A predefined threshold or a threshold determined based on the image is used for conversion to a binary value. That is, the device compares the value of each pixel of the preprocessed spectrogram image with a threshold, and changes the value of the corresponding pixel to a positive value if it is above the threshold and to a negative value if it is less than the threshold. In other words, the device creates a tertiary image by binarizing each of the pixel values of the secondary image.

In step S605 , the device determines at least one region to include pixels having a positive value. According to an embodiment, one region may be determined to have a rectangular shape specified by a starting point, a horizontal length, and a vertical length. For example, the region may be determined to include all pixels in a pixel cluster that include pixels having a threshold number or more of adjacent positive values. In this case, at least one pixel having a negative value may be included in the region. As another example, the region may be determined so that pixels having a negative value are not included. In this case, at least one pixel having a positive value in the cluster may be excluded from the region. As another example, the area may be determined such that a ratio of a pixel having a negative value to a pixel having a positive value is minimized.

In the procedure described with reference to FIG. 6 , an operation in which pixel values are converted into binary values is performed, and for this purpose, determination of a threshold is required. The threshold value may be determined according to various criteria, and the present invention is not limited to a specific threshold value determination criterion. According to an embodiment, the threshold may be determined based on a histogram of a spectrogram image. For example, when dividing pixels into two classes based on the threshold in the histogram, the device may set the threshold to maximize the variance between the classes. That is, the device may set a value that most uniformly distributes the light/dark distribution of the two classes as the threshold value.

7A and 7B illustrate examples of signal regions selected in a spectrogram image according to an embodiment of the present invention. 7A and 7B illustrate a result of selecting a signal band after pre-processing for a spectrogram image and displaying a region to be used for direction detection even within the band. In each of FIGS. 7A and 7B , 25 signal regions and 16 signal regions were selected. The existing wideband direction finding technique is performed for each frequency (channel) if the threshold level is higher than the threshold level for all frequency channels within the bandwidth at a specific time. On the other hand, as shown in FIGS. 7A and 7B, the boundary is divided by extracting the signal band in which the signal related to the unmanned aerial vehicle is expected to exist, and direction detection is performed within a specific frequency (eg, channel) belonging to the divided area, The amount of computation for direction detection is greatly reduced, and as a result, the direction detection execution time may be reduced. Furthermore, by performing channel direction detection by adding up frequencies (eg, channels) at the maximum level or near the maximum level among regions, the direction detection execution time may be minimized.

7A and 7B illustrate spectrograms in the WiFi band. Therefore, in the spectrogram, the area including the unmanned aerial vehicle signal and the area including the WiFi signal are mixed. In this case, since the unmanned aerial vehicle and the WiFi device will be estimated at different angles of incidence when direction detection is performed, the unmanned aerial vehicle may be distinguished by grouping a plurality of direction detection results.

8 illustrates an example of a procedure for detecting a direction of an unmanned aerial vehicle according to an embodiment of the present invention. 8 illustrates a method of operation of a device (eg, the detection device 110 of FIG. 1 ).

Referring to FIG. 8 , in step S801, the device checks a phase difference value between antenna elements of an array antenna. The array antenna may be a one-dimensional array antenna or a two-dimensional array antenna.

In step S803, the device determines the incident angle of the signal based on the phase difference value. Depending on the direction of the signal, a difference may occur between a distance between one antenna element and a signal source and a distance between another antenna element and a signal source, and the difference in distance causes a phase difference. Accordingly, the angle of incidence may be calculated based on the phase difference between signals received by the antenna elements. Here, the angle of incidence includes at least one of an azimuth and an elevation.

In step S805, the device determines the direction of the unmanned aerial vehicle based on the angle of incidence. The angle of incidence indicates a relative direction with respect to antenna elements included in the antenna array. Accordingly, the device may convert the calculated angle of incidence based on the phase difference value into an absolute direction or a direction based on other criteria.

As described with reference to FIG. 8 , the direction of the unmanned aerial vehicle may be determined. According to another embodiment, in addition to the direction, a distance to the unmanned aerial vehicle may be further estimated. For example, the device may estimate the distance based on signal strength to the unmanned aerial vehicle. As another example, the device may estimate the distance based on a means other than the signal (eg, loudness, image, etc.). In this case, the device may estimate how far the unmanned aerial vehicle is located based on a sound collected in the determined direction, an image captured in the determined direction, and the like.

According to another embodiment, in addition to the direction, the location of the unmanned aerial vehicle may be further estimated. For example, the location may be estimated using two or more direction finding devices. When directions are estimated by each of the direction finding devices disposed at different locations, a point where vectors representing the estimated directions intersect on the map may be estimated as the location of the unmanned aerial vehicle. That is, the existence and direction/position of the unmanned aerial vehicle may be estimated based on directions detected from each using two or more devices.

9A and 9B illustrate a principle of determining an incident angle using an array antenna according to an embodiment of the present invention. 9A illustrates the determination of an angle in a two-dimensional plane, and FIG. 9B illustrates an angle determination in a three-dimensional space.

Referring to FIG. 9A , a first antenna element 911 , a second antenna element 912 , and a third antenna element 913 are disposed at right angles on a plane. An angle between a straight line passing through the first antenna element 911 and the second antenna element 912 and a vector indicating the direction of the signal is α. Accordingly, the difference between the propagation distances of the received signals in the first antenna element 911 and the second antenna element 912 is d·cosα. Here, d is the distance between the first antenna element 911 and the second antenna element 912 . Since the difference in propagation distance may be derived from the phase difference, the angle α may be determined from the phase difference between the received signals at the first antenna element 911 and the second antenna element 912 .

Referring to FIG. 9B , the first antenna element 911 , the second antenna element 912 , and the third antenna element 913 are disposed at right angles to the xy plane. A signal is received with an azimuth α and an elevation Δ. _{The propagation distance difference L 1} between the first antenna element 911 and the third antenna element 913 is d·cosα·cosΔ, and the propagation distance difference L2 between the first antenna element 911 and the second antenna element 912 is d·sinα·sinΔ. Therefore, in the phase value difference between the received signals of the first antenna element 911 and the third antenna element 913, the phase value difference between the received signals of the first antenna element 911 and the second antenna element 912 Based on it, the azimuth angle α and the elevation angle Δ can be determined.

In addition to the scheme based on trigonometric functions as in FIGS. 9A and 9B , other schemes may be used. For example, an incident angle of a signal may be determined based on a circular antenna array including a plurality of antenna elements. When n antenna elements are included in the circular antenna array, n phase difference values may be obtained by calculating phase difference values of received signals between antennas adjacent to each other. The n phase difference values may be treated as one vector, and incident angles corresponding to each of the various vectors may be predefined in the form of a mapping table. In this case, the apparatus may check the n phase difference values and check the incident angle corresponding to the identified phase difference values from the mapping table.

According to the above-described various embodiments, the presence of the unmanned aerial vehicle may be detected, and the direction may be detected. However, as previously exemplified, there may be other signals (eg, WiFi signals) other than signals related to the unmanned aerial vehicle in the signal band. Therefore, it is necessary to distinguish it from the detection result for other signals and the detection result of the unmanned aerial vehicle. According to an embodiment, the device may classify the detection result of the unmanned aerial vehicle based on the signal generation pattern. As described above, a signal transmitted or received from the unmanned aerial vehicle may have a certain pattern (eg, short duration, frequency hopping).

Accordingly, the device may determine a signal similar to a predetermined pattern to a certain level or more as a signal related to the unmanned aerial vehicle. Specifically, the device classifies the signal regions identified in the spectrogram image into a plurality of groups, and determines which group corresponds to the signal related to the unmanned aerial vehicle based on the size and frequency axis position of the signal regions belonging to each group. can Here, for classification, the device may use at least one of an average intensity of a signal domain, a bandwidth of a signal domain, and a time axis length of the signal domain as a reference.

The radio wave measurement method according to the embodiment described above may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured according to the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

Each of the drawings referenced in the description of the previous embodiment is merely an embodiment shown for convenience of description, and items, contents, and images of information displayed on each screen may be modified and displayed in various forms.

Although the present invention has been described with reference to an embodiment shown in the drawings, this is merely exemplary, and those of ordinary skill in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Accordingly, the true technical protection scope of the present invention should be defined by the technical spirit of the appended claims.

Claims (10)

A method of operating a device for detecting an unmanned aerial vehicle, the method comprising:
generating an image representing a real-time spectrogram by detecting radio waves;
generating a secondary image by performing pre-processing on the image;
generating a tertiary image by binarizing each of the pixel values of the secondary image;
determining at least one region based on at least one cluster of pixels having a positive value among pixels having binarized values included in the tertiary image; and
and finding a direction of the unmanned aerial vehicle based on received signals corresponding to the at least one area.
The method according to claim 1,
classifying the at least one region into a plurality of groups; and
The method further comprising the step of identifying a group corresponding to the signal related to the unmanned aerial vehicle based on at least one of a size and a frequency axis position of at least one signal region belonging to each of the plurality of groups.
The method according to claim 1,
The step of detecting the direction of the unmanned aerial vehicle comprises:
reading information on received signals corresponding to the at least one region; and
and determining the direction of the unmanned aerial vehicle based on the analysis of the received signals.
delete The method according to claim 1,
The pre-processing includes at least one of a noise reduction operation on the image and a boundary value suppression operation on pixel values included in the image.
6. The method of claim 5,
The boundary value suppression operation includes one of an operation of changing values less than a threshold among the pixel values to minimum values and an operation of upwardly or downwardly adjusting values adjacent to the threshold.
The method according to claim 1,
The process of detecting the direction of the unmanned aerial vehicle is
checking phase difference values between received signals at antenna elements of an array antenna;
determining an incident angle of the received signals based on the phase difference values;
and detecting the direction based on the angle of incidence.
The method according to claim 1,
The method further comprising the step of estimating a distance to the unmanned aerial vehicle.
9. The method of claim 8,
The distance is estimated based on at least one of a sound collected in the direction and an image captured in the direction.
A device for detecting an unmanned aerial vehicle, comprising:
a signal receiving unit for receiving received signals;
a real-time signal processing unit that generates a real-time spectrogram of the received signals; and
A processor connected to the real-time signal processing unit,
The processor is
To detect radio waves and generate an image based on the real-time spectrogram,
By performing pre-processing on the image, a secondary image is generated,
A tertiary image is generated by binarizing each of the pixel values of the secondary image,
determining at least one region based on at least one cluster of pixels having a positive value among pixels having binarized values included in the tertiary image;
An apparatus for detecting a direction of the unmanned aerial vehicle based on received signals corresponding to the at least one area.

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