Target positioning method and device based on digital elevation model, equipment and medium

Abstract

The present application relates to a target positioning method and device based on a digital elevation model, equipment and medium, the method comprising: acquiring a full dynamic video for a target to be positioned, acquiring each frame of the image in the full dynamic video, for each frame of the image, converting the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates according to the corresponding pod parameters and the parameters of the unmanned aerial vehicle; according to the geographical coordinates corresponding to the target to be positioned in each frame of the image, determining the predicted altitude corresponding to the target to be positioned; according to the geographical coordinates corresponding to the target to be positioned in each frame of the image and the preset digital elevation model, determining the real altitude corresponding to the target to be positioned; according to the real altitude and the predicted altitude corresponding to the target to be positioned, determining the positioning result of the target to be positioned. Through the method of the present application, the target result of the target to be positioned can be determined.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of positioning, in particular, the present application relates to a target positioning method and device based on a digital elevation model, equipment and medium. BACKGROUND

[0002] In the process of unmanned aerial vehicle video inspection, the field of view of the video picture is large, and the threat target concerned by the user only accounts for a small part of the video picture. In order to qualitatively analyze the threat target, the distance between the threat target and the protected target needs to be estimated. For example, for unmanned aerial vehicle video inspection of oil and gas pipelines, when the distance between the third-party construction vehicle and the oil and gas pipeline is less than 200 m, the third-party construction vehicle is considered as a threat target. Therefore, only by realizing high-precision threat target positioning can the unmanned aerial vehicle video inspection task be efficiently and accurately realized.

[0003] The existing target positioning methods mainly include the following three kinds: (1) target positioning based on collinear configuration; (2) target positioning based on image matching mode; and (3) active target positioning based on laser ranging. The target positioning method based on collinear configuration needs to obtain the flight attitude, latitude and longitude of the unmanned aerial vehicle, as well as the attitude of the pod and the pod camera sensor information. Then, the ground target position is calculated according to the collinear condition equation. In actual use, this method needs to assume that the target area to be measured is a flat ground, and the target positioning accuracy is low. The target positioning method based on image matching mode uses the available multi-angle multi-source images, and matches the corrected unmanned aerial vehicle pod image with the reference picture under the condition of pre-established reference picture, so as to realize target positioning. This method has high positioning accuracy, but the acquisition of reference pictures has certain limitations, and the real-time performance of picture matching is poor, so the practicability is not high. The active target positioning method based on laser ranging has the highest positioning accuracy, but is limited by the cost, and is mainly applied in the military field at present.

[0004] In addition, the error of target positioning accuracy is related to the spatio-temporal consistency of the input unmanned aerial vehicle parameters (unmanned aerial vehicle attitude, latitude and longitude) and pod parameters (pod attitude, pod camera sensor information). The existing method obtains the unmanned aerial vehicle parameters and pod parameters respectively, and then transmits them back to the ground terminal server through the unmanned aerial vehicle data link and image link respectively. The ground terminal server obtains the unmanned aerial vehicle parameters and pod parameters, and then fuses and solves them through the target positioning algorithm to obtain the geographical position of the threat target. In this method, the frequency bands and data sizes transmitted by the data link and the image link are different, and the data delay in the transmission process is large. Therefore, this method causes the spatio-temporal inconsistency of the input data due to the link delay in the transmission process, thereby reducing the target positioning accuracy. SUMMARY

[0005] The technical problem solved by the present application is to provide a target positioning method, device, equipment and medium based on a digital elevation model.

[0006] The technical solution for solving the above technical problem is as follows: a target positioning method based on a digital elevation model, the method comprising:

[0007] Obtaining full dynamic video for a target to be positioned, the full dynamic video being determined based on data collected by a drone carrying a pod for the target to be positioned, the data including frames of images and pod parameters and drone parameters corresponding to each frame of image, for each frame of image, the pod parameters including a pod attitude and pod camera sensor information, and the drone parameters including a drone attitude and latitude and longitude information;

[0008] Obtaining each frame of image in the full dynamic video, for each frame of image, converting pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates according to the pod parameters and the drone parameters corresponding to the image;

[0009] Determining a predicted altitude corresponding to the target to be positioned according to the geographical coordinates corresponding to the target to be positioned in each frame of image, and determining a true altitude corresponding to the target to be positioned according to the geographical coordinates corresponding to the target to be positioned in each frame of image and a preset digital elevation model, the digital elevation model including longitude, latitude and altitude of each point;

[0010] Determining a positioning result of the target to be positioned according to the true altitude and the predicted altitude corresponding to the target to be positioned.

[0011] The present application has the advantages that: in view of the problems of poor positioning accuracy and poor effectiveness of existing target positioning algorithms, the present application integrates a digital elevation model, compares the predicted altitude and the true altitude, and accurately and quickly determines the position of the target to be positioned, i.e., the positioning result, thereby reducing the influence of complex terrain on the positioning algorithm in the case of prior information digital elevation model data, and achieving high positioning accuracy and strong real-time performance.

[0012] On the basis of the above technical solution, the present application can be further improved as follows.

[0013] Further, the above method further comprises:

[0014] Collecting each frame of image, pod parameters and drone parameters of the target to be positioned region by the drone carrying the pod;

[0015] Encoding each frame of image and the pod parameters and drone parameters corresponding to each frame of image to obtain the full dynamic video.

[0016] The beneficial effect of the further scheme is that the unmanned aerial vehicle on-board end performs space-time synchronization data processing on the data collected by the unmanned aerial vehicle, thereby ensuring high space-time synchronization of input data of a target positioning algorithm.

[0017] Further, the method further comprises:

[0018] obtaining a plurality of pixel point coordinates and geographical coordinates corresponding to each of the pixel point coordinates;

[0019] determining a first conversion relationship between the pixel point coordinates and the geographical coordinates through a perspective model conversion according to the pixel point coordinates and the geographical coordinates;

[0020] For each of the images, the conversion of the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters comprises:

[0021] the conversion of the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates through the first conversion relationship according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters.

[0022] The beneficial effect of the further scheme is that the first conversion relationship between the pixel point coordinates and the geographical coordinates can be accurately determined based on the perspective model conversion, thereby accurately converting the pixel point coordinates corresponding to the image into geographical coordinates.

[0023] Further, the first conversion relationship comprises a second conversion relationship between the pixel point coordinates and the image physical coordinates, a third conversion relationship between the image physical coordinates and the camera coordinates, a fourth conversion relationship between the pod camera coordinates and the pod gimbal coordinates, a fifth conversion relationship between the pod gimbal coordinates and the unmanned aerial vehicle body coordinates, a sixth conversion relationship between the unmanned aerial vehicle body coordinates and the north-east ground coordinates, a seventh conversion relationship between the north-east ground coordinates and the north-east sky coordinates, and an eighth conversion relationship between the north-east sky coordinates and the geographical coordinates.

[0024] For each of the images, the conversion of the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters comprises:

[0025] the conversion of the pixel point coordinates corresponding to the target to be positioned in the image into image physical coordinates through the second conversion relationship according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters;

[0026] the conversion of the image physical coordinates into pod camera coordinates through the third conversion relationship according to the image physical coordinates corresponding to the target to be positioned;

[0027] According to the gondola camera coordinates, the gondola camera coordinates are converted into gondola gimbal coordinates through the fourth conversion relationship;

[0028] According to the gondola gimbal coordinates, the gondola gimbal coordinates are converted into unmanned aerial vehicle body coordinates through the fifth conversion relationship;

[0029] According to the unmanned aerial vehicle body coordinates, the unmanned aerial vehicle body coordinates are converted into north-east-land coordinates through the sixth conversion relationship;

[0030] According to the north-east-land coordinates, the north-east-land coordinates are converted into east-north-sky coordinates through the seventh conversion relationship;

[0031] According to the east-north-sky coordinates, the east-north-sky coordinates are converted into geographic coordinates through the eighth conversion relationship.

[0032] The beneficial effect of the above further scheme is that through the above seven conversion relationships, the pixel point coordinates can be accurately converted into geographic coordinates.

[0033] Further, the above determining the positioning result of the target to be positioned according to the real altitude and the predicted altitude corresponding to the target to be positioned comprises:

[0034] calculating the height difference between the real altitude and the predicted altitude corresponding to the target to be positioned;

[0035] if the height difference is less than a threshold value, determining the positioning result of the target to be positioned according to the real altitude and the digital elevation model;

[0036] if the height difference is not less than the threshold value, determining a new predicted altitude according to a set altitude step and the predicted altitude, and determining a new height difference according to the new predicted altitude and the real altitude, until the new height difference is less than the threshold value.

[0037] The beneficial effect of the above further scheme is that through the continuous iteration of the set altitude step, the accuracy of the positioning result can be improved.

[0038] Further, the above second conversion relationship is represented by a first formula, and the above converting the pixel point coordinates of the target to be positioned in the image into physical coordinates through the second conversion relationship according to the gondola parameters and the unmanned aerial vehicle parameters corresponding to the image comprises:

[0039] converting the pixel point coordinates of the target to be positioned in the image into physical coordinates through the first formula according to the gondola parameters and the unmanned aerial vehicle parameters corresponding to the image, wherein the first formula is:

[0040]

[0041]

[0042] wherein (u, v) is a pixel point coordinate, (x, y) is a physical coordinate, c x , c y is a physical coordinate origin position relative to a pixel coordinate, dx, dy is a physical coordinate size corresponding to a unit pixel.

[0043] The beneficial effect of adopting the further scheme is that the second conversion relationship can be accurately expressed by the first formula, and the pixel point coordinate corresponding to the image can be accurately converted into the physical coordinate.

[0044] Further, the third conversion relationship is expressed by the second formula, and the physical coordinate corresponding to the target to be positioned in the image is converted into the pod camera coordinate through the third conversion relationship, comprising:

[0045] The physical coordinate corresponding to the image is converted into the pod camera coordinate through the second formula, wherein the second formula is:

[0046]

[0047] wherein p c (x c , y c , z c ) represents the pod camera coordinate, f x , f y , c x , c y is a parameter determined by the camera internal parameter, and p′c represents the vector of p c .

[0048] The beneficial effect of adopting the further scheme is that the third conversion relationship can be accurately expressed by the second formula, and the physical coordinate corresponding to the pod parameter can be accurately converted into the pod camera coordinate.

[0049] In a second aspect, the present application also provides a target positioning device based on a digital elevation model, comprising:

[0050] A full dynamic video acquisition module is configured to acquire a full dynamic video for a target to be positioned, wherein the full dynamic video is determined based on data collected by a pod-carrying unmanned aerial vehicle for the target to be positioned, and the data includes images and pod parameters and unmanned aerial vehicle parameters corresponding to each image, wherein for each image, the pod parameters include a pod attitude and pod camera sensor information, and the unmanned aerial vehicle parameters include an unmanned aerial vehicle attitude and latitude and longitude information.

[0051] a coordinate conversion module, configured to obtain images in each frame of the full dynamic video, and convert pixel point coordinates corresponding to a target to be located in each image into geographic coordinates according to parameters of the pod corresponding to the image and parameters of the unmanned aerial vehicle;

[0052] an altitude determination module, configured to determine a predicted altitude corresponding to the target to be located according to the geographic coordinates corresponding to the target to be located in each image, and determine a real altitude corresponding to the target to be located according to the geographic coordinates corresponding to the target to be located in each image and a preset digital elevation model, the digital elevation model including longitude, latitude and altitude of each point;

[0053] a positioning module, configured to determine a positioning result of the target to be located according to the real altitude and the predicted altitude corresponding to the target to be located.

[0054] In a third aspect, the present application provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the target positioning method based on a digital elevation model when executing the computer program.

[0055] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the target positioning method based on a digital elevation model.

[0056] Additional aspects and advantages of the present application will be made apparent by the following description. BRIEF DESCRIPTION OF DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced.

[0058] Figure 1 A flowchart of the target positioning method based on a digital elevation model provided by an embodiment of the present application;

[0059] Figure 2 A schematic diagram of a conversion relationship between pixel point coordinates and geographic coordinates provided by an embodiment of the present application;

[0060] Figure 3 A schematic diagram of a digital elevation model provided by an embodiment of the present application;

[0061] Figure 4A structural schematic diagram of a target positioning device based on a digital elevation model provided by an embodiment of the present application is shown in the figure.

[0062] Figure 5 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0063] The principles and features of the present application are described below, and the examples are only used to explain the present application and are not intended to limit the scope of the present application.

[0064] The technical solutions of the present application and how the technical solutions solve the above technical problems are described in detail below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0065] The scheme provided by the embodiments of the present application can be applied to any application scenario that needs to position a target. The scheme provided by the embodiments of the present application can be executed by an electronic device, such as a terminal device of a user, including at least one of the following: a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart television, and a smart vehicle-mounted device.

[0066] The embodiments of the present application provide a possible implementation manner, as shown in the figure. Figure 1 A flowchart of a target positioning method based on a digital elevation model is provided, which can be executed by any electronic device, for example, a terminal device, or jointly executed by a terminal device and a server. For the sake of description, the method provided by the embodiments of the present application will be described below taking the terminal device as an execution subject, as shown in the flowchart in the figure. The method can include the following steps: Figure 1

[0067] In step S110, a full dynamic video for a target to be positioned is acquired, the full dynamic video being determined based on data collected by a gimbal-carrying unmanned aerial vehicle for the target to be positioned, the data including frames of images and gimbal parameters and unmanned aerial vehicle parameters corresponding to each frame of image, for each frame of image, the gimbal parameters including a gimbal attitude and gimbal camera sensor information, and the unmanned aerial vehicle parameters including unmanned aerial vehicle attitude and latitude and longitude information;

[0068] In step S120, each frame of image in the full dynamic video is acquired, and for each frame of image, pixel point coordinates corresponding to a target to be positioned in the image are converted into geographic coordinates according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image.

[0069] ​Step S130, determining the real altitude corresponding to the target to be positioned, determining the predicted altitude corresponding to the target to be positioned according to the geographical coordinates of the target to be positioned in each frame of the image, and according to the geographical coordinates of the target to be positioned in each frame of the image and a preset digital elevation model, wherein the digital elevation model includes the longitude, latitude and altitude of each point.

[0070] Step S140, determining the positioning result of the target to be positioned according to the real altitude and the predicted altitude corresponding to the target to be positioned.

[0071] In view of the problems of poor positioning accuracy and poor effectiveness of the existing target positioning algorithm, in the scheme of the present application, by incorporating a digital elevation model, by comparing the predicted altitude and the real altitude, the position of the target to be positioned, i.e. the positioning result, can be accurately and quickly determined. In the case of possessing prior information of the digital elevation model data, the influence of complex terrain on the positioning algorithm is reduced, and the scheme has the characteristics of high positioning accuracy and strong real-time performance.

[0072] The scheme of the present application will be further described below in combination with the following specific embodiments. In the embodiments, the target positioning method based on a digital elevation model can include the following steps:

[0073] Step S110, acquiring a full dynamic video for a target to be positioned, wherein the full dynamic video is determined based on data collected by a gimbal-equipped unmanned aerial vehicle for the target to be positioned, and the data includes frames of images and gimbal parameters and unmanned aerial vehicle parameters corresponding to each frame of the images. For each frame of image, the gimbal parameters include gimbal attitude and gimbal camera sensor information, and the unmanned aerial vehicle parameters include unmanned aerial vehicle attitude and latitude and longitude information.

[0074] Optionally, before step S110, the method can further include:

[0075] collecting frames of images, gimbal parameters and unmanned aerial vehicle parameters of a target to be positioned region by a gimbal-equipped unmanned aerial vehicle;

[0076] encoding each frame of the images and the gimbal parameters and the unmanned aerial vehicle parameters corresponding to each frame of the images to obtain a full dynamic video.

[0077] The gimbal attitude reflects three angles of pitch, yaw and roll of the image. The gimbal sensor data reflects the field of view size of the image. The unmanned aerial vehicle attitude also reflects the pitch, yaw and roll angles of the gimbal; and the latitude and longitude of the unmanned aerial vehicle reflect the geographical position of the image.

[0078] The encoding of each frame of the image and the corresponding pod parameters and unmanned aerial vehicle parameters of each frame of the image can specifically refer to packing each frame of image in a set format according to the acquisition order of each frame of the image. In the scheme, the unmanned aerial vehicle on-board processor can use a video fusion algorithm to encode the unmanned aerial vehicle parameters and the pod parameters to obtain a full dynamic video, and then send the full dynamic video to the ground terminal server. After obtaining the full dynamic video, the ground terminal server decodes the full dynamic video to obtain each frame of the image in the full dynamic video and the corresponding pod parameters and unmanned aerial vehicle parameters of each frame of the image.

[0079] In step S120, each frame of the image in the full dynamic video is obtained, and for each frame of the image, the pixel point coordinates corresponding to the target to be positioned in the image are converted into geographical coordinates according to the corresponding pod parameters and the unmanned aerial vehicle parameters of the image.

[0080] The unmanned aerial vehicle parameters and the pod parameters reflect the image attitude and position, and the positioning of the target to be positioned is to obtain the positioning result of the target to be positioned in the geographical coordinate system. Therefore, the target pixel coordinates corresponding to the target to be positioned in the image coordinate system are converted into geographical coordinates in the geographical coordinate system, so that the target to be positioned can be accurately positioned.

[0081] In one frame of image, there can be one or more targets, for example, the target to be positioned is a vehicle, the pixel of the frame of image is 1920*1080, and the position (pixel coordinates) of the target to be positioned in the image is (797, 680). Finally, the real geographical coordinates corresponding to the pixel coordinates need to be solved.

[0082] Optionally, the method further comprises:

[0083] Obtaining a plurality of pixel point coordinates and geographical coordinates corresponding to each of the pixel point coordinates;

[0084] Determining a first conversion relationship between the pixel point coordinates and the geographical coordinates through a perspective model; and converting the pixel point coordinates and the geographical coordinates through the first conversion relationship.

[0085] For each frame of the image, the conversion of the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates according to the corresponding pod parameters and the unmanned aerial vehicle parameters of the image comprises:

[0086] Converting the pixel point coordinates corresponding to the target to be positioned in the image into geographical coordinates through the first conversion relationship according to the corresponding pod parameters and the unmanned aerial vehicle parameters of the image.

[0087] Optionally, the first conversion relationship includes a second conversion relationship between the pixel point coordinates and the image physical coordinates, a third conversion relationship between the image physical coordinates and the camera coordinates, a fourth conversion relationship between the pod camera coordinates and the pod gimbal coordinates, a fifth conversion relationship between the pod gimbal coordinates and the UAV body coordinates, a sixth conversion relationship between the UAV body coordinates and the NEU ground coordinates, a seventh conversion relationship between the NEU ground coordinates and the NEU sky coordinates, and an eighth conversion relationship between the NEU sky coordinates and the geographic coordinates.

[0088] Then, for each frame of the image, the pixel point coordinates corresponding to the target to be positioned in the image are converted into the geographic coordinates according to the image corresponding and the UAV parameters through the first conversion relationship, including:

[0089] S21, according to the pod parameters corresponding to the image and the UAV parameters, the pixel point coordinates corresponding to the target to be positioned in the image are converted into the image physical coordinates through the second conversion relationship.

[0090] Optionally, the second conversion relationship can be represented by a first formula, and the pixel point coordinates corresponding to the target to be positioned in the image are converted into the image physical coordinates according to the pod parameters corresponding to the image and the UAV parameters through the second conversion relationship, including:

[0091] According to the pod parameters corresponding to the image and the UAV parameters, the pixel point coordinates corresponding to the target to be positioned in the image are converted into the image physical coordinates through the first formula, wherein the first formula is:

[0092]

[0093]

[0094] Wherein, (u, v) is the pixel point coordinates, (x, y) is the image physical coordinates, c x , c y is the origin position of the image physical coordinates relative to the pixel coordinates, dx and dy are the image physical coordinates corresponding to the size of the unit pixel, and the unit is mm / pixel.

[0095] Wherein, the conversion relationship between the pixel point coordinates and the image physical coordinates can be referred to Figure 2, pixel coordinate system (pixel point coordinate system) and like physical coordinate system (like physical coordinates in the coordinate system) are on the imaging plane. The pixel point coordinates (u, v) of each frame of image are converted into like physical coordinates (x, y); wherein, the pixel coordinate system and the like physical coordinate system are on the imaging plane, only the origins and the measurement units are different. The origin of the pixel coordinate system is the intersection of the camera optical axis and the imaging plane, which is usually the midpoint of the imaging plane or the principal point. The unit of the like physical coordinate system is mm, which belongs to the physical unit, while the unit of the pixel coordinate system is pixel. We usually describe a pixel point as several rows and several columns.

[0096] S22, according to the like physical coordinates corresponding to the target to be positioned in the image, the like physical coordinates are converted into pod camera coordinates (coordinates in the camera coordinate system) through the third conversion relationship;

[0097] Optionally, the third conversion relationship is represented by a second formula, and the conversion of the like physical coordinates into the pod camera coordinates according to the like physical coordinates corresponding to the target to be positioned in the image through the third conversion relationship comprises:

[0098] The like physical coordinates corresponding to the image are converted into the pod camera coordinates through the second formula, wherein the second formula is:

[0099]

[0100] Wherein, p c (x c , y c , z c ) represents the pod camera coordinates, f x , f y , c x , c y are parameters determined by the camera intrinsic parameters, and p′ c represents the vector of p c .

[0101] S23, according to the pod camera coordinates, the pod camera coordinates are converted into the pod gimbal coordinates through the fourth conversion relationship;

[0102] Optionally, the fourth conversion relationship can be represented by a third formula, and the fourth conversion relationship comprises a conversion matrix R C→G between the pod camera coordinates and the pod gimbal coordinates, and a translation vector T C→G from the pod camera coordinate system to the pod gimbal coordinate system, and the conversion of the pod camera coordinates into the pod gimbal coordinates according to the pod camera coordinates through the fourth conversion relationship comprises:

[0103] According to the gondola camera coordinates, the gondola camera coordinates are converted into gondola gimbal coordinates by the third formula, wherein the third formula is:

[0104] P′ G = R C→G P′ C + T C→G

[0105] wherein P′ G (x G , y G , z G ), that is, P′ G represents the gondola gimbal coordinates, and p′ c represents a vector corresponding to the gondola camera coordinates.

[0106] S24, according to the gondola gimbal coordinates, the gondola gimbal coordinates are converted into unmanned aerial vehicle body coordinates by the fifth conversion relationship;

[0107] Because the gondola is carried on the unmanned aerial vehicle, the gondola gimbal coordinates can be converted into unmanned aerial vehicle body coordinates.

[0108] Optionally, the fifth conversion relationship can be represented by a fourth formula, and the fifth conversion relationship includes a conversion matrix R C→UAS between the gondola gimbal coordinates and the unmanned aerial vehicle body coordinates and a translation vector T G→UAS from the gondola gimbal coordinates to the unmanned aerial vehicle body coordinates, so that the gondola gimbal coordinates are converted into the unmanned aerial vehicle body coordinates according to the gondola gimbal coordinates by the fifth conversion relationship, including:

[0109] According to the gondola gimbal coordinates, the gondola gimbal coordinates are converted into unmanned aerial vehicle body coordinates by the fourth formula, wherein the fourth formula is:

[0110] P′ UAS = R C→UAS R C→G P′ C + R C→UAS T C→G + T G→UAS

[0111] wherein P′ UAS (x UAS , y UAS , z UAS ), that is, P′ UAS represents the unmanned aerial vehicle body coordinates. The P′ C can be represented by the gondola gimbal coordinates.

[0112] S25, converting the UAV body coordinates into North-East-Geodetic coordinates according to the sixth conversion relationship;

[0113] Optionally, the sixth conversion relationship can be represented by a fifth formula, and the sixth conversion relationship includes a conversion matrix R UAS→NED and a translation vector T UAS→NED from the UAV body coordinates to the North-East-Geodetic coordinates.

[0114] According to the UAV body coordinates, the UAV body coordinates are converted into North-East-Geodetic coordinates by the fifth formula, wherein the fifth formula is:

[0115] P′ NED = R UAS→NED P′ UAS + T UAS→NED

[0116] wherein P′ NED (x NED , y NED , z NED ), that is, P′ NED represents the North-East-Geodetic coordinates.

[0117] S26, converting the North-East-Geodetic coordinates into North-East-Sky coordinates according to the seventh conversion relationship;

[0118] Optionally, the seventh conversion relationship can be represented by a sixth formula, and the seventh conversion relationship includes a conversion matrix R NED→ENU and a translation vector T NED→ENU from the North-East-Geodetic coordinates to the North-East-Sky coordinates.

[0119] According to the North-East-Geodetic coordinates, the North-East-Geodetic coordinates are converted into North-East-Sky coordinates by the sixth formula, wherein the sixth formula is:

[0120] P′ ENU = R NED→ENU P′ NED + T NED→ENU

[0121] wherein P′ ENU (x ENU , y ENU , z ENU ), that is, P′ ENUThe northeast celestial coordinate represents the east-north-up coordinate system.

[0122] S27, converting the northeast celestial coordinate into a geographic coordinate according to the eighth conversion relationship.

[0123] Optionally, the eighth conversion relationship can be represented by a seventh formula, and the eighth conversion relationship includes a translation vector T of the gondola coordinate to the northeast celestial coordinate C→ENU , and z C , the eighth conversion relationship includes:

[0124] According to the seventh formula, the northeast celestial coordinate is converted into a geographic coordinate P ENU , wherein the seventh formula is:

[0125] P ENU = z C P ′ENU -z C T C→ENU + T C→ENU

[0126] Step S130, determining the predicted altitude of the target to be positioned according to the geographic coordinates of the target to be positioned in each frame of the image, and determining the true altitude of the target to be positioned according to the geographic coordinates of the target to be positioned in each frame of the image and a preset digital elevation model, wherein the digital elevation model includes the longitude, latitude and altitude of each point.

[0127] The digital elevation model can be determined in advance according to the longitude, latitude and altitude information of each position in the region where the target to be positioned is located, i.e., each position in the region where the target to be positioned is located is represented by three values (longitude, latitude, altitude). For details, refer to the digital elevation model diagram shown in FIG. 8. Figure 3 Figure 3 Each grid represents the altitude of the point, and different colors represent different altitudes, with the altitude decreasing from black to white. If the altitude of the region where the target to be positioned is located is consistent with the altitude of the takeoff point, i.e., z ENU = 0, P ENU is a point with a relative height of 0. Considering the actual scenario, the terrain has ups and downs, and the relative height of the target to be positioned is not 0.

[0128] Step S140, determining the positioning result of the target to be positioned according to the true altitude and the predicted altitude of the target to be positioned.

[0129] ​Optionally, the determining the positioning result of the target to be positioned according to the real altitude and the predicted altitude corresponding to the target to be positioned comprises:

[0130] calculating a height difference value ΔP between the real altitude and the predicted altitude corresponding to the target to be positioned; z for the predicted altitude z ENU and the real altitude z DENU determined according to the digital elevation model.

[0131] if the height difference value ΔP Z is less than a threshold value ΔP Zmin , determining the positioning result of the target to be positioned according to the real altitude and the digital elevation model;

[0132] if the height difference value ΔP Z is not less than the threshold value ΔP Zmin , determining a new predicted altitude according to a set altitude step and the predicted altitude, generally the new predicted altitude is equal to the sum of the set altitude step and the predicted altitude, then determining a new height difference value according to the new predicted altitude and the real altitude, comparing the new height difference value with the threshold value, until the new height difference value is less than the threshold value, the positioning result P of the target to be positioned can be determined DENU , generally the positioning result can be represented by longitude and latitude.

[0133] Through the scheme of the present application, aiming at the problems of poor positioning accuracy and poor effectiveness of the existing target positioning algorithm, by integrating the digital elevation model, based on the change of the perspective model and the variable step iteration algorithm to improve the positioning accuracy, in the case of possessing prior information digital elevation model data, the influence of complex terrain on the positioning algorithm is reduced, and the present application has the characteristics of high positioning accuracy and strong real-time performance;

[0134] Aiming at the problem of space-time mismatch of input data of the target positioning algorithm, through the space-time synchronous data processing of the unmanned aerial vehicle parameters and the nacelle parameters by the unmanned aerial vehicle on-board video fusion algorithm, the high space-time synchronization of the input data of the target positioning algorithm is ensured.

[0135] Based on the same principle as the method shown in Figure 1 , the present application also provides a target positioning device 20 based on a digital elevation model, as shown in Figure 4 , the target positioning device 20 based on the digital elevation model can comprise a full dynamic video acquisition module 210, a coordinate conversion module 220, an altitude determination module 230 and a positioning module 240, wherein:

[0136] The full-dynamic video acquisition module 210 is configured to acquire a full-dynamic video of a target to be positioned, wherein the full-dynamic video is determined based on data collected by a gimbal-carrying unmanned aerial vehicle on the target to be positioned, and the data includes images and gimbal parameters and unmanned aerial vehicle parameters corresponding to each image, wherein for each image, the gimbal parameters include a gimbal attitude and gimbal camera sensor information, and the unmanned aerial vehicle parameters include an unmanned aerial vehicle attitude and latitude and longitude information.

[0137] The coordinate conversion module 220 is configured to acquire each image in the full-dynamic video, and for each image, convert pixel point coordinates corresponding to a target to be positioned in the image into geographic coordinates according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image.

[0138] The altitude determination module 230 is configured to determine a predicted altitude corresponding to the target to be positioned according to the geographic coordinates corresponding to the target to be positioned in each image, and determine a true altitude corresponding to the target to be positioned according to the geographic coordinates corresponding to the target to be positioned in each image and a preset digital elevation model, wherein the digital elevation model includes longitude, latitude and altitude of each point.

[0139] The positioning module 240 is configured to determine a positioning result of the target to be positioned according to the true altitude and the predicted altitude corresponding to the target to be positioned.

[0140] Optionally, the apparatus further includes:

[0141] The full-dynamic video determination module is configured to collect each image, gimbal parameters and unmanned aerial vehicle parameters of a target to be positioned region by a gimbal-carrying unmanned aerial vehicle, and encode each image and the gimbal parameters and the unmanned aerial vehicle parameters corresponding to each image to obtain a full-dynamic video.

[0142] Optionally, the apparatus further includes:

[0143] The first conversion relationship determination module is configured to acquire a plurality of pixel point coordinates and geographic coordinates corresponding to each pixel point coordinate, and determine a first conversion relationship between pixel point coordinates and geographic coordinates through a perspective model conversion according to each pixel point coordinate and each geographic coordinate.

[0144] For each image, the coordinate conversion module 220 is specifically configured to, when converting pixel point coordinates corresponding to a target to be positioned in the image into geographic coordinates according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image:

[0145] According to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image, convert the pixel point coordinates corresponding to the target to be positioned in the image into geographic coordinates through the first conversion relationship.

[0146] Optionally, the first conversion relationship includes a second conversion relationship between the pixel point coordinates and the image physical coordinates, a third conversion relationship between the image physical coordinates and the camera coordinates, a fourth conversion relationship between the gondola camera coordinates and the gondola gimbal coordinates, a fifth conversion relationship between the gondola gimbal coordinates and the unmanned aerial vehicle body coordinates, a sixth conversion relationship between the unmanned aerial vehicle body coordinates and the north-east ground coordinates, a seventh conversion relationship between the north-east ground coordinates and the north-east sky coordinates, and an eighth conversion relationship between the north-east sky coordinates and the geographic coordinates.

[0147] For each frame of the image, when the coordinate conversion module 220 converts the pixel point coordinates corresponding to the target to be positioned in the image into the geographic coordinates according to the first conversion relationship based on the image corresponding parameters and the unmanned aerial vehicle parameters, the coordinate conversion module 220 is specifically configured to:

[0148] convert the pixel point coordinates corresponding to the target to be positioned in the image into the image physical coordinates according to the second conversion relationship based on the image corresponding gondola parameters and the unmanned aerial vehicle parameters;

[0149] convert the image physical coordinates into the gondola camera coordinates according to the third conversion relationship based on the image physical coordinates corresponding to the target to be positioned;

[0150] convert the gondola camera coordinates into the gondola gimbal coordinates according to the fourth conversion relationship based on the gondola camera coordinates;

[0151] convert the gondola gimbal coordinates into the unmanned aerial vehicle body coordinates according to the fifth conversion relationship based on the gondola gimbal coordinates;

[0152] convert the unmanned aerial vehicle body coordinates into the north-east ground coordinates according to the sixth conversion relationship based on the unmanned aerial vehicle body coordinates;

[0153] convert the north-east ground coordinates into the north-east sky coordinates according to the seventh conversion relationship based on the north-east ground coordinates;

[0154] convert the north-east sky coordinates into the geographic coordinates according to the eighth conversion relationship based on the north-east sky coordinates.

[0155] Optionally, when the positioning module 240 determines the positioning result of the target to be positioned according to the real altitude corresponding to the target to be positioned and the predicted altitude, the positioning module 240 is specifically configured to:

[0156] calculate a height difference value between the real altitude corresponding to the target to be positioned and the predicted altitude;

[0157] if the height difference value is less than a threshold value, determine the positioning result of the target to be positioned according to the real altitude and the digital elevation model;

[0158] If the height difference value is not less than the threshold value, a new predicted altitude is determined according to a set altitude step and the predicted altitude, and a new height difference value is determined according to the new predicted altitude and the real altitude, until the new height difference value is less than the threshold value.

[0159] Optionally, the second conversion relationship is represented by a first formula, and when the coordinate conversion module 220 converts the pixel point coordinates corresponding to the target to be positioned in the image into physical coordinates according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters through the second conversion relationship, is specifically used for:

[0160] The pixel point coordinates corresponding to the target to be positioned in the image are converted into physical coordinates according to the pod parameters corresponding to the image and the unmanned aerial vehicle parameters through the first formula, wherein the first formula is:

[0161]

[0162]

[0163] wherein (u, v) is the pixel point coordinates, (x, y) is the physical coordinates, c x , c y is the origin position of the physical coordinates relative to the pixel coordinates, dx and dy are the physical coordinates corresponding to the unit pixel size respectively.

[0164] Optionally, the third conversion relationship is represented by a second formula, and when the coordinate conversion module 220 converts the physical coordinates corresponding to the target to be positioned in the image into pod camera coordinates according to the physical coordinates corresponding to the target to be positioned in the image through the third conversion relationship, is specifically used for:

[0165] The physical coordinates corresponding to the target to be positioned in the image are converted into pod camera coordinates according to the physical coordinates corresponding to the target to be positioned in the image through the second formula, wherein the second formula is:

[0166]

[0167] wherein p c (x c , y c , z c ) represents the pod camera coordinates, f x , f y , c x , c y are parameters determined by camera intrinsic parameters, and p′ c represents the vector of p c .

[0168] The target positioning apparatus based on a digital elevation model can execute the target positioning method based on a digital elevation model provided by the embodiments of the present application, and the implementation principles are similar. The actions performed by each module and unit in the target positioning apparatus based on a digital elevation model in the embodiments of the present application correspond to the steps in the target positioning method based on a digital elevation model in the embodiments of the present application. For the detailed functions of each module of the target positioning apparatus based on a digital elevation model, refer to the description of the corresponding target positioning method based on a digital elevation model provided in the foregoing, which will not be repeated here.

[0169] The target positioning apparatus based on a digital elevation model can be a computer program (including program code) running in a computer device, for example, the target positioning apparatus based on a digital elevation model is an application software. The apparatus can be used to execute the corresponding steps in the method provided by the embodiments of the present application.

[0170] In some embodiments, the target positioning apparatus based on a digital elevation model provided by the embodiments of the present application can be implemented in a combination of software and hardware. For example, the target positioning apparatus based on a digital elevation model provided by the embodiments of the present application can be a processor in the form of a hardware decoding processor, which is programmed to execute the target positioning method based on a digital elevation model provided by the embodiments of the present application. For example, the processor in the form of a hardware decoding processor can use one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic elements.

[0171] In some other embodiments, the target positioning apparatus based on a digital elevation model provided by the embodiments of the present application can be implemented in software, Figure 4 The target positioning apparatus based on a digital elevation model stored in the memory is shown, which can be software in the form of programs and plug-ins, and includes a series of modules, including a full dynamic video acquisition module 210, a coordinate conversion module 220, an elevation determination module 230, and a positioning module 240, for implementing the target positioning method based on a digital elevation model provided by the embodiments of the present application.

[0172] The modules described in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the names of the modules do not constitute a limitation on the modules themselves.

[0173] Based on the same principles as the method shown in the embodiments of the present application, the embodiments of the present application also provide an electronic device, which can include but is not limited to a processor and a memory; the memory is configured to store a computer program; and the processor is configured to execute the method shown in any of the embodiments of the present application by invoking the computer program.

[0174] In an optional embodiment, an electronic device is provided, which can include but is not limited to a processor and a memory; the memory is configured to store a computer program; and the processor is configured to execute the method shown in any of the embodiments of the present application by invoking the computer program. Figure 5 As shown in the figure, Figure 5 The electronic device 4000 shown in the figure includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, through a bus 4002. Optionally, the electronic device 4000 can also include a transceiver 4004, which can be used for data interaction, such as data transmission and / or data reception, between the electronic device and other electronic devices. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present application.

[0175] The processor 4001 can be a CPU (Central Processing Unit, central processing unit), a general-purpose processor, a DSP (Digital Signal Processor, digital signal processor), an ASIC (Application Specific Integrated Circuit, application specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure. The processor 4001 can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0176] The bus 4002 can include a channel for transmitting information between the above-mentioned components. The bus 4002 can be a PCI (Peripheral Component Interconnect, peripheral component interconnect) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience,Figure 5 Only one bus or type of bus might exist but implementations that have more than one bus or type of bus are possible.

[0177] The memory 4003 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions that are not to be changed by the computer; a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions for execution by the processor 4001 and / or the computer; an EEPROM (Electrically Erasable Programmable Read-Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disk storage; a magnetic disk storage or other magnetic storage devices or any other non-transitory medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer; and the like, but is not limited thereto.

[0178] The memory 4003 is used to store application code (computer program) for implementing the scheme of the present application, and is controlled by the processor 4001 to execute. The processor 4001 is used to execute the application code stored in the memory 4003 to realize the content shown in the foregoing method embodiments.

[0179] The electronic device can also be a terminal device, Figure 5 The electronic device shown is only an example and should not limit the functions and use range of the embodiments of the present application.

[0180] The computer readable storage medium provided by the embodiments of the present application has computer program stored thereon, when the computer program runs on the computer, the computer can execute the corresponding content in the foregoing method embodiments.

[0181] According to another aspect of the present application, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes the target positioning method based on the digital elevation model provided in the various implementation manners of the above embodiments.

[0182] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0183] It should be understood that the flowchart and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of various embodiments of the present application. In this regard, each block in the flowchart and block diagrams can represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or combinations of hardware and software.

[0184] The computer readable storage medium of the present application embodiment can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program and / or data used by an instruction execution system, apparatus, or device to create a machine.

[0185] The computer readable storage medium described above bears one or more programs, when the one or more programs are executed by the electronic device, cause the electronic device to execute the method shown in the above embodiment.

[0186] The above description is merely the preferred embodiments of the present application and the explanation of the applied technical principles. It should be understood by those skilled in the art that the disclosed range of the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combinations of the above technical features or their equivalent features without departing from the disclosed concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features disclosed in the present application (but not limited to) having similar functions.

Claims

1. A method for target location based on digital elevation model, characterized in that, The method comprises the following steps: acquiring full dynamic video for a target to be positioned, the full dynamic video being determined based on data collected by a gimbal-carrying unmanned aerial vehicle for the target to be positioned, the data comprising frames of images and gimbal parameters and unmanned aerial vehicle parameters corresponding to the frames of images, for each frame of image, the gimbal parameters comprising a gimbal attitude and gimbal camera sensor information, the unmanned aerial vehicle parameters comprising an unmanned aerial vehicle attitude and latitude and longitude information, the gimbal attitude reflecting pitch, yaw and roll angles of the image, the unmanned aerial vehicle attitude reflecting pitch, yaw and roll angles of the gimbal; for each frame of image, converting pixel point coordinates corresponding to the target to be positioned in the image into geographic coordinates according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image; determining a predicted altitude of the target to be positioned according to the geographic coordinates of the target to be positioned in each frame of image, and determining a true altitude of the target to be positioned according to the geographic coordinates of the target to be positioned in each frame of image and a preset digital elevation model, the digital elevation model comprising longitude, latitude and altitude of each point; determining a positioning result of the target to be positioned according to the true altitude and the predicted altitude of the target to be positioned.

2. The method of claim 1, wherein, The method further comprises: collecting, by the gimbal-carrying unmanned aerial vehicle, frames of images, gimbal parameters and unmanned aerial vehicle parameters of the target to be positioned region; encoding the frames of images and the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the frames of images to obtain the full dynamic video.

3. The method of claim 1, wherein, The method further comprises: acquiring a plurality of pixel point coordinates and geographic coordinates corresponding to each of the pixel point coordinates; determining a first conversion relationship between pixel point coordinates and geographic coordinates through a perspective model conversion according to each of the pixel point coordinates and each of the geographic coordinates; for each frame of image, the converting, according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image, of pixel point coordinates corresponding to the target to be positioned in the image into geographic coordinates, comprises: converting, according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image, the pixel point coordinates corresponding to the target to be positioned in the image into geographic coordinates through the first conversion relationship.

4. The method of claim 3, wherein, The first conversion relationship comprises a second conversion relationship between pixel point coordinates and image physical coordinates, a third conversion relationship between image physical coordinates and camera coordinates, a fourth conversion relationship between gimbal camera coordinates and gimbal gimbal coordinates, a fifth conversion relationship between gimbal gimbal coordinates and unmanned aerial vehicle body coordinates, a sixth conversion relationship between unmanned aerial vehicle body coordinates and north-east ground coordinates, a seventh conversion relationship between north-east ground coordinates and north-east sky coordinates, and an eighth conversion relationship between north-east sky coordinates and geographic coordinates; for each frame of image, the converting, according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image, of pixel point coordinates corresponding to the target to be positioned in the image into geographic coordinates through the first conversion relationship, comprises: converting, according to the gimbal parameters and the unmanned aerial vehicle parameters corresponding to the image, the pixel point coordinates corresponding to the target to be positioned in the image into image physical coordinates through the second conversion relationship; According to the image corresponding to the physical coordinates of the target to be positioned, the third conversion relationship is used to convert the physical coordinates into pod camera coordinates; According to the pod camera coordinates, the fourth conversion relationship is used to convert the pod camera coordinates into pod gimbal coordinates; According to the pod gimbal coordinates, the fifth conversion relationship is used to convert the pod gimbal coordinates into unmanned aerial vehicle body coordinates; According to the unmanned aerial vehicle body coordinates, the sixth conversion relationship is used to convert the unmanned aerial vehicle body coordinates into north-east-ground coordinates; According to the north-east-ground coordinates, the seventh conversion relationship is used to convert the north-east-ground coordinates into north-east-sky coordinates; According to the north-east-sky coordinates, the eighth conversion relationship is used to convert the north-east-sky coordinates into geographical coordinates.

5. The method according to any one of claims 1 to 4, characterized in that, The method comprises the following steps: calculating the height difference between the real altitude corresponding to the target to be positioned and the predicted altitude; if the height difference is less than a threshold value, determining the positioning result of the target to be positioned according to the real altitude and the digital elevation model; if the height difference is not less than the threshold value, determining a new predicted altitude according to a set altitude step and the predicted altitude, and determining a new height difference according to the new predicted altitude and the real altitude, until the new height difference is less than the threshold value.

6. The method of claim 4, wherein, The second conversion relationship is represented by a first formula, and the method comprises the following steps: according to the pod parameters and the unmanned aerial vehicle parameters corresponding to the image, the first formula is used to convert the pixel point coordinates corresponding to the target to be positioned in the image into physical coordinates, wherein the first formula is: where (u, v) is the pixel point coordinate, (x, y) is the image physical coordinate, c x , c y is the origin position of the image physical coordinate relative to the pixel coordinate, and dx, dy are the image physical coordinate sizes corresponding to a unit pixel, respectively.

7. The method of claim 6, wherein, The third conversion relationship is represented by a second formula, and the method comprises the following steps: according to the physical coordinates of the target to be positioned in the image, the second formula is used to convert the physical coordinates into pod camera coordinates, wherein the second formula is: where p c (x c , y c , z c ) represents the gondola camera coordinates, f x , f y , c x , c y are parameters determined by camera intrinsics, and p c ' represents the vector of p c .

8. A digital elevation model based target location device, characterized by The device comprises: a full-dynamic video acquisition module, which is used to acquire a full-dynamic video of a target to be positioned, wherein the full-dynamic video is determined based on data collected by a pod-carrying unmanned aerial vehicle on the target to be positioned, and the data comprises images and pod parameters and unmanned aerial vehicle parameters corresponding to each image; for each image, the pod parameters comprise a pod attitude and pod camera sensor information, and the unmanned aerial vehicle parameters comprise an unmanned aerial vehicle attitude and latitude and longitude information; a coordinate conversion module, which is used to acquire each image in the full-dynamic video; for each image, the pixel point coordinates corresponding to the target to be positioned in the image are converted into geographical coordinates according to the pod parameters and the unmanned aerial vehicle parameters corresponding to the image. The altitude determination module is configured to determine a predicted altitude corresponding to the target to be positioned according to geographical coordinates corresponding to the target to be positioned in each frame of the images, and determine a real altitude corresponding to the target to be positioned according to the geographical coordinates corresponding to the target to be positioned in each frame of the images and a preset digital elevation model, wherein the digital elevation model comprises longitude, latitude and altitude of each point. The positioning module is configured to determine a positioning result of the target to be positioned according to the real altitude and the predicted altitude corresponding to the target to be positioned.

9. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1-7.

Images