KR102243649B1 - Unmanned aerial vehicle ad-hoc location estimation system in urban environment - Google Patents

Abstract

An unmanned aerial vehicle Ad-hoc position estimation system in an urban environment is disclosed. The method for estimating the location of the unmanned aerial vehicle according to an embodiment includes the steps of receiving first location information of a second unmanned aerial vehicle from a first unmanned aerial vehicle, and the first location information and the first location information of the second unmanned aerial vehicle. 2 estimating second location information of the second unmanned aerial vehicle based on an inertia value, wherein the first location information includes a Global Navigation Satellite System (GNSS) signal, and a first inertia value for the first unmanned aerial vehicle , And the first unmanned aerial vehicle is estimated based on image information of the second unmanned aerial vehicle photographed from above.

Description

Unmanned aerial vehicle ad-hoc location estimation system in urban environment {UNMANNED AERIAL VEHICLE AD-HOC LOCATION ESTIMATION SYSTEM IN URBAN ENVIRONMENT}

The following embodiments relate to an unmanned aerial vehicle Ad-hoc position estimation system in an urban environment.

Unmanned Aerial Vehicles, which are remotely controlled through wireless communication, were developed for military use and were used for simple shooting practice. In recent years, unmanned aerial vehicles have been expanded and spread not only to military use but also to various other fields according to the continuous development of electronic communication technology.

The unmanned aerial vehicle updates its location information by receiving signals from the Global Navigation Satellite System (GNSS), which is a satellite positioning system. However, if the GNSS signal received by the unmanned aerial vehicle is blocked by an obstacle such as an urban building or a building and cannot be received, the unmanned aerial vehicle cannot update its location information.

In this case, the unmanned aerial vehicle estimated the location by using a radio wave generating device such as a beacon installed at a fixed location, or by using image information captured by a camera installed at a fixed location of the unmanned aerial vehicle.

However, it is difficult to estimate the location of the unmanned aerial vehicle in an area where a device for location estimation is not fixedly installed in advance.

The embodiments provide a technology that allows the first unmanned aerial vehicle to flexibly provide data necessary for estimating the location of the second unmanned aerial vehicle in a communication shadowing area, thereby updating location information, etc. even when the unmanned aerial vehicle is in a communication shadowing area. Can provide.

The method for estimating the location of the unmanned aerial vehicle according to an embodiment includes the steps of receiving first location information of a second unmanned aerial vehicle from a first unmanned aerial vehicle, and the first location information and the first location information of the second unmanned aerial vehicle. 2 estimating second location information of the second unmanned aerial vehicle based on an inertia value, wherein the first location information includes a Global Navigation Satellite System (GNSS) signal, and a first inertia value for the first unmanned aerial vehicle , And the first unmanned aerial vehicle is estimated based on image information of the second unmanned aerial vehicle photographed from above.

The first location information may be estimated using the image information and a navigation solution generated based on the GNSS signal and the first inertia value.

The method includes receiving first speed information of the second unmanned aerial vehicle from the first unmanned aerial vehicle, and second speed information of the second unmanned aerial vehicle based on the first speed information and the second inertia value It may further include the step of generating.

The first speed information may be calculated based on the GNSS signal, the first inertia value, and the image information.

A method for estimating a location of an unmanned aerial vehicle according to another embodiment includes the steps of receiving a Global Navigation Satellite System (GNSS) signal and a first inertia value of a first unmanned aerial vehicle, the GNSS signal, and the first inertia. Estimating first location information of the first unmanned aerial vehicle based on a value, a second inertia value of the second unmanned aerial vehicle, and image information of the first unmanned aerial vehicle captured by the second unmanned aerial vehicle from above do.

The estimating may include estimating second position information of the first unmanned aerial vehicle based on the GNSS signal, the second inertia value, and the image information, and the second position information and the first inertia value It may include the step of estimating the first location information of the first unmanned aerial vehicle.

The step of estimating the second location information includes generating a navigation solution based on the GNSS signal and the second inertia value, and the second location information using the navigation solution and the image information. It may include the step of estimating.

The method includes calculating first speed information of the first unmanned aerial vehicle based on the GNSS signal, the second inertia value, and the image information, and based on the first speed information and the first inertia value. It may further include generating second speed information of the first unmanned aerial vehicle.

A method for estimating a location of a drone according to another embodiment is a method of estimating the location of a first unmanned aerial vehicle and a second unmanned aerial vehicle, the step of generating image information by photographing the second unmanned aerial vehicle, and a GNSS signal , The second unmanned aerial vehicle based on the first inertia value of the first unmanned aerial vehicle, the second inertial value of the second unmanned aerial vehicle, and the image information of the second unmanned aerial vehicle captured by the first unmanned aerial vehicle in the sky. And estimating the first location information of.

The estimating may include estimating second position information of the second unmanned aerial vehicle based on the GNSS signal, the first inertia value, and the image information, and the first position information and the second inertia value It may include the step of estimating the first location information of the second unmanned aerial vehicle.

The step of estimating the second location information includes generating a navigation solution based on the GNSS signal and the first inertia value, and the second location information using the navigation solution and the image information. It may include the step of estimating.

The method includes calculating first speed information of the second unmanned aerial vehicle based on the GNSS signal, the first inertia value, and the image information, and based on the first speed information and the second inertia value. It may further include generating second speed information of the second unmanned aerial vehicle.

1 is a diagram showing a situation in which the unmanned aerial vehicle cannot receive a communication signal due to an obstacle.
2 is a diagram illustrating a system for estimating a location of an unmanned aerial vehicle according to an exemplary embodiment.
3 is a diagram illustrating a system for estimating a location of an unmanned aerial vehicle according to another embodiment.
Figure 4 is a schematic block diagram of the master unmanned aerial vehicle shown in Figure 2;
5 is a schematic block diagram of the sub unmanned aerial vehicle shown in FIG. 2.
6 is a detailed block diagram of the position estimation apparatus shown in FIG. 3.
7 is a diagram showing an example of a procedure for estimating the position of the unmanned aerial vehicle by the unmanned aerial vehicle position estimation system.
8 is a schematic diagram of an image captured by the master unmanned aerial vehicle shown in FIG. 2 from above.
9 is a diagram showing an example of an image captured from the sky by the master unmanned aerial vehicle shown in FIG. 2.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, since various changes may be made to the embodiments, the scope of the patent application is not limited or limited by these embodiments. It is to be understood that all changes, equivalents, or substitutes to the embodiments are included in the scope of the rights.

The terms used in the examples are used for illustrative purposes only and should not be construed as limiting. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present specification, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof does not preclude in advance.

Terms such as first or second may be used to describe various elements, but the elements should not be limited by terms. The terms are only for the purpose of distinguishing one component from other components, for example, without departing from the scope of rights according to the concept of the embodiment, the first component may be named as the second component, and similarly The second component may also be referred to as a first component.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiment belongs. Terms as defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in the present application. Does not.

In addition, in the description with reference to the accompanying drawings, the same reference numerals are assigned to the same components regardless of the reference numerals, and redundant descriptions thereof will be omitted. In describing the embodiments, when it is determined that a detailed description of related known technologies may unnecessarily obscure the subject matter of the embodiments, the detailed description thereof will be omitted.

1 is a diagram showing a situation in which the unmanned aerial vehicle cannot receive a communication signal due to an obstacle.

Referring to FIG. 1, an unmanned aerial vehicle 10 remotely controlled through a wireless communication method may be developed for military use and used for simple shooting practice. In recent years, the unmanned aerial vehicle 10 may be expanded and spread not only to military use but also to various fields other than that according to the continuous development of electronic communication technology.

For example, the unmanned aerial vehicle 10 may receive a Global Navigation Satellite System (GNSS) signal 2, which is a satellite positioning system, from the communication satellite 1 and update its location information. However, when the GNSS signal 2 received by the unmanned aerial vehicle 10 is blocked by an obstacle such as an urban building or a building and cannot be received (11), the unmanned aerial vehicle 10 may not be able to update its own location information.

In this case, the unmanned aerial vehicle 10 uses a radio wave generating device such as a beacon installed at a fixed location, or a camera installed at a fixed location uses image information of the unmanned aerial vehicle. Can be estimated.

However, in an unmanned aerial vehicle, it may be difficult to estimate its own location in an area where a device for location estimation is not fixedly installed in advance.

In the embodiments, the first unmanned aerial vehicle flexibly provides data necessary for estimating the position of the second unmanned aerial vehicle in the communication shadow area, so that the unmanned aerial vehicle is in a communication shadow area where a device for location estimation is not fixedly installed in advance. Even if there is, it is possible to provide a technology capable of updating location information and the like using the received data.

Hereinafter, embodiments will be described with reference to FIGS. 2 to 6.

FIG. 2 is a diagram illustrating a system for estimating a position of an unmanned aerial vehicle according to an embodiment, and FIG. 3 is a diagram illustrating a system for estimating a position of an unmanned aerial vehicle according to another embodiment.

Referring to FIG. 2, the unmanned aerial vehicle position estimation system 20 includes a master unmanned aerial vehicle 100 and a sub unmanned aerial vehicle 200.

The unmanned aerial vehicle position estimation system 20 improves the accuracy and communication availability of the position estimation of the sub unmanned aerial vehicle 200 in a communication shadowing environment where communication availability is low due to a large number of communication obstacles such as an urban environment, under a bridge, etc. I can make it.

The unmanned aerial vehicle position estimation system 20 may be implemented with a single master unmanned aerial vehicle 100 and a single sub unmanned aerial vehicle 200. The unmanned aerial vehicle position estimation system 20 may be implemented with a single master unmanned aerial vehicle 100 and a plurality of sub unmanned aerial vehicles 200. The unmanned aerial vehicle position estimation system 20 may be implemented with a plurality of master unmanned aerial vehicles 100 and a plurality of sub unmanned aerial vehicles 200.

The master unmanned aerial vehicle 100 is capable of communicating with the communication satellite 1, and is flexibly disposed in a place capable of communicating with the sub unmanned aerial vehicle 200 in the communication shaded area to transmit a communication signal to the sub unmanned aerial vehicle 200. .

As it becomes possible to flexibly deploy the master unmanned aerial vehicle 100 in the communication shaded area, it is possible to estimate the location of the unmanned aerial vehicle in the communication shaded area only when a radio wave generating device and/or a camera is installed fixedly. Can be solved.

The master unmanned aerial vehicle 100 may transmit a communication signal to the sub unmanned aerial vehicle 200 in a communication shaded area. The master unmanned aerial vehicle 100 may provide data for estimating the location of the sub unmanned aerial vehicle 200 in the shaded area. The detailed operation of the master unmanned aerial vehicle 100 will be described in detail in FIG. 4.

The sub unmanned aerial vehicle 200 may receive data transmitted by the master unmanned aerial vehicle 100 and estimate its own location information, etc. based on the received data. The sub unmanned aerial vehicle 200 may receive data transmitted by the master unmanned aerial vehicle 100 and generate speed information or the like based on the received data.

When the sub unmanned aerial vehicle 200 is located in an urban environment and does not receive a signal from the communication satellite 1, it updates its own location information and/or speed information based on the data transmitted by the master unmanned aerial vehicle 100 can do.

The sub unmanned aerial vehicle 200 updates its own location information (eg, location information of the sub unmanned aerial vehicle 200) using the location information of the sub unmanned aerial vehicle 200 measured by the master unmanned aerial vehicle 100 By doing so, the position estimation performance of the sub unmanned aerial vehicle 200 may be improved. The detailed operation of the sub unmanned aerial vehicle 200 will be described in detail with reference to FIG. 5.

Referring to FIG. 3, the unmanned aerial vehicle position estimation system 20 may further include a position estimation apparatus 300.

The location estimation apparatus 300 may communicate with the master unmanned aerial vehicle 100 and the sub unmanned aerial vehicle 200 by being connected to the Internet 3000. The position estimation apparatus 300 may receive data from the communication satellite 1, the master unmanned aerial vehicle 100, and the sub unmanned aerial vehicle 200.

The position estimating apparatus 300 may estimate first position information, second position information, first speed information, and second speed information of the sub unmanned aerial vehicle 200 based on the received data.

The location estimation apparatus 300 may transmit first location information, second location information, first speed information, and second speed information of the sub unmanned aerial vehicle 200 to the sub unmanned aerial vehicle 200.

A detailed operation of the position estimation apparatus 300 will be described in detail with reference to FIG. 6.

Figure 4 is a schematic block diagram of the master unmanned aerial vehicle shown in Figure 2;

Referring to FIG. 4, the master unmanned aerial vehicle 100 may include a receiver 110, a memory 130, a controller 150, and a camera 170. The master unmanned aerial vehicle 100 may further include an inertial measurement device (not shown).

The receiver 110 may receive the GNSS signal 2 from the communication satellite 1. The receiver 110 may receive a second inertia value from the sub unmanned aerial vehicle 200.

The memory 130 may store instructions (or programs) executable by the controller 150. For example, the instructions may include instructions for executing an operation of each component included in the controller 150.

The controller 150 may estimate first location information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, the second inertia value, and the image information.

The first inertia value may be a value measured by an inertial measurement unit (not shown). An inertial measurement device (not shown) may measure acceleration using one or more accelerometers. The inertial measurement device (not shown) may detect the rotational speed using one or more gyroscopes. The inertial measuring device (not shown) may measure magnetic force using a magnetic measuring device.

The controller 150 may estimate first location information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, and image information. The first location information may correspond to location information in which the controller 150 primarily estimates the absolute location of the sub unmanned aerial vehicle 200.

The controller 150 may identify the sub unmanned aerial vehicle 200 from a picture taken by the camera 170 and generate image information obtained by extracting a relative position.

The controller 150 may estimate second location information of the second unmanned aerial vehicle based on the first location information and the second inertia value. The second location information may mean the finally estimated current absolute location information of the sub unmanned aerial vehicle 200.

The controller 150 may generate a navigation solution based on the GNSS signal and the first inertia value.

The controller 150 may estimate the first location information using the navigation solution and image information.

The controller 150 may calculate first speed information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, and the image information.

The controller 150 may generate second speed information of the sub unmanned aerial vehicle 200 based on the first speed information and the second inertia value. The second speed information may mean information on the current speed of the sub-unmanned aerial vehicle 200 that is finally estimated.

The camera 170 may photograph the sub unmanned aerial vehicle 200 to generate a photo including the sub unmanned aerial vehicle 200.

5 is a schematic block diagram of the sub unmanned aerial vehicle shown in FIG. 2.

Referring to FIG. 5, the sub unmanned aerial vehicle 200 may include a receiver 210, a memory 230, and a controller 250. The sub unmanned aerial vehicle 200 may further include an inertial measurement device (not shown).

The receiver 210 may receive data transmitted by the master unmanned aerial vehicle 100. The data transmitted by the master unmanned aerial vehicle 100 may include a GNSS signal, a first inertia value, image information, a navigation solution, first position information, and first speed information.

The memory 230 may store instructions (or programs) executable by the controller 250. For example, the instructions may include instructions for executing an operation of each component included in the controller 250.

The controller 250 may estimate second location information of the second unmanned aerial vehicle based on the first location information and a second inertia value of the second unmanned aerial vehicle.

The second inertia value may be a value measured by an inertial measuring device (not shown). An inertial measurement device (not shown) may measure acceleration using one or more accelerometers. The inertial measurement device (not shown) may detect the rotational speed using one or more gyroscopes. The inertial measuring device (not shown) may measure magnetic force using a magnetic measuring device.

The controller 250 may generate second speed information of the sub unmanned aerial vehicle 200 based on the first speed information and the second inertia value.

6 is a schematic block diagram of the position estimation apparatus shown in FIG. 3.

Referring to FIG. 6, the position estimation apparatus 300 may include a receiver 310, a memory 330, and a third controller 350.

The receiver 310 may receive a GNSS signal, a first inertia value, image information, a navigation solution, and the like from the master unmanned aerial vehicle 100. The receiver 310 may transmit a GNSS signal, first position information, second position information, first speed information, and second speed information to the master unmanned aerial vehicle 100.

The receiver 310 may receive a second inertia value from the sub unmanned aerial vehicle 200. The receiver 310 may transmit a GNSS signal, first position information, second position information, first speed information, and second speed information to the sub unmanned aerial vehicle 200.

The memory 330 may store instructions (or programs) executable by the third controller 350. For example, the instructions may include instructions for executing an operation of each component included in the third controller 350.

The third controller 350 may estimate second location information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, the second inertia value, and the image information.

The third controller 350 may estimate first location information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, and the image information.

The third controller 350 may estimate second location information of the sub unmanned aerial vehicle 200 based on the first location information and the second inertia value.

The third controller 350 may generate a navigation solution based on the GNSS signal and the first inertia value.

The third controller 350 may estimate the first location information using the navigation solution and image information.

The third controller 350 may calculate first speed information of the sub unmanned aerial vehicle 200 based on the GNSS signal, the first inertia value, and image information.

The third controller 350 may generate second speed information of the sub unmanned aerial vehicle 200 based on the first speed information and the second inertia value.

7 is a diagram showing an example of a procedure for estimating the position of the unmanned aerial vehicle by the unmanned aerial vehicle position estimation system.

Referring to FIG. 7, the master unmanned aerial vehicle 100 may receive a GNSS signal, measure a first inertia value, and generate image information (710).

The master unmanned aerial vehicle 100 may generate a navigation solution using the GNSS signal and the first inertial value (720).

The master unmanned aerial vehicle 100 may estimate the first location information based on the navigation solution and image information (730).

The master unmanned aerial vehicle 100 may transmit the first location information to the second unmanned aerial vehicle (740).

The sub unmanned aerial vehicle 200 may receive the first location information (752). The sub unmanned aerial vehicle 200 may measure the second inertia value (754).

The sub unmanned aerial vehicle 200 may estimate the second location information based on the first location information and the second inertia value (760 ).

FIG. 8 is a schematic diagram of an image captured from the sky by the master unmanned aerial vehicle shown in FIG. 2, and FIG. 9 is a view showing an example of an image captured by the master unmanned aerial vehicle shown in FIG. 2.

Referring to FIG. 8, a viewpoint of the master unmanned aerial vehicle 100 looking at obstacles a to f obstructing communication and the sub unmanned aerial vehicles 810, 820, and 830 from above may be shown.

As shown in FIG. 8, the master unmanned aerial vehicle 100 may determine the positions of the sub unmanned aerial vehicles 810, 820, and 830 above the sub unmanned aerial vehicles 810, 820, and 830.

The master unmanned aerial vehicle 100 may take a picture including the sub unmanned aerial vehicles 810, 820, and 830. The master unmanned aerial vehicle 100 may generate relative position information of the sub unmanned aerial vehicles 810, 820, and 830 from the photographed photo.

Referring to FIG. 9, an example of a picture taken from the viewpoint of the master unmanned aerial vehicle 100 may be shown. As such, when the sub unmanned aerial vehicle 200 is in a communication shaded area, the master unmanned aerial vehicle 100 may provide a communication signal such as a GNSS signal of the communication satellite 1 above the sub unmanned aerial vehicle 200.

In addition, the master unmanned aerial vehicle 100 may generate first location information of the sub unmanned aerial vehicle 200 with image information as shown in FIG. 9. The master unmanned aerial vehicle 100 may generate second location information based on the second inertia value received from the sub unmanned aerial vehicle 200.

As described above, the unmanned aerial vehicle position estimation system 20 is used to estimate the position of the unmanned aerial vehicle in a satellite shading environment, such as when the GNSS, which is a satellite positioning system, cannot be used or is difficult to trust because there are many high obstacles such as an urban environment, under a bridge, etc. Accuracy and communication availability can be improved.

The unmanned aerial vehicle position estimation system 20 secures the mobility of the relative navigation platform and detection area by using a master unmanned aerial vehicle equipped with a camera, and sends navigation assistance information to a number of sub-unmanned aerial vehicles in the local area to provide information. 2 It can improve the position estimation performance of unmanned aerial vehicles.

The unmanned aerial vehicle position estimation system 20 can provide navigation measurements to sub-unmanned aerial vehicles for performing multiple missions through one master unmanned aerial vehicle, so that it performs missions such as multi-flying and swarming in areas with many obstacles, such as urban areas. It can be effective when done.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -A hardware device specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

The software may include a computer program, code, instructions, or a combination of one or more of these, configuring the processing unit to operate as desired or processed independently or collectively. You can command the device. Software and/or data may be interpreted by a processing device or, to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodyed in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

As described above, although the embodiments have been described by the limited drawings, a person of ordinary skill in the art can apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order from the described method, and/or components such as systems, structures, devices, circuits, etc. described are combined or combined in a form different from the described method, or other components Alternatively, even if substituted or substituted by an equivalent, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and claims and equivalents fall within the scope of the following claims.

Claims (12)

In the method for estimating the position of the sub unmanned aerial vehicle using the master unmanned aerial vehicle,
Receiving, by the sub unmanned aerial vehicle, first estimated position information of the sub unmanned aerial vehicle from the master unmanned aerial vehicle; And
Estimating, by the sub unmanned aerial vehicle, final estimated location information of the sub unmanned aerial vehicle based on the first estimated location information and a second inertia value of the sub unmanned aerial vehicle
Including,
The first estimated location information is based on a GNSS (Global Navigation Satellite System) signal by the master unmanned aerial vehicle, a first inertia value for the master unmanned aerial vehicle, and image information of the sub unmanned aerial vehicle captured by the master unmanned aerial vehicle from above. Is an estimate based on
The first estimated location information and the final estimated location information are absolute location information for the sub unmanned aerial vehicle.
How to estimate the location of the drone.
The method of claim 1,
The first estimated location information,
Estimated using the navigation solution and the image information generated based on the GNSS signal and the first inertia value
How to estimate the location of the drone.
The method of claim 1,
Receiving, by the sub unmanned aerial vehicle, first speed information of the sub unmanned aerial vehicle from the master unmanned aerial vehicle; And
Generating, by the sub unmanned aerial vehicle, second speed information of the sub unmanned aerial vehicle based on the first speed information and the second inertia value
Unmanned aerial vehicle position estimation method further comprising a.
The method of claim 3,
The first speed information is
A method of estimating the position of the unmanned aerial vehicle calculated based on the GNSS signal, the first inertia value, and the image information.
Receiving, by a position estimation apparatus, a Global Navigation Satellite System (GNSS) signal from a master unmanned aerial vehicle, a first inertial value of the master unmanned aerial vehicle, and image information of a sub unmanned aerial vehicle captured by the master unmanned aerial vehicle from above;
Receiving, by the position estimation apparatus, a second inertia value of the sub unmanned aerial vehicle from the sub unmanned aerial vehicle; And
Estimating, by the position estimating apparatus, final estimated position information of the sub unmanned aerial vehicle based on the GNSS signal, the first inertia value, the second inertia value, and the image information
Including,
The final estimated location information is absolute location information for the sub unmanned aerial vehicle.
How to estimate the location of the drone.
The method of claim 5,
The estimating step,
Estimating first estimated position information of the sub unmanned aerial vehicle based on the GNSS signal, the first inertia value, and the image information; And
Estimating final estimated position information of the sub unmanned aerial vehicle based on the first estimated position information and the second inertial value
Including,
The first estimated location information is absolute location information for the sub unmanned aerial vehicle.
How to estimate the location of the drone.
The method of claim 6,
The step of estimating the first estimated location information,
Generating a navigation solution based on the GNSS signal and the first inertia value; And
Estimating the first estimated position information using the navigation solution and the image information
Unmanned aerial vehicle position estimation method comprising a.
The method of claim 5,
Calculating, by the position estimation apparatus, first speed information of the sub unmanned aerial vehicle based on the GNSS signal, the first inertia value, and the image information; And
Generating, by the position estimating device, second speed information of the sub unmanned aerial vehicle based on the first speed information and the second inertia value
Unmanned aerial vehicle position estimation method further comprising a. delete delete delete delete

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