Signal strength prediction method, program product, equipment and medium

Abstract

The embodiment of the invention provides a signal strength prediction method, a program product, equipment and a medium. The method comprises the following steps: acquiring a signal data set of a plurality of first signal points in a space region; the spatial region comprises a plurality of signal points, and screening out second signal points of which the signal intensity is not obtained from the plurality of signal points; for each second signal point, establishing a target sphere by taking the second signal point as a sphere center, and determining a plurality of target first signal points forming a target geometric figure on the surface of the target sphere; the second signal point is included by the target geometric figure; and determining the target signal strength of the target first signal point from the signal data set, and determining the signal strength of the second signal point based on the target signal strength. Therefore, signal intensity prediction of an unknown area is realized.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a signal strength prediction method, program product, device and medium. Background Art

[0002] During flight, drones have the ability to plan routes in real time based on the surrounding environment. However, route planning relies on the knowledge of regional signal strength. In practice, drones can only collect signal strength in areas they pass through, and cannot determine signal strength in areas they do not pass through, which limits the drone's route planning for areas it has not passed through. Furthermore, when a drone needs to change its flight route, if the signal strength in the area it passes through cannot be confirmed, this will cause the drone's communication to be disconnected, and in severe cases, damage to the drone. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a signal strength prediction method, program product, device and medium to achieve the technical effect of signal prediction.

[0004] A first aspect of an embodiment of the present application provides a signal strength prediction method, the method comprising: Acquire a signal data set of a plurality of first signal points in a spatial region; wherein the spatial region includes a plurality of signal points, and the first signal point is a signal point of known signal strength among the plurality of signal points; Filter out a second signal point whose signal strength is not acquired from the plurality of signal points in the spatial area; For each of the second signal points, a target sphere is established with the second signal point as the center, and a plurality of target first signal points constituting a target geometric figure are determined on the surface of the target sphere; wherein the second signal point is included in the target geometric figure; A target signal strength of the target first signal point is determined from the signal data set, and a signal strength of the second signal point is determined based on the target signal strength.

[0005] In the above implementation process, by dividing the spatial area into multiple signal points and obtaining a signal data set of the first signal point with known signal strength, for the second signal point whose signal strength is not obtained, a virtual target sphere is established with the second signal point as the center, and multiple target first signal points constituting the target geometric figure are determined on the surface of the target sphere, and the signal strength of the second signal point is predicted based on the target signal strength of the multiple target first signal points. In this way, on the one hand, the signal strength prediction of the unknown area is realized. On the other hand, by requiring the second signal point to be included in the target geometric figure, the influence of the signal points located in various directions around the second signal point on the signal strength of the second signal point can be taken into account, thereby improving the accuracy of signal prediction.

[0006] Furthermore, for each of the second signal points, a target sphere is established with the second signal point as the center, and a plurality of target first signal points constituting a target geometric figure are determined on the surface of the target sphere, including: For each of the second signal points, a target sphere is established with the second signal point as the sphere center and a preset length as the sphere radius; When the surface of the target sphere includes at least two candidate first signal points, if at least part of the candidate first signal points constitute the target geometric figure, determining the candidate first signal points constituting the target geometric figure as the target first signal points; If any multiple candidate first signal points do not form the target geometric figure, the next second signal point is obtained, and the step of establishing the target sphere is returned to be executed until all the second signal points are traversed.

[0007] In the above implementation process, when the surface of the target sphere includes at least two candidate first signal points, at least two candidate first signal points are extracted from all candidate first signal points to determine whether they form a target geometric figure. If they do, the target first signal point can be determined. If they do not, the next second signal point is selected to be predicted first, rather than using an insufficient number of signal points for signal strength prediction, thereby ensuring prediction accuracy.

[0008] Furthermore, the method further comprises: When the surface of the target sphere includes only one first signal point, acquiring the next second signal point, and returning to execute the step of establishing the target sphere; In the case that the surface of the target sphere does not include the first signal point, the next sphere radius is determined with the distance between adjacent signal points as the radius increase step, and the step of establishing the target sphere is returned to execute until the target first signal point is determined or the surface of the target sphere includes only one first signal point or the candidate first signal points on the surface of the target sphere do not constitute the target geometry.

[0009] In the above implementation process, when there is only one first signal point on the surface of the target sphere, or the first signal points on the surface of the target sphere cannot form a target geometric body, it means that the signal distribution around the current second signal point is still unclear, and thus the signal strength prediction of the next second signal point is continued to avoid reducing the prediction accuracy by performing signal prediction based on unclear signal distribution.

[0010] Further, after determining the signal strength of the second signal point based on the target signal strength, the method further includes: The signal data set is updated based on the signal strength of the second signal point, and the step of filtering out the second signal points whose signal strengths have not been acquired from the multiple signal points is returned to be executed until the signal strengths of all the signal points are acquired.

[0011] In the above implementation process, the signal strength predicted in the previous round can be used as the signal prediction basis of the second signal point in the next round. The number of second signal points in the next round will be less than the number of second signal points in the previous round. As the number of second signal points decreases, the signal distribution of the spatial area becomes more complete, and finally the signal acquisition of the entire spatial area is completed.

[0012] Furthermore, the second signal point is contained in the target geometric figure, including: the second signal point coincides with a center point of the target geometric figure.

[0013] In the above implementation process, by limiting the second signal point to coincide with the center point of the target geometric figure, the credibility of the signal strength of the second signal point can be improved.

[0014] Further, the determining the signal strength of the second signal point based on the target signal strength includes: An average value of the plurality of target signal strengths is determined as the signal strength of the second signal point.

[0015] In the above implementation process, by determining multiple target first signal points from the surface of the target sphere and utilizing the fact that the distance from each point on the sphere to the center of the sphere is the same, there is no need to evaluate the influence weight of each target first signal point on the signal strength of the second signal point. The average can be directly calculated as the signal strength of the second signal point, thereby improving the signal prediction efficiency.

[0016] Furthermore, the acquiring of a signal data set of a plurality of first signal points in a spatial region includes: A signal data set collected by the aircraft when flying along a signal collection route in the spatial area is obtained; wherein the waypoints in the signal collection route overlap with some of the multiple signal points.

[0017] In the above implementation process, by designing a signal collection route that passes through some signal points, the aircraft can collect signal data of some signal points along the signal collection route. For the second signal point in the area not collected by the aircraft, the signal strength prediction can be performed, and the aircraft does not need to cruise through each signal point for signal collection, thereby improving the acquisition efficiency of spatial area signal distribution.

[0018] Furthermore, the signal collection route includes a plurality of signal collection routes at different altitudes, and the projection of each of the signal collection routes on the horizontal plane is the same.

[0019] In the above implementation process, by designing multiple signal collection routes with different altitudes, the aircraft can obtain signal data of multiple signal points in the three-dimensional space area, providing a prediction basis for the subsequent signal strength prediction of the second signal point.

[0020] Furthermore, the spatial region includes a plurality of three-dimensional grids, and a feature point on each three-dimensional grid is a signal point in the spatial region; the feature point includes a vertex and / or a center point of the three-dimensional grid.

[0021] In the above implementation process, by gridding the spatial area into multiple three-dimensional grids and predicting the signal strength of the three-dimensional grids with unknown signal strength distribution, it is beneficial to improve the quality of aircraft patrol operations and flight safety during aircraft patrol operations.

[0022] A second aspect of an embodiment of the present application provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, any method described in the first aspect is implemented.

[0023] According to a third aspect of the present application, an electronic device is provided, the electronic device comprising: processor; a memory for storing processor-executable instructions; Wherein, when the processor calls the executable instruction, it implements the operation of any method described in the first aspect.

[0024] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of any method described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 A schematic diagram of a flow chart of a signal strength prediction method provided in an embodiment of the present application; Figure 2 A schematic diagram of a target sphere and a target geometric figure provided in an embodiment of the present application; Figure 3 A schematic diagram of a flow chart of another signal strength prediction method provided in an embodiment of the present application; Figure 4 A schematic diagram of a flow chart of another signal strength prediction method provided in an embodiment of the present application; Figure 5 A schematic diagram of a signal collection route provided in an embodiment of the present application; Figure 6 A hardware structure diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0028] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0029] In the relevant technology, for flight route planning, it is crucial to accurately grasp the signal distribution in each area of ​​space. In order to avoid loss of aircraft communication, route planning often avoids passing through areas with unknown signal distribution. The signal distribution of an area requires the aircraft to fly to the area for signal collection and determination. If the aircraft flies to every area in the space to collect signals, this is obviously a time-consuming and costly task. Therefore, it is of great significance to improve the signal prediction capability for unfly areas.

[0030] To this end, the present application provides a signal strength prediction method, which specifically includes the following steps: Figure 1 Steps 110 - 140 are shown.

[0031] Step 110: Acquire a signal data set of multiple first signal points in a spatial region; wherein the spatial region includes multiple signal points, and the first signal point is a signal point with known signal strength among the multiple signal points.

[0032] Exemplarily, the spatial region may refer to the flight airspace of an aircraft or other spatial regions. The spatial region may be divided into multiple signal points. The signal point refers to a virtual point with signal strength. The signal point is a virtual concept and may not have any physical form. The signal strength of each signal point in the spatial region characterizes the signal distribution of the spatial region. Among the multiple signal points included in the spatial region, a signal point with a known signal strength may be referred to as a first signal point. The signal strength acquisition process of the first signal point may refer to the relevant technology. The signal data set includes signal data of all first signal points in the spatial region. The signal data includes at least signal strength and may also include signal direction.

[0033] Step 120: Filter out second signal points for which signal strength is not acquired from the multiple signal points in the spatial area.

[0034] Exemplarily, among multiple signal points in a spatial region, a signal point with a known signal strength can be referred to as a first signal point, and the remaining signal points with unknown signal strengths can be referred to as second signal points. As an example, since the signal data set includes the signal strengths of multiple first signal points, the remaining signal points in the spatial region other than the signal points recorded in the signal data set can be determined as the second signal points. The determined second signal points include one or more, and for each second signal point, its signal strength can be predicted by executing steps 130-140.

[0035] Step 130: For each of the second signal points, establish a target sphere with the second signal point as the center, and determine a plurality of target first signal points constituting a target geometric figure on the surface of the target sphere; wherein the second signal point is included in the target geometric figure.

[0036] Step 140: Determine a target signal strength of the target first signal point from the signal data set, and determine a signal strength of the second signal point based on the target signal strength.

[0037] Exemplarily, the target sphere established for each second signal point is a virtual sphere and may not have any physical form. The purpose of establishing the target sphere is to predict the signal strength of the second signal point. Specifically, multiple target first signal points can be determined from the surface of the target sphere. Among them, the target first signal point meets the following conditions: 1) the signal strength is known, that is, the signal point recorded in the signal data set; 2) it is located on the surface of the target sphere; 3) multiple target first signal points form a target geometry, and the target geometry is a geometry that can contain the second signal point.

[0038] As an example, Figure 2 As shown in Figure (a), the target geometric figure includes a one-dimensional line segment, such as Figure 2 The middle figure (a) shows the line segment A1A2 formed by the target first signal point A1 and the target first signal point A2. The second signal point is contained by the target geometric figure, which means that the second signal point is located on the one-dimensional line segment. That is, the one-dimensional line segment passes through the second signal point. At the same time, considering that the two target first signal points constituting the one-dimensional line segment are located on the surface of the target sphere, and the second signal point is the center of the target sphere, the second signal point is located at the center point of the one-dimensional line segment.

[0039] As an example, Figure 2 As shown in the middle figure (b), the target geometric figure includes a two-dimensional plane figure, such as Figure 2 The triangle B1B2B3 formed by the target first signal point B1, the target first signal point B2 and the target first signal point B3 is shown in the middle figure (b). The second signal point is contained by the target geometric figure, which means that the second signal point is located inside the two-dimensional plane figure. Of course, except Figure 2 In addition to the triangle shown in the middle figure (b), the two-dimensional plane figure can also include other plane polygons, which is not limited in this application.

[0040] As another example, Figure 2 As shown in the middle figure (c), the target geometric figure includes a three-dimensional solid figure, such as Figure 2 In the figure (c), the triangular pyramid C1C2C3C4 is formed by the target first signal point C1 to the target first signal point C4. Figure 2 In the figure (d), the cone D1D2D3D4D5D6 is formed by the target first signal point D1 to the target first signal point D6. The second signal point is contained by the target geometric figure, which means that the second signal point is located inside the three-dimensional figure. Of course, except Figure 2 In addition to the vertebrae shown in Figures (c) and (d), the three-dimensional figure may also include other polyhedrons, which is not limited in the present application.

[0041] It can be understood that when the second signal point is included in the target geometry, then the target first signal point comes from at least two directions relative to the second signal point. For example, when the target geometry is a one-dimensional line segment, the two target first signal points are located at both ends of the second signal point. When the target geometry is a two-dimensional plane figure, at least three target first signal points are located at three positions relative to the second signal point. When the target geometry is a three-dimensional solid figure, at least four target first signal points are located at four positions relative to the second signal point, and so on, thereby taking into account the influence of the signal points located at various positions around the second signal point on the signal strength of the second signal point. If the second signal point is not included in the target geometry, then the target first signal point will come from the same side relative to the second signal point. At this time, the influence of the signal points on the other side on the signal strength of the second signal point will not be considered, reducing the accuracy of the signal strength prediction.

[0042] It can be seen that the present application divides the spatial area into multiple signal points, obtains a signal data set of the first signal point with known signal strength, and for the second signal point whose signal strength is not obtained, establishes a virtual target sphere with the second signal point as the center, determines multiple target first signal points constituting the target geometric figure on the surface of the target sphere, and predicts the signal strength of the second signal point based on the target signal strength of the multiple target first signal points. In this way, on the one hand, the signal strength prediction of the unknown area is realized, and on the other hand, by requiring the second signal point to be included in the target geometric figure, the influence of the signal points located in various directions around the second signal point on the signal strength of the second signal point can be taken into account, thereby improving the accuracy of signal prediction.

[0043] Steps 110 to 140 are described in detail below.

[0044] According to some embodiments of the present application, determining a plurality of target first signal points constituting a target geometric figure in step 130 may specifically include: Figure 3 Steps 131 to 133 are shown.

[0045] Step 131: For each of the second signal points, a target sphere is established with the second signal point as the sphere center and a preset length as the sphere radius.

[0046] Exemplarily, for each second signal point, when the target sphere is first established, the preset length may be the distance between adjacent signal points. That is, if the distance between two adjacent signal points in the spatial region is r, then when the target sphere is first established for a second signal point, the target sphere is established with the second signal point as the sphere center and the distance r as the sphere radius.

[0047] After executing step 131, it is determined whether the first condition is satisfied: the surface of the target sphere includes at least two candidate first signal points. If the first condition is satisfied, step 132 or step 133 is executed. The candidate first signal point refers to the first signal point located on the surface of the target sphere among all the first signal points whose signal strengths have been acquired.

[0048] Step 132: If at least part of the candidate first signal points constitute the target geometric figure, determine the candidate first signal points constituting the target geometric figure as the target first signal points.

[0049] Step 133: If any multiple candidate first signal points do not form the target geometric figure, obtain the next second signal point and return to execute the step of establishing the target sphere until all the second signal points are traversed.

[0050] Exemplarily, when the surface of the target sphere includes at least two candidate first signal points, at least two candidate first signal points can be extracted from all candidate first signal points by permutation and combination, and it is determined whether the extracted at least two candidate first signal points can form the target geometry. At this time, it is possible that all candidate first signal points together form the target geometry, or only some of the candidate first signal points can together form the target geometry, or the combination of various candidate first signal points cannot form the target geometry. Then if the target geometry can be formed (composed of some or all of the candidate first signal points), the candidate first signal points that form the target geometry are determined to be the target first signal points. On the contrary, if any multiple candidate first signal points cannot form the target geometry, it means that there are not enough first signal points with acquired signal strength around the second signal point, and there are not enough first signal points that can be used as references for signal strength prediction, making it difficult to accurately predict the signal strength of the second signal point. Therefore, the next second signal point can be obtained first, and the signal strength prediction can be performed through any embodiment of the present application.

[0051] It can be seen that in this embodiment, when the surface of the target sphere includes at least two candidate first signal points, at least two candidate first signal points are extracted from all candidate first signal points to determine whether they form a target geometric figure. If they do, the target first signal point can be determined. If they do not, the next second signal point is selected first, rather than using an insufficient number of first signal points for signal strength prediction, thereby ensuring prediction accuracy.

[0052] In addition, in some embodiments, determining a plurality of target first signal points constituting a target geometric figure in step 130 may specifically include: Figure 4 Step 131, and step 134-step 135 are shown.

[0053] Step 131: For each of the second signal points, a target sphere is established with the second signal point as the sphere center and a preset length as the sphere radius.

[0054] The specific implementation process of step 131 is referred to the above embodiment and will not be described again here.

[0055] After executing step 131, it is determined whether the second case or the third case is satisfied. In the second case, the surface of the target sphere includes only one first signal point; and the third case, the surface of the target sphere does not include the first signal point. If the second case is satisfied, step 134 is executed. If the third case is satisfied, step 135 is executed.

[0056] Step 134: when the surface of the target sphere includes only one first signal point, obtain the next second signal point, and return to execute the step of establishing the target sphere.

[0057] Exemplarily, in situation two, the surface of the target sphere includes only one first signal point whose signal strength has been acquired. One first signal point cannot form a geometric figure, which also indicates that there are insufficient first signal points that can be used as references for signal strength prediction. Therefore, it is chosen to first predict the signal strength of the next second signal point, that is, to acquire the next second signal point, and return to execute step 131.

[0058] Step 135: When the surface of the target sphere does not include the first signal point, determine the next sphere radius with the distance between adjacent signal points as the radius increase step, and return to execute the step of establishing the target sphere until the target first signal point is determined or the surface of the target sphere includes only one first signal point or the candidate first signal points on the surface of the target sphere do not constitute the target geometry.

[0059] Exemplarily, in case three, the surface of the target sphere does not include the first signal point. At this time, the radius of the target sphere can be increased, and the sphere can be expanded outward to find the first signal point. Among them, the distance between adjacent signal points can be used as the step of increasing the radius. For example, in the above example, if the distance between two adjacent signal points in the spatial region is r, then when the target sphere is first established for a second signal point, the target sphere is established with the second signal point as the center of the sphere and the distance r as the radius of the sphere. When the surface of the target sphere with a radius of r does not include the first signal point, the next sphere radius is determined to be 2r with r as the step of increasing the radius, and return to execute step 131, that is, a target sphere with a radius of 2r is established with the second signal point as the center of the sphere, until the target first signal point is determined, or the re-established target sphere surface includes only one first signal point (this meets case two, and the next second signal point will be selected), or the candidate first signal points of the re-established target sphere surface fail to form the target geometric figure (the next second signal point will be selected at this time).

[0060] Combining the above three situations, it can be seen that when there is only one first signal point on the surface of the target sphere, or the first signal points on the surface of the target sphere cannot form a target geometry, the signal strength prediction of the current second signal point will be skipped and the signal strength prediction of the next second signal point will be continued. This is because the present embodiment believes that both of these situations represent that there are not enough first signal points with known signal strengths around the current second signal point as a basis for signal strength prediction, or that the signal distribution around the current second signal point is not yet clear. The signal strength prediction of the second signal point depends on the signal distribution around it. If the signal prediction is based on unclear signal distribution, the prediction accuracy will be reduced. Therefore, the signal strength prediction of the next second signal point is selected. At the same time, according to the corresponding processing measures for the above three situations, it can be seen that the target sphere will only include the first signal point on the surface, and does not include other signal points except the second signal point inside the sphere.

[0061] In addition, based on any of the above embodiments, after step 140, step 150 is also included.

[0062] Step 150: Update the signal data set based on the signal strength of the second signal point, and return to execute the step of filtering out the second signal points whose signal strength has not been obtained from the multiple signal points until the signal strength of all the signal points is obtained.

[0063] Exemplarily, after obtaining the signal strength of the second signal point through any of the above embodiments, the second signal point with predicted signal strength can be determined as the first signal point with known signal strength. At this time, the signal point and the corresponding signal strength can be recorded in the signal data set to update the signal data set.

[0064] It is understandable that after completing a traversal prediction of all second signal points, as a possible scenario, all second signal points complete the signal strength prediction in the first traversal. As another possible scenario, some second signal points complete the signal strength prediction in the first traversal, while other second signal points cannot predict the signal strength in the first traversal because there are insufficient first signal points with known signal strengths around them. At this time, a second traversal prediction is required. Therefore, in the second traversal prediction, it is first necessary to determine a new round of second signal points based on the updated signal data set, and then predict the signal strength of each second signal point based on the method provided in any embodiment.

[0065] The prediction traversal in the previous round supplements the signal strength of some second signal points, which is actually to continuously improve the signal distribution in the spatial area. At the same time, the signal strength obtained in the previous round of prediction can be used as the basis for signal prediction of the second signal point in the next round. Therefore, in multiple rounds of signal strength prediction, the number of second signal points in the next round will be less than the number of second signal points in the previous round. As the number of second signal points decreases, the signal distribution in the spatial area continues to become complete, and finally the signal acquisition of the entire spatial area is completed.

[0066] In addition, based on any of the above embodiments, the second signal point is included in the target geometric figure, specifically including: the second signal point coincides with the center point of the target geometric figure.

[0067] As an example, the target geometry includes a one-dimensional line segment. As described above, the second signal point will be located at the center point of the one-dimensional line segment, bisecting the one-dimensional line segment. As an example, the target geometry includes a two-dimensional plane figure, then the second signal point coincides with the center point of the two-dimensional plane figure. As another example, the target geometry includes a three-dimensional solid figure, then the second signal point coincides with the center point of the three-dimensional solid figure.

[0068] It can be seen that by limiting the second signal point to coincide with the center point of the target geometric figure, the credibility of the signal strength predicted for the second signal point can be improved.

[0069] In addition, based on any of the above embodiments, determining the signal strength of the second signal point based on the target signal strength in step 140 specifically includes: determining an average of a plurality of the target signal strengths as the signal strength of the second signal point.

[0070] For example, since multiple target first signal points are located on the surface of the target sphere, the distance from each target first signal point to the center of the sphere (i.e., the second signal point) is the same, and the influence weight of each target first signal point on the signal strength of the second signal point is the same. Therefore, the average of the target signal strengths of the multiple target first signal points can be directly determined as the signal strength of the second signal point.

[0071] It can be seen that this embodiment determines multiple target first signal points from the surface of the target sphere, and utilizes the fact that the distance from each point on the sphere to the center of the sphere is the same. There is no need to evaluate the influence weight of each target first signal point on the signal strength of the second signal point. The average can be directly calculated as the signal strength of the second signal point, thereby improving the signal prediction efficiency.

[0072] Based on any of the above embodiments, regarding the process of collecting signal data of the first signal point, as an example, signal data collection of signal points in a space region may be performed based on an aircraft. Specifically, step 110 may include: A signal data set collected by the aircraft when flying along a signal collection route in the spatial area is obtained; wherein the waypoints in the signal collection route overlap with some of the multiple signal points.

[0073] Exemplarily, the aircraft includes but is not limited to drones, manned aircraft, helicopters and other aerial devices with flight capabilities. Based on this, the signal strength prediction method can be applied to aircraft, or electronic devices connected to the aircraft for communication. The electronic devices connected to the aircraft for communication include but are not limited to remote controllers, central consoles, servers, mobile terminals and other devices with data processing capabilities.

[0074] The aircraft is equipped with a signal acquisition device. Optionally, the signal acquisition device can capture omnidirectional signal strength. For example, the signal acquisition device may include three mutually perpendicular antennas, and the three antennas are arranged in mutually perpendicular x, y, and z directions, respectively, so that the signal acquisition device can collect omnidirectional signal data.

[0075] As an example, the signal acquisition device includes multiple sets, each set of signal acquisition devices is used to collect signals in different frequency bands, and multiple sets of signal acquisition devices can receive signals in different frequency bands at the same time. The layout of multiple sets of signal acquisition devices on the aircraft needs to avoid mutual interference to ensure the best signal reception performance. The frequency bands include but are not limited to 4G frequency bands, 5G frequency bands, and image transmission frequency bands, etc. As another example, the signal acquisition device may include a set, and the signal acquisition device can use software defined radio technology (Software Defined Radio, SDR) to switch between different frequency bands and collect signals by dynamically adjusting the frequency band. Since the aircraft has the ability to collect signals in multiple frequency bands, for each frequency band signal, the signal strength of the frequency band can be predicted by a signal strength prediction method provided in any of the above embodiments.

[0076] The aircraft collects signal data of signal points by flying along a signal collection route in a spatial region. The signal collection route includes multiple waypoints. The waypoints of the signal collection route overlap with some signal points in the spatial region, so that when the aircraft flies along the signal collection route, signal data is collected at each waypoint to obtain the signal data of the signal point corresponding to the waypoint. If the signal data collection is successful, then the signal point is the first signal point. Optionally, if the aircraft collects signal data multiple times at a certain waypoint, the average of the multiple signal data can be determined as the signal data of the signal point corresponding to the waypoint. After completing the flight, a signal data set can be obtained, and the signal data set includes signal data of signal points (or first signal points) corresponding to multiple waypoints.

[0077] In addition, as described above, the waypoints of the signal collection route overlap with some signal points in the space region. Then, except for some signal points that overlap with the waypoints, other signal points in the space region do not obtain the corresponding signal strength because no aircraft has arrived to collect signals, and are the second signal points described in step 120. In addition, for the signal points that overlap with the waypoints, some of them may fail to collect signals, so the signal points corresponding to the waypoints where signal collection fails are also the second signal points described in step 120.

[0078] It can be seen that in this embodiment, by designing a signal collection route that passes through some signal points, the aircraft can collect signal data of some signal points along the signal collection route. For the second signal point in the area not collected by the aircraft, the signal strength can be predicted by the above method, without the need for the aircraft to cruise through each signal point for signal collection, thereby improving the acquisition efficiency of spatial area signal distribution.

[0079] In addition, based on any of the above embodiments, the signal collection routes include multiple ones, and the multiple signal collection routes have different altitudes, and the projections of each signal collection route at different altitudes on the horizontal plane are the same. In the case where there are multiple signal collection routes, the signal data set can be obtained after the aircraft completes the flight of all signal collection routes.

[0080] like Figure 5 Five signal collection routes at different altitudes are shown as illustrative examples. Each signal collection route includes a plurality of waypoints. Figure 5 The signal strength of the signal point corresponding to each waypoint is represented by color. These five signal collection routes have the same projection on the horizontal plane. As an example, Figure 5 As shown, each signal collection route includes N sequentially connected waypoints, and the i-th waypoint of each signal collection route has the same longitude and latitude and different altitudes, 1≤i≤N, and i is a positive integer. As another example, the i-th waypoint of each signal collection route can have different longitude and latitude and altitude.

[0081] It can be seen that in this embodiment, by designing multiple signal collection routes with different altitudes, the aircraft can obtain signal data of multiple signal points in the three-dimensional space area, providing a prediction basis for the subsequent signal strength prediction of the second signal point.

[0082] In addition, based on any of the above embodiments, the spatial region includes a plurality of three-dimensional grids, and the characteristic points on each three-dimensional grid are signal points in the spatial region, wherein the characteristic points include vertices and / or center points of the three-dimensional grids.

[0083] Exemplarily, the three-dimensional space corresponding to the spatial region can be gridded to obtain multiple three-dimensional grids. The vertices and / or center points in each three-dimensional grid can be the signal points described in any of the above embodiments. In this way, each three-dimensional grid includes one or more signal points. In this way, for all three-dimensional grids in the spatial region, there are signal points in some three-dimensional grids that have obtained signal strength, which are first signal points, while signal points in another part of the three-dimensional grids have not obtained signal strength, which are second signal points. Then, through a signal strength prediction method described in any of the above embodiments, the signal distribution in another part of the three-dimensional grid can be predicted.

[0084] It can be seen that in this embodiment, by gridding the spatial area into multiple three-dimensional grids and predicting the signal strength of the three-dimensional grids with unknown signal strength distribution, it is beneficial to improve the quality of aircraft patrol operations and flight safety during aircraft patrol operations.

[0085] Based on a signal strength prediction method described in any of the above embodiments, the present application also provides a computer program product, which includes one or more computer programs or instructions. The computer program or instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. When the computer program is executed by a processor, a signal strength prediction method described in any of the above embodiments is implemented.

[0086] Based on a signal strength prediction method described in any of the above embodiments, the present application also provides Figure 6 A schematic diagram of the structure of an electronic device is shown in FIG. Figure 6 At the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement a signal strength prediction method described in any of the above embodiments.

[0087] The present application also provides a computer storage medium, which stores a computer program. When the computer program is executed by a processor, it can be used to execute a signal strength prediction method described in any of the above embodiments.

[0088] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0089] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0090] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0091] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0092] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0093] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A signal strength prediction method, characterized in that: The method comprises: Acquire a signal data set of a plurality of first signal points in a spatial region; wherein the spatial region includes a plurality of signal points, and the first signal point is a signal point of known signal strength among the plurality of signal points; Filter out a second signal point whose signal strength is not acquired from the plurality of signal points in the spatial area; For each of the second signal points, a target sphere is established with the second signal point as the center, and a plurality of target first signal points constituting a target geometric figure are determined on the surface of the target sphere; wherein the second signal point is included in the target geometric figure; A target signal strength of the target first signal point is determined from the signal data set, and a signal strength of the second signal point is determined based on the target signal strength.

2. The method according to claim 1, characterized in that The method of establishing a target sphere with the second signal point as the center for each of the second signal points, and determining a plurality of target first signal points constituting a target geometric figure on the surface of the target sphere includes: For each of the second signal points, a target sphere is established with the second signal point as the sphere center and a preset length as the sphere radius; When the surface of the target sphere includes at least two candidate first signal points, if at least part of the candidate first signal points constitute the target geometric figure, determining the candidate first signal points constituting the target geometric figure as the target first signal points; If any multiple candidate first signal points do not form the target geometric figure, the next second signal point is obtained, and the step of establishing the target sphere is returned to be executed until all the second signal points are traversed.

3. The method according to claim 2, characterized in that The method further comprises: When the surface of the target sphere includes only one first signal point, acquiring the next second signal point, and returning to execute the step of establishing the target sphere; When the surface of the target sphere does not include the first signal point, the next sphere radius is determined with the distance between adjacent signal points as the step of increasing the radius, and the step of establishing the target sphere is returned to execute until the target first signal point is determined or the surface of the target sphere includes only one first signal point or the candidate first signal points on the surface of the target sphere do not constitute the target geometry.

4. The method according to claim 2 or 3, characterized in that: After determining the signal strength of the second signal point based on the target signal strength, the method further includes: The signal data set is updated based on the signal strength of the second signal point, and the step of filtering out the second signal points whose signal strengths have not been acquired from the multiple signal points is returned to be executed until the signal strengths of all the signal points are acquired.

5. The method according to any one of claims 1 to 3, characterized in that: The second signal point is contained by the target geometric figure, including: the second signal point coincides with the center point of the target geometric figure.

6. The method according to any one of claims 1 to 3, characterized in that: The determining the signal strength of the second signal point based on the target signal strength includes: An average value of the plurality of target signal strengths is determined as the signal strength of the second signal point.

7. The method according to any one of claims 1 to 3, characterized in that: The acquiring of a signal data set of a plurality of first signal points in a spatial region comprises: A signal data set collected by the aircraft when flying along a signal collection route in the spatial area is obtained; wherein the waypoints in the signal collection route overlap with some of the multiple signal points.

8. The method according to claim 7, characterized in that The signal collection route includes a plurality of signal collection routes at different altitudes, and the projection of each of the signal collection routes on the horizontal plane is the same.

9. The method according to any one of claims 1 to 3, characterized in that: The spatial region includes a plurality of three-dimensional grids, and a feature point on each three-dimensional grid is a signal point in the spatial region; the feature point includes a vertex and / or a center point of the three-dimensional grid.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

11. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; Wherein, when the processor calls the executable instructions, it implements the operation of any method described in claims 1-9.

12. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed by a processor, the steps of any method described in claims 1-9 are implemented.

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