CN113157848A - Method and device for determining air route, electronic equipment and storage medium - Google Patents
Method and device for determining air route, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure relates to a method and a device for determining an airway, an electronic device and a storage medium, wherein the method comprises the following steps: removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information; according to a preset spatial sampling density, respectively carrying out spatial resampling on the plurality of first track information to obtain a plurality of second track information; clustering track points of the second track information according to the number of the preset peaks of the airway to obtain target position information of the peaks of the airway; and determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information. According to the method for determining the air route, the track information to be processed is processed, and compared with the image processing, the processing efficiency is improved. Through the processing of removing isolated points, noise is reduced, and the positions of track points in the air route information are obtained through spatial resampling and clustering, so that the direction information is determined.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for determining an airway, an electronic device, and a storage medium.
Background
Although the route of equipment such as an aircraft or a ship is usually preset, the preset route is a global route map and cannot reflect the local detailed route of the aircraft or the ship. In the related art, when determining a local detail airway, a series of processing such as image expansion, erosion, refinement and the like is generally performed by an image processing method based on a track imaging mode to form airway geometric data. However, the imaging process is inefficient to execute, is sensitive to noise, and may generate a non-existent road segment, and the imaging processing method cannot better identify two closer routes, which easily causes a plurality of closer routes to be identified as one route, and in addition, the "circle" shaped route structure is easily extracted by mistake into a "point" shaped route structure, which results in a low extraction accuracy.
Disclosure of Invention
The disclosure provides a method and a device for determining an airway, electronic equipment and a storage medium.
According to an aspect of the present disclosure, there is provided a route determination method, including: removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information, wherein the track information to be processed comprises position information and direction information of the plurality of track points; according to a preset spatial sampling density, respectively carrying out spatial resampling on the plurality of first track information to obtain a plurality of second track information; clustering track points of the second track information according to the number of the preset peaks of the airway to obtain target position information of the peaks of the airway; and determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information.
In a possible implementation manner, removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information includes: determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold; and removing the isolated track points to obtain the first track information.
In a possible implementation manner, determining isolated track points in a plurality of pieces of track information to be processed according to a preset domain radius and a preset number threshold includes: respectively determining a first number of track points in a neighborhood radius range of each track point; and determining the track points with the first number smaller than a preset number threshold value as the isolated track points.
In a possible implementation manner, clustering track points of the plurality of second track information according to the number of preset vertexes of the airway, and obtaining the target position information of the vertexes of the airway includes: determining the number of clustering centers according to the number of the top points of the preset airway; clustering track points of the second track information according to the number of the clustering centers to obtain a plurality of first clustering centers; merging the first clustering centers with the distances smaller than or equal to a distance threshold value to obtain a plurality of second clustering centers; and determining the position information of the second cluster center as the target position information of the top point of the air route.
In a possible implementation manner, determining, according to direction information of track points in the second track information, target direction information of vertices of the route includes: determining a second clustering center corresponding to a plurality of track points in the second track information; determining the direction information of the corresponding second clustering center according to the direction information of the track points in the second track information; and determining the direction information of the second cluster center as the target direction information of the top point of the air route.
In one possible implementation, the method further includes: determining outlier track points in the historical track information according to the position information of the plurality of track points in the historical track information; and removing outlier track points in the historical track information, and performing Kalman filtering processing on the position information of the residual track points to obtain the track information to be processed.
According to an aspect of the present disclosure, there is provided an airway determination device including: the device comprises a removing module, a processing module and a processing module, wherein the removing module is used for removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information, and the track information to be processed comprises position information and direction information of the track points; the resampling module is used for respectively performing spatial resampling on the plurality of first track information according to a preset spatial sampling density to obtain a plurality of second track information; the clustering module is used for clustering track points of the second track information according to the number of the vertexes of the preset airway to obtain target position information of the vertexes of the airway; and the direction determining module is used for determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information.
In one possible implementation, the removing module is further configured to: determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold; and removing the isolated track points to obtain the first track information.
In one possible implementation, the removing module is further configured to: respectively determining a first number of track points in a neighborhood radius range of each track point; and determining the track points with the first number smaller than a preset number threshold value as the isolated track points.
In one possible implementation, the clustering module is further configured to: determining the number of clustering centers according to the number of the top points of the preset airway; clustering track points of the second track information according to the number of the clustering centers to obtain a plurality of first clustering centers; merging the first clustering centers with the distances smaller than or equal to a distance threshold value to obtain a plurality of second clustering centers; and determining the position information of the second cluster center as the target position information of the top point of the air route.
In one possible implementation, the direction determining module is further configured to: determining a second clustering center corresponding to a plurality of track points in the second track information; determining the direction information of the corresponding second clustering center according to the direction information of the track points in the second track information; and determining the direction information of the second cluster center as the target direction information of the top point of the air route.
In one possible implementation, the apparatus further includes: the preprocessing module is used for determining outlier track points in the historical track information according to the position information of the plurality of track points in the historical track information; and removing outlier track points in the historical track information, and performing Kalman filtering processing on the position information of the residual track points to obtain the track information to be processed.
According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.
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 disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.
FIG. 1 shows a flow chart of a method of route determination according to an embodiment of the present disclosure;
FIG. 2 shows a schematic diagram of isolated trace points, according to an embodiment of the present disclosure;
FIG. 3 shows a schematic diagram of spatial resampling, according to an embodiment of the disclosure;
fig. 4A and 4B show schematic diagrams of a clustering process according to an embodiment of the present disclosure;
FIGS. 5A and 5B illustrate application diagrams of a method of determining a route according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram of a route determination device according to an embodiment of the present disclosure;
FIG. 7 shows a block diagram of an electronic device according to an embodiment of the disclosure;
fig. 8 illustrates a block diagram of an electronic device in accordance with an embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
Fig. 1 shows a flowchart of a route determination method according to an embodiment of the present disclosure, and as shown in fig. 1, the image processing method includes:
in step S11, removing isolated track points in a plurality of pieces of track information to be processed, and obtaining a plurality of pieces of first track information, where the track information to be processed includes position information and direction information of the plurality of track points;
in step S12, according to a preset spatial sampling density, performing spatial resampling on the plurality of first trajectory information, respectively, to obtain a plurality of second trajectory information;
in step S13, clustering track points of the plurality of second track information according to the number of vertices of the preset route, to obtain target position information of the vertices of the route;
in step S14, target direction information of the vertex of the route is determined according to the direction information of the track point in the second track information.
According to the method for determining the air route, the track information to be processed is processed, compared with the image processing, the processing efficiency is improved, the noise is reduced through the processing of removing the isolated points, the positions of the vertexes in the air route information are obtained through spatial resampling and clustering, the direction information is further determined, and the air route can be obtained. Namely, the airway can be obtained by processing data such as position information, direction information and the like in the track information without processing images, so that the error of image recognition is avoided, and the accuracy of the airway is improved.
In one possible implementation, the route determining method may be performed by an electronic device such as a terminal device or a server, the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor calling a computer readable instruction stored in a memory. Alternatively, the method may be performed by a server.
In one possible implementation, a route may be preset for a vehicle, such as an aircraft, a ship, a vehicle, etc., and the vehicle may be caused to navigate the preset route. However, the preset route is a global route, i.e., only the general direction in which the vehicle travels can be set, but the specific route of the vehicle cannot be determined. For example, the route of the vehicle may be set so that the vehicle can reach the point B from the point a, but during the traveling of the vehicle, an obstacle may be avoided, a congested road segment may be avoided, and the specific route may be changed. For another example, the route of the aircraft may be set so that the aircraft flies from city C to city D, but during the flight, a local deviation may occur, for example, to avoid airflow, birds, etc. temporarily deviating from the route. And the air route of the aircraft is a preset abstract route, namely, the air route of the aircraft has no limitation of tracks or road surfaces and the like, but is an abstract route invisible to naked eyes. Therefore, it is difficult to study the route of the aircraft, determine whether the aircraft is abnormal or whether a preset route is abnormal based on the route, and perform processes such as tracking, recognition, and trajectory prediction for an unknown aircraft.
Based on the above problem, the historical track information of the vehicle (e.g., aircraft) is recorded, and the route of the vehicle is analyzed based on the historical track information, so that the route can be applied to the fields of identification and tracking of the aircraft, and the like.
In one possible implementation, historical trajectory information of the vehicle may be recorded, for example, location information of track points during navigation of the vehicle, as well as directional information. In an example, the position information of a vehicle (i.e., the position information of track points) can be recorded every 10 seconds, and the direction information is determined, for example, the position information of 6 track points of a certain vehicle is recorded within 1 minute, and the navigation direction thereof is from track point 1 to track point 2, from track point 2 to track point 3, from track point 3 to track point 4, from track point 4 to track point 5, and from track point 5 to track point 6.
In one possible implementation, historical trajectory information may be recorded for a plurality of vehicles (e.g., a plurality of aircraft), or historical trajectory information may be recorded for multiple flights of a vehicle. Further, the historical trajectory information may be analyzed to determine the route of the vehicle.
In one possible implementation, the method further includes: determining outlier track points in the historical track information according to the position information of the plurality of track points in the historical track information; and removing outlier track points in the historical track information, and performing Kalman filtering processing on the position information of the residual track points to obtain the track information to be processed.
In a possible implementation manner, the historical track information can be preprocessed to reduce noise interference in the historical track information and improve the accuracy of analyzing the track information. In an example, outlier track points in the historical track information can be determined based on statistical principles and removed.
In an example, fitting or regression processing can be performed on a plurality of track points according to position information of the plurality of track points in historical track information, a fitting curve or a regression curve can be obtained through the fitting or regression processing, the plurality of track points can be distributed near the fitting curve or the regression curve, the distance between the positions of the plurality of track points and the fitting curve or the regression curve accords with Gaussian distribution, and outlier track points can be screened through the characteristics. For example, in a case where the distance between the position of the trajectory point and the fitted curve or the regression curve conforms to a gaussian distribution, the farther the distance between the position of the trajectory point and the fitted curve or the regression curve is, the lower the confidence is, and the trajectory point whose confidence is less than or equal to the confidence threshold may be taken as the outlier. For example, when the distance between the trajectory point and the fitted curve or the regression curve is greater than or equal to the distance threshold, the confidence thereof is less than or equal to the confidence threshold (e.g., 0.3%, etc.), then the trajectory point having the distance from the fitted curve or the regression curve greater than or equal to the distance threshold may be determined as an outlier trajectory point.
In one possible implementation, outlier track points may be removed from historical track information. And direction information is determined based on remaining track point, for example, including 6 track points in the historical track information, direction information is from track point 1 to track point 2, from track point 2 to track point 3, from track point 3 to track point 4, from track point 4 to track point 5, from track point 5 to track point 6. Through above-mentioned processing, can confirm track point 4 and be outlier track point, then after getting rid of outlier track point, can be from track point 1 to track point 2 with direction information determination, from track point 2 to track point 3, from track point 3 to track point 5, from track point 5 to track point 6.
In a possible implementation manner, kalman filtering processing may be performed on the position information of the remaining track points to further reduce noise interference, optimize the position information of each track point, and obtain the track information to be processed. And the trajectory information to be processed corresponding to a plurality of pieces of historical trajectory information (for example, historical trajectory information recorded for the same vehicle a plurality of times, or historical trajectory information recorded for a plurality of vehicles) can be obtained by the above method.
Through the mode, outliers in historical track information can be removed, the position information of track points can be further optimized through Kalman filtering, and the accuracy of the air route is improved.
In one possible implementation, after obtaining the trajectory information to be processed, the trajectory information to be processed may be further optimized. For example, isolated trace points may be further determined in the plurality of information to be processed. For example, in the course of navigation, if a plurality of vehicles pass through a certain position at a certain time, a plurality of track points of information to be processed may be recorded near the position, and if no track point closer to the position exists in a certain track information to be processed at the time, an isolated track point may exist in the track information to be processed. The isolated track points deviate from the route determined by the plurality of pieces of track information to be processed, so that the reference value is low, noise interference is formed, and the isolated track points can be removed.
In one possible implementation, step S11 may include: determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold; and removing the isolated track points to obtain the first track information.
In a possible implementation manner, an isolated trace point, that is, a trace point far from other trace points, may be determined in a plurality of trace points of a plurality of to-be-processed trace information. For example, the number of trace points near each trace point may be determined separately, and if the number is small, the trace point is located far away from most of the other trace points, i.e., the trace point may be determined as an isolated trace point. This step may include: respectively determining a first number of track points in a neighborhood radius range of each track point; and determining the track points of which the first number is less than or equal to a preset number threshold value as the isolated track points.
In one possible implementation, the neighborhood radius and the preset number may be set, and the number of track points within the neighborhood radius range of each track point may be determined separately. If the number of the track points in the neighborhood radius range is small, the track point can be determined to be far away from most other track points. For example, a number threshold may be set, and if the first number of trace points within the domain radius range of a certain trace point is smaller than the number threshold, the trace point may be determined to be an isolated trace point.
Fig. 2 shows a schematic diagram of isolated track points according to an embodiment of the present disclosure, and as shown in fig. 2, the plurality of to-be-processed track information may include a plurality of track points, and a first number of track points within a preset domain radius range of each track point may be determined respectively. And a quantity threshold value can be set, and if the first quantity of the track points in the neighborhood radius range of a certain track point is smaller than the quantity threshold value, the track point can be determined as an isolated track point. In an example, the number threshold may be set to 2, except for the track point a, the number of track points in the neighborhood radius range of other track points is greater than or equal to 2, and the neighborhood radius range of the track point a (the range shown by the circular dotted line around the track point a) has no other track points, that is, the number of other track points in the neighborhood radius range of the track point a is 0, and therefore, the track point a may be determined to be an isolated track point.
In an example, after determining the isolated track points, the isolated track points can be removed and the direction information in the track information can be adjusted. For example, after removing the isolated track point a, the direction information may be determined to be directed by an adjacent track point before the track point a to an adjacent track point after the track point a (as indicated by the straight dashed line in fig. 1). After the isolated track points are removed and the direction information is adjusted, first track information can be obtained.
Through the mode, the isolated track points far away from other track points can be determined through the neighborhood radius and the quantity threshold, so that the isolated track points are removed, the noise interference can be further reduced, and the accuracy of the air route is improved.
In an example, when obtaining the historical trajectory information, sampling is generally performed at preset time intervals, that is, in a plurality of pieces of historical trajectory information, time intervals of sampling points (i.e., trajectory points) are uniform, but since speeds of vehicles may be non-uniform, spatial intervals may be non-uniform. If the speed difference of the vehicles is large, the spatial interval difference of the track points in each historical track information may be large, that is, the spatial density difference of the track points in each historical track information is large in the same road section.
In a possible implementation manner, based on the above problem, the position information of the track points in the plurality of first track information may be further optimized, and in step S12, the first track information may be spatially resampled. That is, the route determined based on each piece of first trajectory information is resampled at the same spatial sampling density, and a plurality of pieces of second trajectory information having the same spatial density of the trajectory points in the same link can be obtained.
Fig. 3 shows a schematic diagram of spatial resampling according to an embodiment of the disclosure. Before spatial resampling, the spatial density difference between the first track information is large, that is, the difference between the number of the collected track points is large in the same road section. Resampling may be performed based on a preset spatial density, for example, a route may be determined according to track points in each first track information, and resampling may be performed on the route according to the preset spatial sampling density, as shown in fig. 3, a plurality of second track information with the same spatial density of the track points may be obtained, that is, the second track information with the same number of collected track points in the same road segment.
Through the mode, a plurality of second track information with the same space density can be obtained through space resampling, so that the number of track points of each second track information in the same road section is the same, the characteristics of each second track information are favorably analyzed, and the accuracy of the air route is improved.
In one possible implementation, the airway may be determined based on a plurality of second trajectory information. First, target position information of a vertex of the airway can be determined based on position information of the track point in the plurality of second track information. Step S13 may include: determining the number of clustering centers according to the number of the top points of the preset airway; clustering track points of the second track information according to the number of the clustering centers to obtain a plurality of first clustering centers; merging the first clustering centers with the characteristic distance smaller than or equal to a distance threshold value to obtain a plurality of second clustering centers; and determining the position information of the second cluster center as the target position information of the top point of the air route.
In an example, the number of track points in the airway may be preset, and the number of track points in the second track information may be referred to when the number of track points in the airway is set. For example, after spatial resampling processing, the number of track points included in each second track information is the same, and the number of track points in the fairway can be made equal to the number of track points in the second track information. The present disclosure does not limit the number of track points in the airway. The number of track points in the airway can be used as the number of cluster centers in the clustering process.
In a possible implementation manner, in the clustering process, the first clustering center may be obtained based on a plurality of track points closer to each other in the plurality of second track information. For example, the first and second trace information may include a plurality of trace points { a }1,a2,…anN is a positive integer, and the second track information may include a plurality of track points { b }1,b2,…bnThe third second track information may include a plurality of track points { c }1,c2,…cn}. After the spatial resampling is carried out, the trace point a1And the track point b1And locus point c1Is relatively close to the track point a2And the track point b2And locus point c2When the distance of (2) is short and … … is set, the number of the clustering centers can be set as n, and track points a can be obtained through clustering1And the track point b1And locus point c1Cluster center d of1Points of track a2And the track point b2And locus point c2Cluster center ofd2… … tracing point anAnd the track point bnAnd locus point cnCluster center d ofn. The present disclosure does not limit the manner of clustering.
In one possible implementation, if there are cluster centers that are spatially closer among the plurality of first cluster centers, the spatially closer first cluster centers may be merged to reduce redundant data for subsequent analysis. For example, the average position of two or more first cluster centers that are closer may be selected as the position of the merged cluster center. In an example, a distance threshold may be set, and first cluster centers having a distance threshold less than or equal to the distance threshold are merged, and a plurality of second cluster centers may be obtained. The location information of the second cluster center may be determined as target location information of a vertex of the airway.
Fig. 4A and 4B show schematic diagrams of a clustering process according to an embodiment of the present disclosure. As shown in fig. 4A, the track points of the second track information may be clustered to obtain a plurality of first cluster centers, where there are two first cluster centers whose distance is smaller than the distance threshold (for example, the 7 th and 8 th first cluster centers from the left), and the two first cluster centers may be merged to obtain a plurality of second cluster centers as shown in fig. 4B. And the position information of the second cluster center is the target position information of the top point of the air route.
In one possible implementation, after determining the target location information for the vertices in the airway, target direction information may also be determined. The target direction information of the top point of the airway can be determined based on the direction information of the track point in the second track information. Step S14 may include: determining a second clustering center corresponding to a plurality of track points in the second track information; determining the direction information of the corresponding second clustering center according to the direction information of the track points in the second track information; and determining the direction information of the second cluster center as the target direction information of the top point of the air route.
In a possible implementation manner, the second clustering center is obtained by clustering track points in the plurality of second track information, and the second clustering center and the track points in the second track information have a corresponding relationship, so that the direction information of the second clustering center can be determined based on the direction information of the track points in the second track information, and further, the target direction information of the top point of the fairway is determined.
In an example, the track points of the second track information include { a }1,a2,…an}、{b1,b2,…bn}、{c1,c2,…cnAnd the second clustering center obtained according to the clustering processing is { d }1,d2,…dmM is a positive integer less than or equal to n, wherein the second cluster center d1Is a track point a based on the second track information1、b1And c1Obtained by clustering, the second cluster center d2Is a track point a based on the second track information2、b2And c2… … second clustering center d obtained by clusteringk(k is a positive integer less than or equal to m) is a track point a of the second track informationk、bkAnd ckA first clustering center obtained after clustering, and a track point a of the second track informationk+1、bk+1And ck+1… … obtained by merging the first clustering centers obtained after clustering, therefore, the second clustering centers have corresponding relations with the track points of the second track information.
In an example, the direction information of the second cluster center may be determined based on the direction information of the second track information, e.g., the direction information of the second track information is from a1To a2From a2To a3… … the direction information of the second cluster center is d1To d2From d2To d3… … further, the directional information of the second cluster center may be determined to be the directional information of the top of the airway.
According to the method for determining the air route, the outliers in the historical track information can be removed, the position information of the track points can be further optimized through Kalman filtering, the accuracy of the air route is improved, the isolated track points far away from other track points can be determined through the neighborhood radius and the quantity threshold, the isolated track points are removed, and the noise interference can be further reduced. Furthermore, a plurality of second track information with the same space density can be obtained through space resampling, so that the number of track points of each second track information in the same road section is the same, the analysis of the characteristics of each second track information is facilitated, and the accuracy of the air route is improved. And the target position information of the top point of the airway can be obtained through clustering processing, and the target direction information of the top point of the airway can be determined through the direction information of the second track information. By processing the track information to be processed, compared with processing the image, the processing efficiency is improved, the airway can be obtained by processing the data such as the position information, the direction information and the like in the track information, the image does not need to be processed, the error of image recognition is avoided, and the accuracy of the airway is improved.
Fig. 5A and 5B show application diagrams of a route determination method according to an embodiment of the present disclosure. As shown in fig. 5A, the historical track information of multiple aircraft may be preprocessed, for example, outlier track points in the historical track information may be removed, and kalman filtering processing may be performed on the position information of the remaining track points to obtain the track information to be processed.
In a possible implementation manner, isolated track points in the track information to be processed can be further removed, for example, whether the track points are isolated track points can be determined by determining the number of other track points in the neighborhood radius range of the track points, and if the track points are isolated track points, the isolated track points are removed to obtain the first track information.
In one possible implementation, the route may be determined based on a plurality of first trajectory information. The track points in the first track information may be obtained by sampling at fixed time intervals. If the speed difference of the aircraft is large, the spatial density difference of the track points in each first track information is large, and each first track information can be subjected to spatial resampling to obtain second track information with consistent spatial density.
In a possible implementation manner, the number of the clustering centers may be determined based on the number of the track points in the second track information, the track points of the plurality of second track information may be clustered based on the number, the clustering centers with a short distance may be merged, the positions of the clustering centers may be optimized, and the target position information of the top point in the air route may be obtained. Further, the direction information of the vertex of the route may be determined based on the direction information of the second trajectory information based on the correspondence relationship of the trajectory point of the second trajectory information and the vertex of the route. Further, a route pattern of the route, for example, a route pattern with direction information as shown in fig. 5B, can be obtained.
In one possible implementation, the route determining method can be used for determining the route of vehicles such as an aircraft, and further researching the property, performance and the like of the aircraft based on the route. The application range of the route determining method is not limited by the disclosure.
Fig. 6 shows a block diagram of a route determination device according to an embodiment of the present disclosure, which, as shown in fig. 6, includes: the device comprises a removing module, a processing module and a processing module, wherein the removing module is used for removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information, and the track information to be processed comprises position information and direction information of the track points; the resampling module is used for respectively performing spatial resampling on the plurality of first track information according to a preset spatial sampling density to obtain a plurality of second track information; the clustering module is used for clustering track points of the second track information according to the number of the vertexes of the preset airway to obtain target position information of the vertexes of the airway; and the direction determining module is used for determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information.
In one possible implementation, the removing module is further configured to: determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold; and removing the isolated track points to obtain the first track information.
In one possible implementation, the removing module is further configured to: respectively determining a first number of track points in a neighborhood radius range of each track point; and determining the track points with the first number smaller than a preset number threshold value as the isolated track points.
In one possible implementation, the clustering module is further configured to: determining the number of clustering centers according to the number of the top points of the preset airway; clustering track points of the second track information according to the number of the clustering centers to obtain a plurality of first clustering centers; merging the first clustering centers with the distances smaller than or equal to a distance threshold value to obtain a plurality of second clustering centers; and determining the position information of the second cluster center as the target position information of the top point of the air route.
In one possible implementation, the direction determining module is further configured to: determining a second clustering center corresponding to a plurality of track points in the second track information; determining the direction information of the corresponding second clustering center according to the direction information of the track points in the second track information; and determining the direction information of the second cluster center as the target direction information of the top point of the air route.
In one possible implementation, the apparatus further includes: the preprocessing module is used for determining outlier track points in the historical track information according to the position information of the plurality of track points in the historical track information; and removing outlier track points in the historical track information, and performing Kalman filtering processing on the position information of the residual track points to obtain the track information to be processed.
It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.
In addition, the present disclosure also provides an airway determining device, an electronic device, a computer-readable storage medium, and a program, which can be used to implement any one of the airway determining methods provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions in the methods section are not repeated.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.
An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
The embodiments of the present disclosure also provide a computer program product, which includes computer readable code, and when the computer readable code runs on a device, a processor in the device executes instructions for implementing the image processing method provided in any one of the above embodiments.
The embodiments of the present disclosure also provide another computer program product for storing computer readable instructions, which when executed cause a computer to perform the operations of the image processing method provided in any of the above embodiments.
The electronic device may be provided as a terminal, server, or other form of device.
Fig. 7 illustrates a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.
Referring to fig. 7, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense an edge of a touch or slide action, but also detect a duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.
Fig. 8 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 8, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may further include a power component 1926 configured to perform power management of the electronic device 1900, and a wired or wireless network interface 1950 configuredFor connecting the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system, such as Windows Server, stored in memory 1932TM，Mac OS XTM，UnixTM,LinuxTM，FreeBSDTMOr the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations 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 in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method for determining a route, comprising:
removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information, wherein the track information to be processed comprises position information and direction information of the plurality of track points;
according to a preset spatial sampling density, respectively carrying out spatial resampling on the plurality of first track information to obtain a plurality of second track information;
clustering track points of the second track information according to the number of the preset peaks of the airway to obtain target position information of the peaks of the airway;
and determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information.
2. The method according to claim 1, wherein removing isolated track points from the plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information comprises:
determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold;
and removing the isolated track points to obtain the first track information.
3. The method according to claim 2, wherein determining the isolated trajectory points in the plurality of pieces of trajectory information to be processed according to a preset domain radius and a preset number threshold comprises:
respectively determining a first number of track points in a neighborhood radius range of each track point;
and determining the track points with the first number smaller than a preset number threshold value as the isolated track points.
4. The method according to claim 1, wherein clustering track points of the plurality of second track information according to a preset number of vertices of the airway, and obtaining target position information of the vertices of the airway comprises:
determining the number of clustering centers according to the number of the top points of the preset airway;
clustering track points of the second track information according to the number of the clustering centers to obtain a plurality of first clustering centers;
merging the first clustering centers with the distances smaller than or equal to a distance threshold value to obtain a plurality of second clustering centers;
and determining the position information of the second cluster center as the target position information of the top point of the air route.
5. The method according to claim 4, wherein determining the target direction information of the vertex of the fairway according to the direction information of the track point in the second track information comprises:
determining a second clustering center corresponding to a plurality of track points in the second track information;
determining the direction information of the corresponding second clustering center according to the direction information of the track points in the second track information;
and determining the direction information of the second cluster center as the target direction information of the top point of the air route.
6. The method of claim 1, further comprising:
determining outlier track points in the historical track information according to the position information of the plurality of track points in the historical track information;
and removing outlier track points in the historical track information, and performing Kalman filtering processing on the position information of the residual track points to obtain the track information to be processed.
7. An airway specification device, comprising:
the device comprises a removing module, a processing module and a processing module, wherein the removing module is used for removing isolated track points in a plurality of pieces of track information to be processed to obtain a plurality of pieces of first track information, and the track information to be processed comprises position information and direction information of the track points;
the resampling module is used for respectively performing spatial resampling on the plurality of first track information according to a preset spatial sampling density to obtain a plurality of second track information;
the clustering module is used for clustering track points of the second track information according to the number of the vertexes of the preset airway to obtain target position information of the vertexes of the airway;
and the direction determining module is used for determining the target direction information of the top point of the air route according to the direction information of the track point in the second track information.
8. The apparatus of claim 7, wherein the removal module is further configured to: determining isolated track points in a plurality of pieces of track information to be processed according to a preset field radius and a preset quantity threshold; and removing the isolated track points to obtain the first track information.
9. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the memory-stored instructions to perform the method of any of claims 1 to 6.
10. A computer readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1 to 6.
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