WO2023056698A1

WO2023056698A1 - Positioning navigation method and system of aircraft, and computing device

Info

Publication number: WO2023056698A1
Application number: PCT/CN2021/135458
Authority: WO
Inventors: 赵德力; 王建明; 陶永康; 傅志刚
Original assignee: 广东汇天航空航天科技有限公司
Priority date: 2021-10-09
Filing date: 2021-12-03
Publication date: 2023-04-13
Also published as: CN113917939A; CN113917939B

Abstract

The present application relates to a positioning navigation method and system of an aircraft, and a computing device. The positioning navigation method comprises: obtaining real-time flight map data generated in the present flight of an aircraft, the real-time flight map data comprising topographic data; determining, according to the topographic data in the real-time flight map data and pre-stored historical flight map data, whether a current flight area is a known area; and if it is determined that the current flight area is the known area, obtaining positioning navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning navigation data. According to embodiments of the present application, the dependence of the aircraft on GNSS positioning data can be effectively reduced, such that the correct navigation of the aircraft can still be ensured under the condition that a GNSS signal does not satisfy the requirements, thereby improving the flight safety and effectiveness.

Description

Positioning and navigation method, system and computing device for aircraft

This application claims the priority of the Chinese patent application with the application number 202111174390.0 and the application title "Aircraft Positioning and Navigation Method, System and Computing Equipment" submitted to the State Intellectual Property Office on October 09, 2021, the entire contents of which are incorporated by reference in this application.

technical field

The present application relates to the technical field of aircraft, in particular to a positioning and navigation method, system and computing device for an aircraft.

Background technique

As a new type of ground-to-air transportation that combines aircraft and cars, flying cars have gradually entered the consumer's field of vision. Compared with ground cars, the air form of flying cars has a unique traffic environment. Due to the lack of "road" constraints and positioning, at present, flying cars generally rely heavily on the positioning information provided by the GNSS (Global Navigation Satellite System) system under manual driving or automatic driving.

The GNSS positioning method is greatly affected by the GNSS signal. For example, when flying cars fly at low altitudes in cities, GNSS signals are prone to loss or accuracy degradation due to building blockages and multipath effects. For another example, when a flying car is flying in a mountainous area, due to the scarcity of signal base stations, there may be situations where the signal strength in some flight areas is weak or there is no signal. Even, due to the high reliance on GNSS positioning signals, hackers may maliciously induce GNSS signals. These will directly affect the normal flight of flying cars.

technical problem

In order to overcome the problems existing in related technologies, this application provides a positioning and navigation method, system and computing equipment for an aircraft, which can effectively reduce the dependence of the aircraft on GNSS positioning data, so that the aircraft can still operate when the GNSS signal does not meet the requirements. It can ensure the correct navigation of the aircraft, thereby improving flight safety and effectiveness.

technical solution

An embodiment of the present application provides an aircraft positioning and navigation method on the one hand, including:

Obtaining real-time flight map data generated during the current flight of the aircraft, the real-time flight map data including terrain data;

judging whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data;

If it is determined that the current flight area is a known area, the positioning and navigation data of the aircraft is obtained according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data.

In some embodiments, the obtaining the real-time flight map data generated during the current flight of the aircraft includes:

Obtain the aerial survey terrain data of the aircraft and the state parameters of the aircraft that are aligned in time; wherein, the aerial survey terrain data of the aircraft include radar detection terrain fluctuation data, and the state parameters of the aircraft include real-time pose data of the aircraft ;

According to the aerial survey terrain data and state parameters, generate grid-type real-time flight map data, the grid-type real-time flight map data includes grid position data and grid corresponding terrain feature data, wherein the grid The location data includes grid location estimation data obtained from the real-time pose data, and the terrain feature data includes radar object identification tags obtained from the radar detected terrain relief data.

In some embodiments, the terrain feature data also includes prior geographic location data; and/or,

The aerial survey terrain data also includes map image data that is temporally and spatially aligned with the radar-detected terrain relief data, and the terrain feature data also includes terrain visual feature data and/or terrain features obtained from the ground image data. visual semantic feature data; and/or,

The state parameter of the aircraft also includes GNSS positioning data of the aircraft, and the grid position data also includes GNSS positioning data corresponding to the grid.

In some embodiments, the determining whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data includes:

Determine the grid to be matched according to the terrain feature data in the real-time flight map data;

performing feature matching on the flight map data corresponding to the grid to be matched in the real-time flight map data and the pre-stored historical flight map data;

According to the result of the feature matching, it is judged whether the current flight area is the area that the aircraft has flown or whether it is the flight map data sharing area.

Obtaining the current frame flight map data generated during the current flight of the aircraft and the time-lapse flight map data before the current frame;

The current frame flight map data and the time-lapse flight map data are fused to obtain the time-lapse flight map data including the current frame.

In some embodiments, the fusion of the current frame flight map data generated during the current flight of the aircraft and the time-lapse flight map data before the current frame includes:

performing compression processing on the current frame of flight map data generated during the current flight of the aircraft, so as to convert the data of the three-dimensional grid type into two-dimensional grid type data, and retain the terrain in the current frame of flight map data characteristic information;

The flight map data of the current frame of the two-dimensional grid type and the flight map data of the current frame before the current frame of the two-dimensional grid type are fused.

In some embodiments, the method also includes:

If it is determined that the current flight area is not a known area, obtain differential map data between the real-time flight map data and the pre-stored historical flight map data;

The pre-stored historical flight map data is updated according to the differential map data; and/or, the differential map data is uploaded to a cloud server, so that the cloud server updates the shared historical flight map data.

In some embodiments, the obtaining the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data, includes:

Generating dynamic flight route data of the aircraft in real time according to the pre-stored historical flight map data, so as to perform flight control according to the dynamic flight route data.

In some embodiments, pre-generated memory flight route data is obtained from the pre-stored historical flight map data, so as to perform flight control according to the memory flight route data.

In some embodiments, if it is determined that the current flight area is not a known area, the method further includes:

According to part or all of the mission data, status data, and flight control data of the current flight of the aircraft, generate memory flight route data;

The pre-stored historical flight map data is updated according to the stored flight route data; and/or, the stored flight route data is uploaded to a cloud server, so that the cloud server updates the cloud historical flight map data.

Another aspect of an embodiment of the present application provides a computing device, including a processor, a memory, and a computer program stored on the memory and capable of running on the processor. When the computer program is executed by the processor, Implement any of the methods described above.

Another aspect of an embodiment of the present application provides an aircraft positioning and navigation system, including:

a computing device as described above; and

The execution unit is configured to execute the flight control instruction, wherein the flight control instruction is generated according to the positioning and navigation data obtained by the computing device.

In some embodiments, the system also includes:

An altimeter, used to collect the real-time altitude of the aircraft during the flight of the aircraft;

An aerial survey terrain detection device is used to collect terrain data during the flight of the aircraft; the aerial survey terrain control device includes a laser radar;

The inertial measurement unit is used to collect real-time pose data of the aircraft during the flight of the aircraft.

In some embodiments, the aerial terrain detection device further includes an image acquisition device, which is used to collect ground images in real time during the flight of the aircraft, so as to obtain terrain visual feature data and/or terrain visual semantics as part of the real-time flight map data characteristic data; and/or,

The system also includes a GNSS positioning module for obtaining GNSS position data of the aircraft during flight of the aircraft, so as to obtain grid-corresponding GNSS positioning data as a part of the real-time flight map data.

Another aspect of an embodiment of the present application provides an aircraft, including the above-mentioned aircraft positioning and navigation system.

Beneficial effect

According to the aircraft positioning and navigation method provided by an embodiment of the present application, according to the terrain data in the real-time flight map data and the pre-stored historical flight map data, it is judged whether the current flight area of the aircraft is a known area, and when the current flight area is determined to be a known area , obtain the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data. By using the pre-stored historical flight map data for positioning and navigation of the aircraft, the dependence of the aircraft on GNSS positioning data can be effectively reduced, so that the aircraft can still operate when the GNSS signal does not meet the requirements (such as weak signal, insufficient accuracy, loss or even failure). It can ensure the correct navigation of the aircraft, thereby improving flight safety and effectiveness.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Description of drawings

The above and other objects, features and advantages of the present application will become more apparent by describing the exemplary embodiments of the present application in more detail with reference to the accompanying drawings, wherein, in the exemplary embodiments of the present application, the same reference numerals generally represent same parts.

FIG. 1 is a schematic flow chart of an aircraft positioning and navigation method in an embodiment of the present application;

FIG. 2 is a schematic flowchart of a positioning and navigation method for an aircraft in another embodiment of the present application;

Fig. 3 exemplarily shows the terrain detection principle of lidar;

FIG. 4 is a schematic structural diagram of a computing device according to an embodiment of the present application;

5 is a schematic structural diagram of an aircraft positioning and navigation system according to an embodiment of the present application;

FIG. 6 is a schematic structural diagram of an aircraft positioning and navigation system according to another embodiment of the present application.

Embodiments of the present invention

Preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of this application to those skilled in the art.

The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term "and/or" as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

It should be understood that although the terms "first", "second", "third" and so on may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of the present application, first information may also be called second information, and similarly, second information may also be called first information. Thus, a feature defined as "first" and "second" may explicitly or implicitly include one or more of these features. In the description of the present application, "plurality" means two or more, unless otherwise specifically defined.

In order to facilitate understanding of the solutions of the embodiments of the present application, the technical solutions of the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

FIG. 1 is a schematic flowchart of a positioning and navigation method for an aircraft according to an embodiment of the present application. It can be understood that the aircraft in this application may be, but not limited to, a flying car. Referring to Fig. 1, the positioning and navigation method of the aircraft of the present embodiment includes:

In step S101, real-time flight map data generated during the current flight of the aircraft is obtained, and the real-time flight map data includes terrain data.

In the embodiment of the present application, during the execution of the flight mission, as the aircraft continues to fly, relevant data collection may be performed periodically to generate real-time flight map data. The real-time flight map data corresponding to the entire flight mission of the aircraft may be composed of each frame of real-time flight map data corresponding to each data collection moment.

It can be understood that the real-time flight map data in step S101 may be the real-time flight map data corresponding to the entire flight mission of the aircraft, or the real-time flight map data of the current frame, and the current frame may be one frame or several frames.

The terrain data included in the real-time flight map data may be the aerial survey terrain data of the ground area passed by the aircraft during flight. Obtained radar object identification tags. Lidar has high angular resolution and distance resolution, and can effectively and accurately detect terrain under the low-altitude flight conditions of aircraft.

In some embodiments, the terrain data may also include terrain visual feature data and/or terrain visual semantic feature data obtained from the map image data collected by the camera mounted on the aircraft.

In step S102, it is determined whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data.

In this embodiment, the historical flight map data can be pre-stored locally on the aircraft. The historical flight map data can be stored after obtaining from the shared historical flight map data maintained by the cloud server, or it can be the flight mission of the aircraft before this flight. generated and stored in the . It can be understood that the historical flight map data can also be grid-type data, and its data structure can be the same as the real-time flight map data generated by this flight, or it can also be different, for example, it can only include part of the data in the real-time flight map data Items can also include data items not included in the real-time flight map data.

In this embodiment, it can be judged whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data.

It can be understood that the current flight area may correspond to the corresponding ground area of the real-time flight map data in step S101, for example, when the real-time flight map is the real-time flight map data of the current frame, the current flight area is the ground area corresponding to the current frame.

In some implementations, feature matching is performed on the real-time flight map data and the pre-stored historical flight map data. If the matching result meets the preset conditions, it is determined that the current flight area is a known area. If not, it is determined that the current flight area is not a known area. . It can be understood that feature matching may include matching of topographical features, and may also be matching of features other than topographical features.

In some implementations, the real-time flight map data is grid type data, and the grid to be matched can be determined according to the terrain feature data in the real-time flight map data, and then the flight map data corresponding to the grid to be matched in the real-time flight map data and Prestore historical flight map data for feature matching, and then judge whether the current flight area is a known area according to the result of feature matching.

It can be understood that whether the current flight area is a known area may include the situation that the current flight area is an area that the aircraft has flown, and also includes that the current flight area is that other aircraft that share flight map data with the aircraft have flown and generated flight map data (that is, the current flight area is the flight map data sharing area).

In some implementations, the pre-stored historical flight map data is generated and stored by the aircraft in the flight missions before the current flight, and it can be determined whether the current flight area is the area that the aircraft has flown according to the result of terrain feature matching.

In some embodiments, the pre-stored historical flight map data is stored after being obtained from the cloud historical flight map data maintained by the cloud server. A collection of map data. According to the result of terrain feature matching, it can be judged whether the current flight area is a shared area of flight map data of multiple aircraft.

In step S103, if it is determined that the current flight area is a known area, the positioning and navigation data of the aircraft are obtained according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data.

In some implementations, if it is determined that the current flight area is a known area, the dynamic flight route data of the aircraft is generated in real time according to the pre-stored historical flight map data, so as to perform flight control according to the dynamic flight route data.

In other embodiments, if it is determined that the current flight area is a known area, the pre-generated memory flight route data is obtained from the pre-stored historical flight map data, so as to perform flight control according to the memory flight route data.

In this embodiment, it is judged whether the current flight area of the aircraft is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data. Positioning and navigation data of the aircraft, so as to perform flight control according to the positioning and navigation data. By using the pre-stored historical flight map data for positioning and navigation of the aircraft, the dependence of the aircraft on GNSS positioning data can be effectively reduced, so that the aircraft can still operate when the GNSS signal does not meet the requirements (such as weak signal, insufficient accuracy, loss or even failure). It can ensure the correct navigation of the aircraft, thereby improving flight safety and effectiveness.

FIG. 2 is a schematic flowchart of a positioning and navigation method for an aircraft according to another embodiment of the present application. Referring to Fig. 2, the present embodiment includes:

In step S201 , the current frame flight map data generated during the current flight of the aircraft and the time-lapse flight map data before the current frame are obtained.

In this application, the multi-frame flight map data generated by the aircraft during this flight can be fused to form the time-lapse flight map data. After the current frame flight map data is generated, the current frame flight map data can be combined with the current frame previous flight map The data is fused to update the flight map data over time. It can be understood that the current frame may be one frame or multiple frames.

In some embodiments, grid map technology is used to generate real-time flight map data, and one frame of flight map data can be composed of one or more flight map data corresponding to grids with the same area.

In a specific implementation, the time-aligned aerial survey terrain data of the aircraft and the state parameters of the aircraft are respectively obtained, and the real-time flight map data of grid type is generated according to the aerial survey terrain data and state parameters. Among them, the aerial survey terrain data of the aircraft includes radar detection terrain undulation data, the state parameters of the aircraft include the real-time pose data of the aircraft; the real-time flight map data of the grid type includes grid position data, and grid corresponding terrain feature data, wherein, The grid position data includes grid position estimation data obtained from the real-time pose data of the aircraft, and the terrain feature data includes radar-detected terrain relief data and radar object identification labels obtained from the radar-detected terrain relief data. It can be understood that the time alignment of multiple data means that the multiple data correspond to the same collection time or the same collection time range.

It can be understood that an aerial terrain detection device and an inertial measurement unit are pre-installed on the aircraft. Aerial terrain detection devices such as lidar can obtain radar-detected terrain fluctuation data during aircraft flight through lidar; real-time position and attitude data during aircraft flight can be obtained through inertial measurement unit.

In some embodiments, the aerial terrain detection device may be, for example, a laser radar installed at the bottom of the aircraft. It can be understood that multiple laser radars can be installed at different parts of the bottom of the aircraft, and the range of the ground area corresponding to each frame of terrain data can be expanded by fusing the terrain data collected by multiple laser radars. Figure 3 exemplarily shows the terrain detection principle of lidar. As shown in Figure 3, the installation angle of the lidar of the aircraft is β angle, the flight horizontal inclination angle is α angle, and the angle between the center of the lidar and the vertical direction is

h _fly is the real-time altitude of the aircraft obtained by the altimeter of the aircraft. Line ₁ and Line ₂ are the two rays emitted by the lidar. The angle between this ray and the center of the lidar is a known quantity. Through geometric calculation, the height of different objects below the aircraft can be obtained, such as the altitude of P1 in the figure h ₁ , and the altitude h ₂ of point P2, combined with the altitude of each sampling point in the current frame, the radar detection terrain fluctuation data of the current frame can be obtained; ground objects can be identified according to the radar detection terrain fluctuation data, for example, according to the terrain The surface parameters of the object are obtained from the fluctuation data, and then the object identification label is determined according to the surface parameters of the object.

The grid's location data may include the grid's location coordinates and/or index number. The position coordinates of the grid may include, for example, the latitude and longitude coordinates of a preset reference point (such as a central point) in the grid, and the latitude and longitude coordinates may be estimated based on the real-time pose data of the aircraft and the latitude and longitude coordinates of the reference point. The index number of the grid can be, for example, the number of the row and column where the grid is located, and the position coordinates of the grid can be determined through the index number of the grid, the grid size standard, and the latitude and longitude coordinates of the reference point.

It can be understood that, in some embodiments, an altimeter (such as a millimeter-wave radar or a range-finding radar) is pre-installed on the aircraft for obtaining the real-time ground-level altitude of the aircraft, and the real-time ground-level height of the aircraft is combined with the aerial terrain data of the aircraft. After spatial and temporal alignment, the elevation data corresponding to the grid and the grid location data are stored correspondingly. Among them, the altitude data corresponding to the grid is obtained according to the real-time altitude of the aircraft corresponding to the grid, for example, it can be the real-time altitude corresponding to a preset reference point in the grid or it can be multiple preset The real-time corresponding height-weighted average value corresponding to the reference point, etc.

It can be understood that spatially aligning the real-time ground altitude and aerial terrain data of the aircraft refers to obtaining real-time ground altitude and aerial terrain data corresponding to the same ground area (in this embodiment, corresponding to the same grid).

In some embodiments, the terrain feature data corresponding to the grid further includes prior geographic location information corresponding to the grid. The prior geographic location information may include geographic information such as provinces, cities, districts, and streets, for example, and the prior geographic location information may be obtained by matching traditional maps with grid location coordinates. By adding prior geographic location information to the grid flight map data, the correspondence between the grid map and the physical world can be effectively improved, and favorable conditions can be provided for the speed and accuracy of map matching in subsequent steps.

In some embodiments, the ground image can be collected in real time by the camera mounted on the aircraft during the flight of the aircraft; further, the ground image data can be obtained in time and space aligned with the radar detection terrain relief data, and the ground image data can be obtained according to the ground image data. For terrain visual feature data and/or terrain visual semantic feature data, the terrain visual feature data and/or terrain visual semantic feature data are stored in association with corresponding radar object identification tags in the grid flight map data. It can be understood that the radar detection terrain relief data and ground image data aligned in time and space refer to the radar detection corresponding to the same time or the same acquisition time range corresponding to the same ground area (in this embodiment, corresponding to the same grid). Terrain relief data and ground image data, and the two have a pixel-level correspondence. By adding terrain visual feature data and/or terrain visual semantic feature data to the raster flight map data, the feature information can be further enriched on the basis of the lidar detection terrain data, and the information volume and feature dimension of the terrain data can be increased, which is the next step. The speed and accuracy of map matching in .

In some specific implementations, the ground image frames are processed according to a preset image feature extraction algorithm (such as SIFT, SURF, ORB) to obtain terrain visual feature data.

In some specific implementations, the semantic processing is performed on multiple grids of the ground image frame, and corresponding semantic data is generated for each grid. The semantic data includes the label data of terrain elements; The dominant terrain, the label data of terrain elements can be, for example, landmark buildings, building logos, characteristic roads, parks, green plant distribution, etc., but not limited thereto. For example, after the current ground image frame is clustered and segmented using the global clustering segmentation algorithm, in each grid divided by the current ground image frame, feature vectors are extracted from the clustered and segmented regions, and the extracted feature vectors are input into SVM (Support Vector Machines, Support Vector Machines) or cascaded classifiers are used to classify and determine the label data of each type of terrain element in the grid; in addition, the area ratio of each type of terrain in the grid is also calculated , and then determine the dominant terrain in the grid according to the area ratio of each type of terrain. It can be understood that other image processing algorithms can also be used to perform semantic processing on the tiles. For example, the set segmentation algorithm can be segmentation algorithms such as region growing and watershed, or a semantic segmentation algorithm based on a deep learning model. When using the semantic segmentation algorithm based on the deep learning model, based on the computing resources of the aircraft, additional lightweight acceleration processing can be performed on the deep learning model to meet the real-time requirements.

In some embodiments, the GNSS positioning signal of the aircraft can be obtained during the flight of the aircraft through the global navigation satellite system (Global navigation satellite system, referred to as GNSS) positioning module loaded on the aircraft; if the GNSS positioning signal meets the preset conditions, such as satisfying If the preset signal strength and/or meet the preset confidence level, the GNSS position data aligned in time with the real-time pose data of the aircraft is obtained, and the two are associated and stored in the grid flight map data.

Further, by adding GNSS positioning data to the grid flight map data, the position information of the grid can be enriched. In related technologies, the positioning signal of the GNSS positioning module may be weak, lost, or interfered with, resulting in a decrease in accuracy or even failure. By setting the GNSS positioning signal to meet the preset conditions, the GNSS positioning is added to the grid flight map data. Coordinates to ensure the reliability of the added GNSS positioning data.

In step S202, the flight map data of the current frame and the time-lapse flight map data before the current frame are fused to obtain the updated time-lapse flight map data including the current frame.

The current frame flight map data may contain missing data and overlapped data in the previous flight map data of the current frame. After obtaining the current frame flight map data, the current frame flight map data and the current frame previous flight map data are combined Fusion, to update the time-lapse flight map data, that is, to obtain the updated time-lapse flight map data including the current frame.

Understandably, as time goes by, the data volume of the time-lapse flight map data will inevitably increase. In some embodiments, after the current frame flight map data is compressed, the compressed current frame flight map data is fused with the temporal flight map data before the current frame to reduce the data volume of the temporal flight map data. In a specific implementation, the data in the height direction in the three-dimensional grid flight map data is removed from the current frame flight map data, that is, the data of the three-dimensional grid type is converted into two-dimensional grid type data, and at the same time, the current frame flight map is retained Terrain feature information in the data; in this way, the amount of data can be compressed while retaining the terrain feature information.

In step S203, the grid to be matched is determined according to the terrain feature data in the updated flight map data.

In step S204, perform feature matching on the flight map data corresponding to the grid to be matched in the updated flight map data and the pre-stored historical flight map data, and judge whether the current flight area is a known area according to the result of feature matching. If the result is yes, execute step S205, and if the judgment result is no, execute step S206.

It is understandable that if the updated chronological flight map data is directly matched with the pre-stored historical flight map data, as the flight area continues to expand over time, the data volume of the updated chronological flight map will also continue to increase, such as using the original polling method (Expressed by the following formula) Calculating the matching value between the grids will lead to an increase in the amount of calculation.

Among them, lastmap is the pre-stored historical flight map, locmap is the local updated diachronic flight map data map, and block _{1, 2...m} is the grid contained in the updated diachronic flight map.

In this embodiment, before matching the updated chronological flight map data with the pre-stored historical flight map data, first determine the grid to be matched according to the terrain feature data in the updated chronological flight map data, which can reduce the grids that need to be matched In order to limit the calculation amount of feature matching, reduce the occupied computing resources and improve the running speed.

It can be understood that the grid to be matched can be determined according to some terrain features in the updated time-lapse flight map data (for example, based on prior geographic location data and/or terrain visual semantic feature data); When feature matching is performed on flight map data, it can be matched according to some terrain features (such as radar object identification tags, terrain visual feature data, and/or terrain visual semantic feature data). Compared with terrain features, it can improve the accuracy of feature matching.

It can be understood that the aircraft updates the chronological flight map data according to a preset cycle, and periodically performs feature matching on the flight map data corresponding to the grid to be matched in the updated chronological flight map data and the pre-stored historical flight map data. In some embodiments, the feature matching interval of the aircraft in this flight is not the same, for example, it can be gradually reduced, or the feature matching interval before the predetermined time point is greater than the feature matching interval after the predetermined time point, like this, it can be avoided. In the initial stage of flight, due to the small range of the flight map, it is difficult to effectively match the pre-stored historical flight map data, resulting in unnecessary waste of computing resources.

In step S205, when it is determined that the current flight area is a known area, the positioning and navigation data of the aircraft is obtained according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data, and then return to step S201 again until the aircraft is completed. this flight.

In some embodiments, feature matching is performed on the updated chronological flight map data and the pre-stored historical flight map data, and the characteristics of the corresponding grids of the updated chronological flight map data and the corresponding grids of the pre-stored historical flight map data can be obtained The number of rasters whose matching degree satisfies the preset condition. When the number of grids meeting the preset conditions is greater than the preset value or preset ratio, it is determined that the updated flight map data and the pre-stored historical flight map data are successfully matched, thereby determining that the current flight area is a known area; otherwise, it is determined that the updated The time-lapse flight map data failed to match with the pre-stored historical flight map data, and it was determined that the current flight area is not a known area.

In this embodiment, obtaining the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data includes: generating the dynamic flight route data of the aircraft in real time according to the pre-stored historical flight map data, so as to obtain the dynamic flight route data according to the dynamic flight route. data for flight control; or obtain pre-generated memory flight route data from pre-stored historical flight map data, so as to perform flight control according to the memory flight route data.

In some specific implementations, the pre-stored historical flight map data includes GNSS positioning data, and after judging that the updated flight map data and the pre-stored historical flight map data match successfully, the real-time GNSS of the aircraft can be determined according to the GNSS positioning data in the pre-stored historical flight map data. Positioning data, so as to solve the problem of GNSS positioning data decline or even failure caused by weak signal, loss, interference and other reasons during the flight of the aircraft.

It can be understood that by periodically matching the updated flight map data with the pre-stored historical flight map data, the real-time GNSS positioning data of the aircraft can be continuously obtained according to the pre-stored historical flight map data.

In some embodiments, the dynamic flight path data of the aircraft can be generated in real time according to the GNSS positioning data obtained by matching the pre-stored historical flight map data, and the flight control can be performed according to the dynamic flight path data. The dynamic flight route data can be segmented data of the flight route within a preset time period after the current moment, and flight control instructions can be generated according to the segmented data of the flight route and the current attitude of the aircraft, so as to control the aircraft within the preset time period Fly according to the path corresponding to the flight path segment data.

In some specific implementations, the pre-stored historical flight map data includes pre-generated memory flight route data, and after it is determined that the updated historical flight map data matches the pre-stored historical flight map data successfully, the matching memory flight map data can be obtained from the pre-stored historical flight map data. route data, and then generate an automatic flight control instruction according to the stored flight route data and the current pose of the aircraft, thereby controlling the aircraft to automatically fly in accordance with the path corresponding to the stored flight route data.

In step S206, if it is determined that the current flight area is not a known area, the difference map data between the updated flight map data and the pre-stored historical flight map data is obtained.

In step S207, the pre-stored historical flight map data is updated according to the differential map data.

If the current flight area is not a known area, the differential map data and the pre-stored historical flight map data are fused to update the pre-stored historical flight map data. In this way, the pre-stored historical flight map data can be gradually upgraded, so that the pre-stored historical flight map data includes flight map data of a larger flight area. In some embodiments, the historical flight map data includes memory flight path data. After it is determined that the previous flight area is not a known area, the memorized flight route data is generated according to the mission data, status data and flight control data of the current flight of the aircraft. Flight mission data may include, for example, starting point, end point, mission duration, etc. Aircraft status data may include, for example, positioning data, velocity data, acceleration data, attitude data, etc. Drive motor control data, steering gear control data, tilt motor control data, etc. It can be understood that the generated memorized flight route data may be the data of some flight segments in the complete flight route of this flight. After the aircraft completes this flight, the memory flight data of each flight segment constitutes the memory flight route data of the complete route, and the pre-stored historical flight map data can be updated according to the memory flight route data for calling in the same flight mission next time ;

It can be understood that, in some embodiments, after the differential map data is obtained, the differential map data is uploaded to the cloud server, so that the cloud server updates the shared historical flight map data. In a further embodiment, after obtaining the memorized flight route data, the memorized flight route data can be uploaded to the cloud server, so that the cloud server can update the shared historical flight map data for other aircraft to call in the same flight mission.

In some embodiments, the aircraft can automatically update the pre-stored historical flight map data according to the memorized flight route data, or it can also output a user prompt option for the user to confirm whether to update.

In some embodiments, the number of memorized flight routes that can be stored is preset, so as to limit the number of memorized flight routes stored in the pre-stored historical flight map data. For example, if the number of memory flight routes that can be stored is set to 5, when the sixth memory flight route data is generated, the specified one or the oldest memory flight route of the pre-stored historical flight map data can be deleted to maintain the preset The storage quantity saves the storage space of the aircraft.

FIG. 4 is a schematic structural diagram of a computing device according to an embodiment of the present application. Referring to FIG. 7 , a computing device 400 includes a memory 410 and a processor 420 .

The processor 420 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), on-site Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

The memory 410 may include various types of storage units, such as system memory, read only memory (ROM), and persistent storage. Wherein, the ROM can store static data or instructions required by the processor 420 or other modules of the computer. The persistent storage device may be a readable and writable storage device. Persistent storage may be a non-volatile storage device that does not lose stored instructions and data even if the computer is powered off. In some embodiments, the permanent storage device adopts a large-capacity storage device (such as a magnetic or optical disk, flash memory) as the permanent storage device. In some other implementations, the permanent storage device may be a removable storage device (such as a floppy disk, an optical drive). The system memory can be a readable and writable storage device or a volatile readable and writable storage device, such as dynamic random access memory. System memory can store some or all of the instructions and data that the processor needs at runtime. In addition, memory 410 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and magnetic and/or optical disks may also be used. In some embodiments, memory 410 may include a readable and/or writable removable storage device, such as a compact disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual-layer DVD-ROM), Read-Only Blu-ray Disc, Super Density Disc, Flash memory card (such as SD card, min SD card, Micro-SD card, etc.), magnetic floppy disk, etc. Computer-readable storage media do not contain carrier waves and transient electronic signals transmitted by wireless or wire.

Executable codes are stored in the memory 410 , and when the executable codes are processed by the processor 420 , the processor 420 can be made to execute part or all of the methods mentioned above.

Fig. 5 is a schematic structural diagram of an aircraft positioning and navigation system shown in an embodiment of the present application.

Referring to FIG. 5 , an aircraft positioning and navigation system includes the above-mentioned computing device 400; and

The execution unit 500 is configured to execute a flight control command to make the aircraft descend to the ground area corresponding to the target tile, wherein the flight control command is generated according to the positioning and navigation data obtained by the computing device 400 .

It will be appreciated that in some embodiments, computing device 400 is a flight controller. In some other embodiments, the computing device is a data processing device dedicated to the above-mentioned positioning and navigation method, and outputs the result to the flight controller after obtaining the positioning and navigation result.

In one embodiment, the computing device 400 obtains the real-time flight map data generated during the current flight of the aircraft, and judges whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data, if It is determined that the current flight area is a known area, and the positioning and navigation data of the aircraft are obtained according to the pre-stored historical flight map data.

In one embodiment, the computing device 400 obtaining the real-time flight map data generated during the current flight of the aircraft includes:

Obtain the aerial survey terrain data of the aircraft aligned in time, and the state parameters of the aircraft; wherein, the aerial survey terrain data of the aircraft include radar detection terrain fluctuation data, and the state parameters of the aircraft include real-time position and attitude data of the aircraft;

According to aerial survey terrain data and status parameters, real-time flight map data of grid type is generated. The real-time flight map data of grid type includes grid position data and terrain feature data corresponding to grid. The grid position estimation data obtained from the attitude data, and the terrain feature data include radar object identification tags obtained from the radar detection terrain relief data.

In one embodiment, the computing device 400 judges whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data, including:

Perform feature matching on the flight map data corresponding to the grid to be matched in the real-time flight map data and the pre-stored historical flight map data;

According to the result of feature matching, it is judged whether the current flight area is an area that the aircraft has flown or whether it is an area for sharing flight map data.

In one embodiment, the computing device 400 obtains the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data. flight path data for flight control.

Fig. 6 is a schematic structural diagram of an aircraft positioning and navigation system shown in another embodiment of the present application.

Referring to FIG. 6 , an aircraft positioning and navigation system includes: the above-mentioned computing device 400 , an execution unit 500 , an altimeter 600 , an aerial terrain detection device 700 , and an inertial measurement unit 800 .

The altimeter 600 is used to collect the real-time ground altitude of the aircraft during the flight of the aircraft;

The aerial survey terrain detection device 700 is used to collect terrain data during the flight of the aircraft; in this embodiment, the aerial survey terrain control device 700 includes a laser radar 710;

The inertial measurement unit 800 is used to collect real-time pose data of the aircraft during flight.

In some embodiments, the aerial terrain detection device further includes an image acquisition device 720, configured to collect ground images in real time during the flight of the aircraft, so as to obtain terrain visual feature data and/or terrain visual semantic feature data as part of the real-time flight map data.

In some embodiments, the aircraft further includes a GNSS positioning module 900, configured to obtain GNSS position data of the aircraft during flight of the aircraft, so as to obtain grid-corresponding GNSS positioning data as part of the real-time flight map data.

The present application also provides an aircraft, including the above-mentioned aircraft positioning and navigation system.

With regard to the aircraft positioning and navigation system in the above embodiments, the specific manner in which each module, device or unit performs operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

In addition, the method according to the present application can also be implemented as a computer program or computer program product, which includes computer program code instructions for executing some or all of the steps in the above-mentioned method of the present application.

Alternatively, the present application may also be implemented as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium), on which executable code (or computer program, or computer instruction code) is stored. ), when the executable code (or computer program, or computer instruction code) is executed by the processor of the electronic device (or electronic device, server, etc.), causing the processor to perform part or all of the steps of the above-mentioned method according to the present application .

Having described various embodiments of the present application above, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principle of each embodiment, practical application or improvement of technology in the market, or to enable other ordinary skilled in the art to understand each embodiment disclosed herein.

Claims

A positioning and navigation method for an aircraft, characterized in that it comprises:

Obtaining real-time flight map data generated during the current flight of the aircraft, the real-time flight map data including terrain data;

judging whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data;

If it is determined that the current flight area is a known area, the positioning and navigation data of the aircraft is obtained according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data.
The method according to claim 1, wherein said obtaining the real-time flight map data generated in this flight of said aircraft comprises:

Obtain the aerial survey terrain data of the aircraft and the state parameters of the aircraft that are aligned in time; wherein, the aerial survey terrain data of the aircraft include radar detection terrain fluctuation data, and the state parameters of the aircraft include real-time pose data of the aircraft ;

According to the aerial survey terrain data and state parameters, generate grid-type real-time flight map data, the grid-type real-time flight map data includes grid position data and grid corresponding terrain feature data, wherein the grid The location data includes grid location estimation data obtained from the real-time pose data, and the terrain feature data includes radar object identification tags obtained from the radar detected terrain relief data.
The method according to claim 2, characterized in that:

The terrain feature data also includes a priori geographic location data; and/or,

The aerial survey terrain data also includes map image data that is temporally and spatially aligned with the radar-detected terrain relief data, and the terrain feature data also includes terrain visual feature data and/or terrain visual semantics obtained from the ground image data characteristic data; and/or,

The state parameter of the aircraft also includes GNSS positioning data of the aircraft, and the grid position data also includes GNSS positioning data corresponding to the grid.
The method according to claim 3, wherein the judging whether the current flight area is a known area according to the terrain data in the real-time flight map data and the pre-stored historical flight map data comprises:

Determine the grid to be matched according to the terrain feature data in the real-time flight map data;

performing feature matching on the flight map data corresponding to the grid to be matched in the real-time flight map data and the pre-stored historical flight map data;

According to the result of the feature matching, it is judged whether the current flight area is the area that the aircraft has flown or whether it is the flight map data sharing area.
The method according to any one of claims 1 to 4, wherein said obtaining the real-time flight map data generated during the flight of said aircraft comprises:

Obtaining the current frame flight map data generated during the current flight of the aircraft and the time-lapse flight map data before the current frame;

The current frame flight map data and the time-lapse flight map data are fused to obtain the time-lapse flight map data including the current frame.
The method according to claim 5, wherein said merging the current frame flight map data generated in the current flight of the aircraft with the time-lapse flight map data before the current frame includes:

performing compression processing on the current frame of flight map data generated during the current flight of the aircraft, so as to convert the data of the three-dimensional grid type into two-dimensional grid type data, and retain the terrain in the current frame of flight map data characteristic information;

The current frame flight map data of the two-dimensional grid type is fused with the time-lapse flight map data of the two-dimensional grid type before the current frame.
The method according to any one of claims 1 to 4, wherein the method further comprises:

If it is determined that the current flight area is not a known area, obtain differential map data between the real-time flight map data and the pre-stored historical flight map data;

The pre-stored historical flight map data is updated according to the differential map data; and/or, the differential map data is uploaded to a cloud server, so that the cloud server updates the shared historical flight map data.
The method according to any one of claims 1 to 4, wherein the obtaining the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data, comprises:

Generating dynamic flight route data of the aircraft in real time according to the pre-stored historical flight map data, so as to perform flight control according to the dynamic flight route data.
The method according to any one of claims 1 to 4, wherein the obtaining the positioning and navigation data of the aircraft according to the pre-stored historical flight map data, so as to perform flight control according to the positioning and navigation data, comprises:

Pre-generated memory flight path data is obtained from the pre-stored historical flight map data, so as to perform flight control according to the memory flight path data.
The method according to claim 7, wherein if it is determined that the current flight area is not a known area, the method further comprises:

According to part or all of the mission data, status data, and flight control data of the current flight of the aircraft, generate memory flight route data;

The pre-stored historical flight map data is updated according to the stored flight route data; and/or, the stored flight route data is uploaded to a cloud server, so that the cloud server updates the cloud historical flight map data.
A computing device, characterized by comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, when the computer program is executed by the processor, the computer program according to claim 1 can be realized. to the method described in any one of 10.
An aircraft positioning and navigation system is characterized in that it comprises:

The computing device of claim 11; and

The execution unit is configured to execute the flight control instruction, wherein the flight control instruction is generated according to the positioning and navigation data obtained by the computing device.
The system according to claim 12, further comprising:

An altimeter, used to collect the real-time altitude of the aircraft during the flight of the aircraft;

An aerial survey terrain detection device is used to collect terrain data during the flight of the aircraft; the aerial survey terrain control device includes a laser radar;

The inertial measurement unit is used to collect real-time pose data of the aircraft during the flight of the aircraft.
The system of claim 13, wherein:

The aerial survey terrain detection device also includes an image acquisition device, which is used to collect ground images in real time during the flight of the aircraft, so as to obtain terrain visual feature data and/or terrain visual semantic feature data as part of the real-time flight map data; and/or or,

The system also includes a GNSS positioning module, which is used to obtain GNSS position data of the aircraft during the flight of the aircraft, so as to obtain the corresponding GNSS positioning data of the grid as a part of the real-time flight map data.
An aircraft, characterized by comprising the aircraft positioning and navigation system according to claims 12-14.