KR20190049086A - Unmanned High-speed Flying Precision Position Image Acquisition Device and Accurate Position Acquisition Method Using the same - Google Patents

Abstract

To solve disadvantages and problems in existing technologies, the present invention relates to a device for obtaining precision position images during a high speed flight of an unmanned aerial vehicle and a method for obtaining precision position using the same. The device is as follows: obtaining rapid 2D precision position data from ocean, wide rivers, farming information difficult in identification and information on forest of which shaking is acute; correcting optimally and physically locations, posture and angles of an unmanned aerial vehicle navigation system; enabling 2D ortho-arranging position verification in real time by images during a high speed flight of an unmanned aerial vehicle necessary for data position determination in real time and an image data map matching algorithm necessary for verification of sensor data position determination; and enabling 2D ortho-arrangement through the image obtained by the unmanned aerial vehicle and error correction of locations and angle arrangement of sensor data by means of an arrangement determination algorithm of image data for identification of the ground and the air in order to determine positions during a high speed flight of the unmanned aerial vehicle and to correct errors of navigation sensor information.

Description

[0001] The present invention relates to a precision position image acquisition apparatus and a precision position acquisition method using the same,

More particularly, the present invention relates to an image data map matching algorithm and a real-time two-dimensional (2D) orthogonal arrangement for high-speed in-flight image and sensor data positioning error optimization verification. Position verification and error correction of navigation information during position verification and UAV flight is performed through 2D image alignment decision algorithm. The present invention relates to an apparatus for acquiring a precise position image during a UAV and a method for acquiring an accurate position using the same.

Spatial information includes location information on natural or artificial objects existing in space such as ground, underground, water, underwater, and spatial information related thereto and information necessary for decision making (Article 2 (1) and (Article 2, Paragraph 1 of the 「Guidelines for Standardization of Spatial Information of National Geographic Information Sources」), it is a service market of location information and attribute information about natural and artificial objects existing in the space.

With the development of spatial information construction technology, the range of acquisition and utilization of spatial information has been expanding. Especially, 3D space information field is growing rapidly with the development of aerial photogrammetry technology.

Conventional satellite images and aerial photograph raster data have a merit of providing a wide range, but they can not be repeatedly photographed only in a small specific area, and spatial resolution is mainly 11cm ~ 1m class image, With the development of various new technologies, the paradigm of spatial information construction is rapidly changing.

In recent years, technology development has been progressing in various fields because it has the merit that it can acquire 5cm high resolution image which can not be provided in satellite and airline easily by using UAV.

In addition, demand for rapidly changing spatial information and rapid and high-level data renewal are required, and rapid data construction is required in the environmental GIS field such as global warming such as red tide and green tide. However, the fast data processing is difficult to precisely arrange the acquired data due to the limit of eliminating the sensor error of the UAV.

With the rapid growth of the small UAV market in recent years, acquisition of space information data and application fields using UAV have been gradually expanded.

Especially, the spatial information industry is widely used in various environments such as urban areas, forests, and oceans, and the acquisition and operation of precise location based image and sensor data is widely utilized. Currently, image and sensor data of the mission equipment installed in low cost small unmanned aerial vehicles, ImageUltra Mapping Process (IMU), geomagnetic sensor, and azimuth sensor are also commonly used.

Data processing such as Image or Hyper Spectra Sensor and thermal image sensor using latest UAV is mostly processed by 3D orthographic mapping processing through commercial specialized software such as Pix4D mapper Overlay Mapping Process is performed. However, it is necessary to secure high or high resolution with most incorrect GPS, IMU, and geomagnetic sensor (azimuth sensor) .

In addition, although the accuracy is improved due to the correction of the multiple side points of the aerial identification reference point surveying for high precision position accuracy, it has a disadvantage of requiring a long post-processing time.

Also, for the orthoimaging process provided by the commercial software, the target data with high overlapping is arranged in the virtual space, and the digital elevation (DME) is obtained by calculating the elevation value by the overlapping, As a final step, it is a conventional technique that a precise post-processing 3D terrain information is obtained through a digital surface model (DSM) process of applying a 3D image to a 3D model.

Although software post-processing correction is performed with inaccurate GPS and IMU attitude information of such UAV, data such as image or Hyper Spectra sensor, thermal image, Terrain data is not being properly generated in non-standardized environments such as lush forests, extensive agricultural areas, high-impact rivers, and marine environments. Also, since the image sensor data processing requires a high degree of overlapping in a wide space, it is difficult to acquire fast data, and ortho image or terrain information of an accurate position is generated by ensuring linear common stereo information with high overlapping degree.

In recent years, there has been an increase in the market for construction of big data (GIS) by the 2-dimensional orthogonal mapping processing by the real-time operation of UAV, and the overlapping real- , The terrain change monitoring and image object analysis are increasingly utilized. Therefore, a real-time operation method, a fast two-dimensional orthogonal placement, an overlay mapping process, and a precise position correction method are required.

Real-time two-dimensional (2D) orthogonal placement by minimizing overlap in a terrestrial data environment where it is difficult to extract non-standardized or linear common stereo information, such as bushy forests, extensive agricultural areas, Development of technology is required.

In addition, satellite navigation (GNSS) and inertial sensors are very important in the development of unmanned airplanes. However, because it is difficult to acquire accurate position information of the ground data during flight due to GNSS, inertial navigation acceleration error, altitude error, geomagnetism error, flight control error, gimbal control error, and image shutter error factor, Software processing through environment optimization is needed.

In real-time processing, real-time processing is inevitable because it is difficult to arrange real-time orthogonality due to communication with big data.

It is expected that quasi - real - time orthogonal processing will be more efficient than post - software dependency processing, and 2D rectangle positioning with accuracy of less than 1m will be possible if the correction algorithm is constantly improved through 2D orthogonal arrangement of acquired images.

However, it is difficult to verify the inertial navigation error with the satellite navigation receiver on the UAV, and it is expected that the GPS position coordinate dependent image processing will cause a large position error of several tens of meters or more and it is difficult to correct the side point because of cumulative error factors such as complex geomagnetism, There was a problem that the construction of GIS such as maritime, forest, and farming was difficult in reality.

Korean Patent Publication No. 2003-0068871 (published on August 25, 2003) - Remote search system using UAV

SUMMARY OF THE INVENTION Accordingly, the present invention has been made keeping in mind the above problems occurring in the prior art, and an object of the present invention is to provide a method and apparatus for acquiring fast two-dimensional accurate position data from sea, wide river, difficult agricultural information, Real-time two-dimensional (2D) orthogonal placement position verification with image data matching algorithm (image matching) required for position, attitude, angle physical optimization and real-time data positioning UAVs that can be deployed in two dimensions by correcting errors in location, angle placement of sensor data, and acquiring UAVs with a decision algorithm of land aerial identification image data to correct errors in positioning and navigation sensor information during high speed UAV And a precise position acquisition method using the same It has its purpose.

In order to achieve the above object, there is provided an apparatus for acquiring a precise position image during a high speed flight of a UAV; (2) a virtual grid matching algorithm (2D) for arranging image or sensor information by correcting a placement error of the aerial identification image with respect to the image information and sensor information obtained from the UAV by checking the aerial identification image on the ground (2D) orthogonal arrangement algorithm processing structure and a pixel vector image grid matching (Grid Map matching) positioning algorithm are used, and the 2D (Orthogonal) When the image is transmitted by bidirectional data communication from the UAV to the ground control equipment, the ground control equipment performs algorithm mapping coordinate determination through image data conversion And vector data are arranged in a two-dimensional (2D) square on the geocentric coordinate system of the virtual space, (2D) coordinate pixel data size change based on unmanned physical coordinates including the position direction and position accuracy of the pixel vector image analyzed by the earth center coordinate system calculation algorithm, And performs an arrangement mapping process (Overlay Mapping Process).

Here, the ground control equipment comprises an image data processing unit for processing the received image data when the image data transmitted from the camera of the UAV is received through a communication unit for bidirectional communication with the UAV, A memory unit for storing data of the image data processing unit and the sensor data processing unit; an ortho-image position data analyzing unit for analyzing ortho-image position data in the image data processed by the image data processing unit; An image data image analyzing unit for analyzing the image data of the image data and a sensor image data analyzing unit for converting the image data into an identical structure of pixel vector data having a data image conversion analysis structure, So that 2D rectangles can be It is characterized by configured by a display unit and a control unit for displaying the sensor data analysis unit, the resulting data.

And a physical optimization error correction method using the aerial identification image, which is a flight identification precise position coordinate acquired beforehand by the UAV, the orthogonal placement algorithm processing may be performed by a Boundary calculation according to an altitude included in images of the UAV (A, B, C, D) ENU of the square information and the ENU (East-North-Up) ) to ECEF (Earth-Centered Earth-Fixed) value to an ECEF to LLH (top / longitude) conversion and performs an image processing process using GPS data.

In order to achieve the above object, there is provided a method for acquiring a precise position using a precise position image acquisition device in a UAV, comprising the steps of: acquiring a precise position image including an aerial identification image of a ground during a high-speed flight; The ground control equipment corrects the image information obtained from the UAV and the placement error of the aerial identification image to generate a virtual grid matching algorithm. (2D) orthogonal arrangement algorithm processing structure and a pixel vector image grid matching method (Grid Map matching) positioning algorithm are used as the above-mentioned ground control equipment, (2D) coordinates based on the unmanned physical coordinates such as the altitude position direction, and the size of the 2D 2D coordinate data And position accuracy of the pixel vector image analyzed by the geocentric coordinate system calculation algorithm. The software installed in the processor of the terrestrial control equipment collects the 2D image information of the sequential processing diagram through the image processing function so that one image can be created by collecting the image information of the sequential processing diagram. And an image processing algorithm is applied after arranging the image by using the position / length, altitude, and heading for the grid map matching arrangement, and the accuracy of the flight identification precision position coordinate obtained by the UAV 100 Boundary calculation according to the altitude of the UAV 100, data acquisition by Pythagorean theorem and the triangulation method with distance = altitude x slope value as the physical optimization error correction method using the aerial identification image, B, C, D) Calculate ENU, convert ECEF to Earth-Centered Earth-Fixed (ECU) to LF (ENU) Performing an image process using ortho arrangement; including features to improve the accuracy of the image acquisition position.

The present invention has the following effects.

First, it is necessary to acquire fast two-dimensional precise position data from sea, wide river, difficult agricultural information, forest information with tremble tremor, physically optimal correction of position, posture and angle of UAV, It is possible to verify real-time two-dimensional (2D) orthogonal placement position by using image data matching algorithm.

Second, in order to correct the error of positioning and navigation sensor information during UAV flight, it is possible to arrange 2D aerial image by correcting errors of UAV acquisition image, It can be used to generate accurate terrain information data modeling from UAVs, wide agricultural areas, and UAV sensors and flight processing environments, where it is difficult to extract non-standardized or linear common stereo information such as moving river environments.

FIG. 1 is a view for explaining an apparatus for acquiring a precise position image during a high speed UAV in accordance with the present invention.
FIG. 2 is a diagram illustrating a two-dimensional (2D) ortho placement algorithm processing structure in an apparatus for acquiring a precise position image of a UAV in high speed in flight according to the present invention.
3 is a view showing an example of a ground control apparatus among the apparatus for acquiring a precise position image in the UAV shown in FIG.
4 and 5 are views showing a 2D image arrangement of a thermal image sensor acquired in a marine environment using an apparatus for acquiring a precise position image in a UAV, according to the present invention.
FIG. 6 is a photograph showing an example of 2D rectangle placement result data using the apparatus for acquiring a precise position image during high speed flight in UAV according to the present invention.
FIG. 7 is a photograph showing an example in which a high-resolution image is acquired by commercial post-processing software for 2D rectangle placement result data using the apparatus for acquiring a precise position image in the UAV in accordance with the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

In addition, although the term used in the present invention is selected as a general term that is widely used at present, there are some terms selected arbitrarily by the applicant in a specific case. In this case, since the meaning is described in detail in the description of the relevant invention, It is to be understood that the present invention should be grasped as a meaning of a term that is not a name of the present invention. Further, in describing the embodiments, descriptions of technical contents which are well known in the technical field to which the present invention belongs and which are not directly related to the present invention will be omitted. This is for the sake of clarity of the present invention without omitting the unnecessary explanation.

As described above, it is necessary to develop the software that can predict the error factors with the virtual target map matching technique algorithm that can quickly verify the physical error factors and verify the accuracy through the quasi-real-time 2D square placement of the acquired images.

It is designed as a data processing arrangement (Grid), a data analysis topographical information mapping (mapping), and a user interface (GUI) item to implement a virtual matching algorithm for verifying the physical error factor of UAV.

FIG. 1 is a view for explaining an apparatus for acquiring a precise position image during a UAV in accordance with the present invention. FIG. 2 is a diagram for explaining a two-dimensional (2D) to be.

FIG. 1 shows an apparatus for acquiring a precise position image during a high speed flight in the UAV according to the present invention. The collected data processing for the UAV 100 for acquiring a precise position image during high-speed flight is based on raw data Pixel vector position information processing method.

For reference, the UAV is a GPS receiver, an accelerometer, a gyro sensor, a geomagnetic sensor, a pressure sensor, a temperature sensor, a flow sensor camera, an altimeter infrared camera, HD camera, GIMBAL, USB connection for WiFi or LTE communication, card slot (eg SD card), RS-232. RS-485 and ADC interface.

The ground maneuvering apparatus 200 checks the aerial image 300 to correct the placement error of the aerial image 300 and the image information obtained from the UAV 100 The image information or the sensor information is arranged in a 2D square shape by a virtual grid matching algorithm. To this end, the ground control equipment 200 is provided with a 2D rectangle arrangement software (2D rectification algorithm) and includes a two-dimensional (2D) rectangle arrangement algorithm processing structure and a Pixel vector Image grid-matching (Grid Map matching) positioning algorithm is used. For reference, the Pixel Vector Image Grid Map matching location algorithm will be reliable as it utilizes existing open data in the present invention.

This software for 2D orthogonal placement is particularly useful in thermal image sensor (IR) data that is difficult to image match other than image image orthogonal placement. Using the collected IR RAW data (raw data, raw data) and RAW data of pixel attributes, it is possible to apply the reference absolute temperature compensation algorithm for each pixel and analyze the data that can measure the sea water temperature deviation. And a processing method for converting the IR RAW data into a temperature distribution image, performing data processing for arranging image position data and logging information in a 2D square shape, and visualizing the image data so that the image data can be easily displayed to the user using the final calculated result value .

In this case, IR RAW DATA Analyze and EO / IR EXIF (Position Information Data) processing are performed in the same manner as the image processing method, IR raw data image conversion and IR / EO Image 2D orthographic positioning are performed , The GUI can perform both the analysis image GUI display and the post processing data and the sensor data UI display.

The data analysis application, the sensor data processing and the GUI are arranged in the same 2D manner through the image arrangement method and the sensor data processing method, and will be described in detail later.

Reference numeral 101 in Fig. 1 denotes a pixel quadrangle (A, B, C, D) coordinate position obtained in the UAV 100. Reference numeral 102 denotes an aviation identification precision geographical coordinates and a heading position at an already known position, (102) and a positional coordinate error correction reference coordinate (104), and 104 denotes an error (102) between the heading angle of the airside identification coordinate and the square heading angle of 101 obtained in the UAV 100 Reference coordinates).

The analysis of the pixel vector data for the images obtained from the camera of the UAV 100 is transmitted by the two-way data communication from the UAV 100 to the ground control equipment 200. Based on the unmanned physical coordinates such as the altitude position direction, the vector data is placed on the earth center coordinate system of the algorithm and the ground coordinate system of the virtual space through the image data converter of the ground control equipment. (2D) overlapped layout mapping processing technique having a structure for calculating the position accuracy navigation coordinates of a pixel vector image analyzed by a two-dimensional (2D) coordinate pixel data size change and an earth center coordinate system calculation algorithm .

Algorithm for Calculating the Earth-Centered Coordinate System The software architecture is composed of several functions. As shown in Fig. 2, the position data (EXIF) tagged in the image is calculated in the position data layer (EXIF Class) The function to calculate and process the tagged EXIF (position data information), the LLH to PIXEL function (Fuction) which can convert collected Latitude / Longitude / Altitude information into Pixel units, And a Rotate function (Function) for rotating the image based on the true north direction using heading information that is converted to an image.

At this time, the processor (PROC.) Of FIG. 2 determines the direction and determines the 2D orthogonal arrangement through the physical arrangement coordinates.

In particular, the rotation function for the true-north direction image rotation processing routine by correcting the difference between the heading sensor information of the north-north reference and the ground reference data of the image obtained by acquiring the aerial reference ground reference data, So that the error correction can be reflected.

The error correction is applied so that the image required for the rectangle placement algorithm is generated by correcting the position data and the logging information collected from the UAV, and the binary data is included in the jpg format by including EXIF (image position data) .

What you need to consider when deploying 2D rectangles is the position data and sensor logger information of the UAV. The minimum required data is laid out one by one to the pixels by calculation with Latitude, Longitude and Altitude data.

The data processing part consists of image processing and sensor data routines such as IR. In the sensor IR RAW data routine, correct data is generated by correcting the errors according to the sensor characteristics. In particular, the temperature data for each pixel of IR RAW data is calculated by calibrating the absolute value temperature and the relative value temperature for each pixel, and the final result data is designated as the temperature distribution color according to the pixel-specific temperature. Using this, one IR raw data file is generated as image data as one jpg image, and the EXIF value is separately formed in the jpg image as the image file in the final routine to create the position data of the corrected image.

And the software installed in the processor processed the structure of storing the 2D rectangle arrangement collected image in the memory through the image processing function (Image Processing Function) so that the image information of the sequential processing diagram is collected and one image can be created.

FIG. 3 shows an example of the ground control device 200 among the apparatus for acquiring a precise position image shown in FIG. 1. The two-dimensional (2D) rectangle arrangement is a communication unit for bidirectional communication with the UAV 100 The image data processing unit 220 processes the received image data when the image data transmitted from the camera of the UAV 100 is received through the image sensor 210 and the sensor data processing unit 220 which processes the sensor data from various sensors of the UAV 100. [ A memory 240 for storing data processed by the image data processing unit 220 and the sensor data processing unit 230 and a memory 240 for storing image data of the image data in the image data processed by the image data processing unit 220. [ An orthographic image position data analyzing unit 250 for analyzing the data and an image data image analyzing unit 260 for analyzing the image data of the image data, The analysis unit 250 has imaging information of the UAV 100 and a satellite navigation and attitude information analysis structure. The sensor data analysis unit 270 mainly includes an ultra-spectral sensor and a thermal image (IR) Transformed into the same structure of the next pixel vector data having the transformation analysis structure, and the 2D square arrangement is made by integrating the two modules and the result data.

The integrated result data is displayed on the display unit 280. The control unit 290 includes a communication unit 210, an image data processing unit 230, a memory unit 240, a normal image position data analysis unit 250, The image analysis unit 260, the sensor data analysis unit 270, and the display unit 280. [

Since the geocentric coordinate positioning of the 2D orthopedic placement algorithm is generally difficult to apply the panoramic image arrangement method using the pixel vector image pattern, the UAV acquisition information applied to the present invention can be used for the grid map matching placement / Alignment processing algorithm after image placement using hardness, altitude, and heading.

However, since the quasi-real-time grid map matching can not be verified by orthogonal placement as the data position error is larger, the physical optimization using the aviation identification image 300, which is the flight identification precise position coordinate acquired beforehand by the UAV 100 Bentley calculation according to altitude, calculation by Pythagorean theorem and triangulation method with center value (ECEF 36.000, 127.000) at distance = altitude x slope value, and four points (A, B, C and D) ENU, ECEF to LLH conversion of East-North-Up (ENU) to Earth-Centered Earth-Fixed (ECEF) values and image rectification using GPS data, Is possible.

The center coordinate calculation of the image or sensor data for orthogonal placement is based on the pole radius calculation equation (equation 1) and the earthlength calculation (equation 2) as shown in the following equations 1 to 5 in FIG. (3), the distance between the axis of rotation and the distance of the equatorial plane (Equation 4), the distance of the observations by Pythagorean theorem and trigonometry, and the latitude calculation algorithm (Equation 5) To determine the pixel vector position.

Data Analysis Topographical Mapping 2D 2D mapping software software performs Pixel positioning algorithm based on Latitude, Longitude and Altitude flight log information including image / sensor data, (2D) sequential arrangement one by one according to equations (1) to (5).

Particularly, in the image data processing unit 220, generation of location data of raw data per pixel, minimum and maximum values of latitude and longitude are calculated, and an automatic conversion decision algorithm is performed so that the sizes are standardized to the same standard according to the image standard and the altitude scale.

The maximum minimum value of each degree of latitude is obtained by calculating the center point of the east, west, north, south, and east / west sides, and the final image scale is calculated based on the Min / Max value. The 2D position is determined by the UAV 100 by correcting the precise position and the error angle deviation obtained beforehand by the UAV 100 in order to calculate, correct the real number, and rotate the heading value.

4 and 5 are views showing a 2D image arrangement of a thermal image sensor acquired in a marine environment using an apparatus for acquiring a precise position image in a UAV, according to the present invention.

The thermal image sensor 2D rectangle arrangement obtained in the marine environment using the apparatus for acquiring a precise position image of the UAV according to the present invention is as shown in FIG. 4 and FIG. 5. The rectangle arrangement is repeated based on the basic information of the image and the sensor And the thermal image (IR) data coordinates are obtained at the resolution position by the ortho arrangement software of Fig. 4, and 2D rectangle arrangement is performed.

Precision surveying in marine environment where image difficulty is difficult Reference data of ground side point Obtained orthocopy accuracy has a method of increasing accuracy by acquiring and correcting a plurality of aerial identification data information.

In order to utilize the experiment of orthogonal placement software in GIS construction such as marine, forest, agricultural, etc., the data was verified through the 3 km flight using the thermal image sensor of the sea environment. It is confirmed that the arrangement of the acquired data is within 1m when there is no influence by wind and when there is influence by wind.

2D orthogonal placement through 2D (2D) orthographic placement software can be used to input UAV equipment or sensor information to 2D orthographic placement software, and to input aerial identification survey location coordinates together for ground accurate location calibration, When the acquired image or sensor data is transmitted from the measurement position coordinates, the ground control device confirms the corresponding aerial identification image and corrects the placement error of the aerial image and the information obtained from the UAV to match the image or sensor information to the virtual grid Grid Map matching algorithm.

FIG. 6 is a photograph showing an example of 2D square placement result data using the apparatus for acquiring a precise position image during a UAV in accordance with the present invention. This is a photograph showing an example in which a high-resolution image is ensured by commercial post-processing software for batch result data.

6, the flight data of the 2D orthogonal placement result is shown in FIG. 6, which is a flight of 700m x 200m, which is followed by flight 15 minute (about 5km) The accuracy of orthogonal positioning is improved as the number of aerial identification precision geodesic points is increased, and quick 2D terrain image processing algorithm of proximity image can be applied by separate image 2D mapping algorithm to obtain quasi-real time fast topographical information.

And FIG. 7 is a photograph showing an example of securing a 5 cm high-resolution image by commercial post-processing Pix 4 D Mapper software.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. Various modifications may be made without departing from the spirit of the invention. Therefore, the examples disclosed in the present invention are not intended to limit the scope of the present invention and are not intended to limit the scope of the present invention. The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of equivalents should be construed as falling within the scope of the present invention.

100: UAV 200: Ground control equipment
210: communication unit 220: video data processing unit
230: sensor data processing unit 240: memory unit
250: ortho data location data analysis unit
260: image data image analysis unit 270: sensor data analysis unit
280: display unit 290:
300: aerial identification image

Claims (4)

UAV (100) for acquisition of precise position image during high - speed flight;
The image recognition unit 300 checks the aerial image 300 on the ground to correct the placement error of the aerial image 300 with respect to the image information and sensor information obtained from the UAV 100, Dimensional (2D) orthogonal arrangement algorithm processing structure and a pixel vector image grid matching (Grid Map matching) positioning (2D) square matching software Algorithm,
The analysis of the pixel vector data for the images acquired by the camera of the UAV 100 is performed when the image is transmitted by the bidirectional data communication from the UAV 100 to the ground control apparatus 200, ) Is based on the 2D coordinates of the algorithm coordinates and the vector coordinate data on the geocentric coordinate system of the virtual space through 2D image transformation, and based on the unmanned physical coordinates including the altitude position direction, (2D) coordinate pixel data size and a position accuracy navigation coordinate of a pixel vector image analyzed by the earth-center-coordinate-system calculation algorithm, and performs a two-dimensional (2D) overlapping mapping process Accurate position image acquisition device during UAV flight.
The method according to claim 1,
The ground control equipment (200)
An image data processing unit 220 for processing the received image data when the image data transmitted from the camera of the UAV 100 is received through the communication unit 210 for bidirectional communication with the UAV 100,
A sensor data processing unit 230 for processing sensor data from various sensors of the UAV 100,
A memory unit 240 for storing data of the image data processing unit 220 and the sensor data processing unit 230,
An orthographic image position data analyzer 250 for analyzing orthographic image position data from the image data processed by the image data processor 220,
An image data image analyzing unit 260 for analyzing the image of the image data,
A sensor data analysis unit for converting 2D image data into an identical structure of pixel vector data having a data image conversion analysis structure by using an ultrasound sensor and an infrared sensor data analysis unit, 270,
And a display unit (280) for displaying the result data and a control unit (290).
The method according to claim 1,
In the physical optimization error correction method using the aerial identification image 300, which is the flight identification precision position coordinate acquired by the UAV 100,
Boundary calculation according to the altitude included in the images of the UAV 100 in the ground control equipment 200, centering on the distance = altitude x inclination value and centering (ECEF 36.000, 127.000) of the Pythagorean theorem and triangulation (A, B, C, D) ENU and convert ECEF to LLH (Earth-Centered Earth-Fixed) to ENU (East-North-Up) Wherein the accuracy processing is performed by performing an image matching process using an image.
A method of acquiring a precise position using the apparatus for obtaining a precise position image of a high speed unmanned aerial vehicle according to any one of claims 1 to 3,
Obtaining a fine position image including the aerial identification image (300) on the ground during high-speed flight;
The ground control apparatus 200 corrects the image information obtained from the UAV 100 and the placement error of the air ID image 300 so that the image information or the sensor information is subjected to a virtual grid matching algorithm, (2D) orthogonal arrangement algorithm processing structure and a pixel vector image grid matching algorithm (Grid Map matching) positioning algorithm,
The ground control equipment 200 receives the vector data in a two-dimensional (2D) square arrangement on the geocentric coordinate system of the algorithm and the geocentric coordinate system of the virtual space through an original image data converter, 100) Position accuracy of the pixel vector image analyzed by 2D 2D coordinate transformation based on physical coordinates and the earth center coordinate system Algorithm 2 dimensional (2D) overlapping mapping processing (Overlay Mapping Process ),
The software installed in the processor of the ground handling equipment 200 stores the 2D rectangle arrangement collected image through the image processing function so that the image information of the sequential processing diagram can be collected and one image can be generated and the grid map matching ) For placement, use image processing algorithm after placement of images using head / hardness, altitude, and heading,
A physical optimization error correction method using an aerial identification image 300 that is a flight identification precise position coordinate acquired by the UAV 100 according to an altitude of the UAV 100, (A, B, C, D) ENU and calculate the value of ENU (East-North-Up) to ECEF (Earth-Centered Earth-Fixed) to ECEF to LLH And performing an image matching process using GPS data to improve the accuracy of the image acquisition position. The method for acquiring the precise position using the precise position image acquiring device in the UAV.

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