Aircraft path planning method and device based on communication optimization, equipment and medium

Abstract

The invention relates to the technical field of communication, and provides an aircraft path planning method, device and equipment based on communication optimization, and a medium, on one hand, mobile communication data of a monitoring area is collected in an auxiliary manner by using a ceclay packet filter, nanosecond timestamp marking can be realized, and thus the time delay measurement precision is improved; on one hand, in the flight process, a mobile communication service quality three-dimensional thermodynamic diagram of a monitoring area is generated based on a height attenuation factor and mobile communication data, the mobile communication service quality of a three-dimensional space can be accurately predicted, and an accurate real-time obstacle avoidance decision basis is provided for subsequent aircraft path planning; and on the other hand, the cost value of each candidate path is calculated, the candidate path with the lowest cost value is selected as the target path, and the target aircraft is controlled to fly to the flight end point according to the target path, so that more accurate three-dimensional path planning can be realized by introducing the path cost, and the success rate of rapidly and safely arriving at the end point is higher.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method, apparatus, device and medium for aircraft path planning based on communication optimization. Background Technology

[0002] With the continuous development of the low-altitude economy, how to accurately monitor the quality of mobile communication services during aircraft flight and thereby scientifically plan flight paths has become an urgent problem to be solved.

[0003] To address the aforementioned issues, existing technologies mainly suffer from the following problems: (1) Existing technologies typically use application layer RTT (Round-Trip Time) to measure latency, which requires waiting for TCP ACK (Transmission Control Protocol Acknowledgment) confirmation mechanism, resulting in a minimum measurement interval of ≥200ms, which cannot capture sudden microsecond-level jitter (such as <10ms instantaneous packet loss caused by 5G (the 5th Generation Mobile Communication Technology) base station handover). (2) Existing technologies mainly rely on RSRP (Reference Signal Received Power) measurement at the MAC (Media Access Control) layer. Two-dimensional planar signal strength maps cannot reflect the multipath interference distribution in low-altitude three-dimensional space below 120 meters. (3) Existing technologies mainly use traditional NetFlow to collect data, with a sampling rate of ≤1%, resulting in a packet loss rate calculation error of >300% and a heat map update delay of >5 seconds, which cannot support real-time obstacle avoidance decisions for drones and other aircraft. Summary of the Invention

[0004] In view of the above, it is necessary to provide a communication-optimized aircraft path planning method, apparatus, equipment and medium, which aims to solve the problem of poor aircraft path planning caused by inaccurate and untimely monitoring of the quality of low-altitude economic mobile communication services.

[0005] A communication-optimized aircraft path planning method, comprising: In response to path planning instructions for the target aircraft, acquire the monitoring area from the flight start point to the flight end point; Berkeley packet filters were used to assist in the collection of mobile communication data in the monitored area. During flight, a three-dimensional heat map of the mobile communication service quality of the monitored area is generated based on the altitude attenuation factor and the mobile communication data. Multiple candidate paths are determined based on the three-dimensional heatmap of mobile communication service quality; Calculate the cost value of each candidate path, and select the candidate path with the lowest cost value from the multiple candidate paths as the target path; Control the target aircraft to fly to the flight destination along the target path.

[0006] According to a preferred embodiment of the present invention, after obtaining the monitoring area from the flight start point to the flight end point, the method further includes: Establish an offline 3D elevation database; The terrain features of the monitored area are preprocessed based on the offline 3D elevation database.

[0007] According to a preferred embodiment of the present invention, the step of using a Berkeley packet filter to assist in collecting mobile communication data in the monitored area includes: The Berkeley packet filter is used to mark the transmission time of each message; The arrival time of each message is obtained by bypassing the mirror port and using the time when the message arrives at the corresponding receiver as the arrival time of each message. Calculate the difference between the arrival time and the corresponding sending time of each message to obtain the one-way delay of each message; The packet loss rate of the monitored area is calculated using a sliding window. Calculate the jitter in the monitored area; The one-way delay of each message, the packet loss rate, and the jitter are determined as the mobile communication data.

[0008] According to a preferred embodiment of the present invention, generating a three-dimensional heatmap of mobile communication service quality of the monitored area based on the height attenuation factor and the mobile communication data includes: The monitoring area is divided into multiple grids in a three-dimensional grid according to a preset grid unit. The initial mobile communication service quality for each grid is calculated using the following formula: QoS = w1 * exp(-Latency / τ) + w2 * (1 - Jitter / J max )+w3*(1-LossRate); where QoS represents the initial mobile communication service quality of each grid; w1, w2, and w3 represent weighting coefficients; Latency represents the one-way latency of each grid; τ represents the latency attenuation coefficient of each grid; Jitter represents the jitter of each grid, J max This represents the maximum tolerable jitter for each grid cell; LossRate represents the packet loss rate for each grid cell. The height attenuation factor is constructed using the following formula: (h)=1 / (1+p*(hh ref ) 2 );in, (h) represents the altitude attenuation factor of the target aircraft at a real-time flight altitude of h; p represents the attenuation coefficient; h ref Indicates the height of the base station antenna; The target mobile communication service quality for each grid is obtained by multiplying the initial mobile communication service quality for each grid with the corresponding height attenuation factor. The three-dimensional heatmap of mobile communication service quality is generated based on the mapping rules between mobile communication service quality and color.

[0009] According to a preferred embodiment of the present invention, calculating the cost of each candidate path includes: Retrieve the subpaths of each candidate path: The path cost of each sub-path is calculated using the constructed path cost function: ;in, This represents the path cost of the current node n where the target aircraft is located; k is a constant used to adjust the weights of the path cost function. This represents the x-axis distance from the flight start point to the current node n; This represents the y-axis distance from the flight start point to the current node n; This represents the z-axis distance from the flight start point to the current node n; Indicates the penalty coefficient for height variation; The heuristic cost of each subpath is calculated using the constructed heuristic function: ;in, This represents the heuristic cost of the current node n, used to measure the heuristically estimated total length from the current node n to the end of each sub-path; This represents the x-axis coordinate of the endpoint of each sub-path; This represents the x-axis coordinate of the current node n; This represents the y-axis coordinate of the endpoint of each sub-path; This represents the y-axis coordinate of the current node n; This represents the z-axis coordinate of the endpoint of each sub-path; This represents the z-axis coordinate of the current node n; The communication cost of each sub-path is calculated using the constructed communication quality factor function: ;in, This represents the communication cost of the current node n; The target mobile communication service quality represents the current node n; t represents the current time. The time-degradation coefficient representing the quality of mobile communication services; The first weighting coefficient is calculated using the following formula: ;in, d represents the first weight coefficient; d represents the path length of each sub-path; D represents the heuristically estimated total length of each sub-path. The second weighting coefficient is calculated using the following formula: Where β represents the second weighting coefficient; The cost of each sub-path is calculated by weighting the path cost, heuristic cost, and communication cost together using the following formula: f(n) = α*g(n) + β*h(n) + γ*q(n); where f(n) represents the cost of traversing each sub-path from the current node n; γ represents the third weight coefficient, and the value of γ is adjusted according to the emphasis on communication quality in the current scenario. Calculate the sum of the cost values ​​of each sub-path corresponding to each candidate path to obtain the cost value of each candidate path.

[0010] According to a preferred embodiment of the present invention, the method further includes: During the process of controlling the target aircraft to fly to the destination along the target path, when the rate of decline in real-time mobile communication service quality is detected to be greater than the deceleration threshold, the current position of the target aircraft is obtained, and the path is replanned based on the current position. Furthermore, the frequency of non-critical data transmission is reduced, data packets are compressed, and the modulation scheme is optimized; or When the real-time mobile communication service quality is detected to be lower than a first threshold, and the continuous mobile communication service quality within a preset duration is lower than a second threshold, the system switches to message queue telemetry transmission degradation mode to transmit only core control and status data. It avoids areas where the real-time mobile communication service quality is lower than the first threshold by slowing down and / or hovering, suspends high-bandwidth applications, caches non-real-time data, and issues a low mobile communication service quality warning; wherein the second threshold is greater than the first threshold; or When the real-time mobile communication service quality is detected to be less than the third threshold or the communication interruption duration is greater than the duration threshold, the system switches to a backup channel and transmits simplified status packets in the backup channel at preset time intervals, initiates autonomous return or safe hovering mode, records logs and issues an emergency alarm; wherein the third threshold is less than the first threshold.

[0011] According to a preferred embodiment of the present invention, after controlling the target aircraft to fly to the flight destination along the target path, the method further includes: The target path is recorded in the path pool, and the flight start point and the flight destination are stored using a hash table.

[0012] A communication-optimized aircraft path planning device, the communication-optimized aircraft path planning device comprising: The acquisition unit is used to acquire the monitoring area from the flight start point to the flight end point in response to the path planning command of the target aircraft; The acquisition unit is used to collect mobile communication data of the monitored area with the assistance of Berkeley packet filters; The generation unit is used to generate a three-dimensional heat map of the mobile communication service quality of the monitored area based on the altitude attenuation factor and the mobile communication data during flight. A determining unit is configured to determine multiple candidate paths based on the three-dimensional heatmap of mobile communication service quality. The selection unit is used to calculate the cost value of each candidate path and select the candidate path with the lowest cost value from the plurality of candidate paths as the target path. The control unit is used to control the target aircraft to fly to the flight destination along the target path.

[0013] A computer device, the computer device comprising: Memory, storing at least one instruction; and The processor executes the instructions stored in the memory to implement the communication-optimized aircraft path planning method.

[0014] A computer-readable storage medium storing at least one instruction, which is executed by a processor in a computer device to implement the communication-optimized aircraft path planning method.

[0015] As can be seen from the above technical solutions, on the one hand, using Berkeley packet filters to assist in the collection of mobile communication data in the monitoring area can achieve nanosecond-level timestamp marking, thereby improving the accuracy of latency measurement; on the other hand, during flight, generating a three-dimensional heat map of mobile communication service quality in the monitoring area based on altitude attenuation factor and mobile communication data can accurately predict the mobile communication service quality in three-dimensional space, providing accurate real-time obstacle avoidance decision-making basis for subsequent aircraft path planning; furthermore, calculating the cost of each candidate path, selecting the candidate path with the lowest cost as the target path, and controlling the target aircraft to fly to the flight destination along the target path can achieve more accurate three-dimensional path planning by introducing path cost, thereby increasing the success rate of the aircraft reaching the destination quickly and safely. Attached Figure Description

[0016] Figure 1 This is a flowchart of a preferred embodiment of the communication-optimized aircraft path planning method of the present invention; Figure 2 This is a functional block diagram of a preferred embodiment of the aircraft path planning device based on communication optimization of the present invention; Figure 3 This is a schematic diagram of the structure of a computer device that implements a preferred embodiment of the communication-optimized aircraft path planning method of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 The diagram shown is a flowchart of a preferred embodiment of the communication-optimized aircraft path planning method of the present invention. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0019] The communication-optimized aircraft path planning method is applied to one or more computer devices. The computer device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0020] The computer device can be any electronic product that can interact with the user, such as a personal computer, tablet computer, smartphone, personal digital assistant (PDA), game console, interactive network television (IPTV), smart wearable device, etc.

[0021] The computer equipment may also include network equipment and / or user equipment. The network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0022] The server can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0023] Artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0024] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0025] The network in which the computer device is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, and virtual private network (VPN).

[0026] S10, in response to the path planning command for the target aircraft, acquires the monitoring area from the flight start point to the flight end point.

[0027] In this embodiment, the target aircraft can be an aircraft in the low-altitude economic zone, such as a drone.

[0028] In this embodiment, the path planning command can be automatically triggered when the target aircraft starts up, so as to realize real-time monitoring and optimization of the entire flight process of the target aircraft.

[0029] In this embodiment, after obtaining the monitoring area from the flight start point to the flight end point, the method further includes: Establish an offline 3D elevation database; The terrain features of the monitored area are preprocessed based on the offline 3D elevation database.

[0030] The above embodiments can provide accurate terrain data for subsequent processing, thereby improving the accuracy of calculations.

[0031] S11, Berkeley Packet Filter (BPF) is used to assist in the collection of mobile communication data in the monitored area.

[0032] In this embodiment, the Berkeley packet filter is based on nanosecond-level timestamp marking technology, which can improve the accuracy of delay measurement by 1000 times compared with the application layer solution.

[0033] In this embodiment, the mobile communication data may include metrics such as latency, packet loss rate, and jitter from 5G (the 5th Generation Mobile Communication Technology) and other mobile communication networks.

[0034] In this embodiment, the use of Berkeley packet filters to assist in collecting mobile communication data in the monitored area includes: The Berkeley packet filter is used to mark the transmission time of each message; The arrival time of each message is obtained by bypassing the mirror port and using the time when the message arrives at the corresponding receiver as the arrival time of each message. Calculate the difference between the arrival time and the corresponding sending time of each message to obtain the one-way delay of each message; The packet loss rate of the monitored area is calculated using a sliding window. Calculate the jitter in the monitored area; The one-way delay of each message, the packet loss rate, and the jitter are determined as the mobile communication data.

[0035] For example, a BPF program can be injected into the Linux kernel data link layer of the target aircraft, and each TCP (Transport Control Protocol) or UDP (User Datagram Protocol) message can be marked with a precise transmission time t1. The actual arrival time t2 of the receiver can be obtained through the bypass mirror port, and the one-way delay (t2-t1) can be calculated.

[0036] For example, a sliding window can be used to count the number of packets sent (Nsent) and received (Nreceived) in the last second, thereby dynamically updating the packet loss rate: (Nsent − Nreceived) / Nsent.

[0037] For example: Suppose ΔDi = |D(i) - D(i-1)|; where D(i) represents the one-way delay of the i-th message; D(i-1) represents the one-way delay of the (i-1)-th message; reference jitter Specifically, the baseline jitter (Jitterbase) can be calculated using the first 100 packets, and then the relative values ​​can be calculated for subsequent packets; thus, the jitter... ;in, Represents the smoothing factor ( It can be set to 0.9 to suppress instantaneous fluctuations; Jitterprev represents the jitter calculated in the last time.

[0038] In this embodiment, FPGA (Field-Programmable Gate Array) hardware can also be used to accelerate data packet processing, thereby improving data acquisition efficiency.

[0039] S12, during flight, a three-dimensional heat map of the mobile communication service quality of the monitored area is generated based on the altitude attenuation factor and the mobile communication data.

[0040] In this embodiment, generating a three-dimensional heatmap of mobile communication service quality for the monitored area based on the height attenuation factor and the mobile communication data includes: The monitoring area is divided into multiple grids in a three-dimensional grid according to a preset grid unit. The initial mobile communication service quality for each grid is calculated using the following formula: QoS = w1 * exp(-Latency / τ) + w2 * (1 - Jitter / J max )+w3*(1-LossRate); where QoS represents the initial mobile communication service quality of each grid; w1, w2, and w3 represent weighting coefficients; Latency represents the one-way latency of each grid; τ represents the latency attenuation coefficient of each grid; Jitter represents the jitter of each grid, J max This represents the maximum tolerable jitter for each grid cell; LossRate represents the packet loss rate for each grid cell. The height attenuation factor is constructed using the following formula: (h)=1 / (1+p*(hh ref ) 2 );in, (h) represents the altitude attenuation factor of the target aircraft at a real-time flight altitude of h; p represents the attenuation coefficient; h ref Indicates the height of the base station antenna; The target mobile communication service quality for each grid is obtained by multiplying the initial mobile communication service quality for each grid with the corresponding height attenuation factor. The three-dimensional heatmap of mobile communication service quality is generated based on the mapping rules between mobile communication service quality and color.

[0041] The preset grid unit can be configured according to actual needs. For example, the preset grid unit can be 1m×1m×0.5m.

[0042] For example: τ = 20ms, J max=50ms, w1+ w2+ w3=1, p=0.05 / m².

[0043] For example, the mapping rule can be expressed as follows: Red (QoS<60): Indicates a high-risk area for communication interruption; Yellow (60≤QoS<80): Indicates that you need to reduce your flight speed to pass; Green (QoS≥80): Indicates the optimal passage area.

[0044] In this embodiment, WebGL 2.0 (Web Graphics Library 2.0) can be used to implement browser-side rendering, supporting real-time updates of 2 million grids, thereby realizing a visualization engine.

[0045] In this embodiment, visualization technologies such as Three.js (Three JavaScript) can also be used to achieve browser-side rendering, thereby supporting the visualization of the three-dimensional heat map of the mobile communication service quality, which is convenient for users to analyze and view.

[0046] In the above embodiments, by introducing a high attenuation factor, a more accurate heatmap can be generated, thereby providing a high-quality data foundation for subsequent path planning.

[0047] In other embodiments, the altitude attenuation factor may also apply only to a 10-meter radius around the aircraft, thereby reducing computational load.

[0048] In this embodiment, the three-dimensional heatmap of mobile communication service quality can reflect the multipath interference distribution in low-altitude three-dimensional space. Furthermore, combined with the efficient and accurate data acquisition mentioned above, it can achieve heatmap updates within 20ms, solving the problem of heatmap update delay caused by low data sampling rate, thereby supporting real-time obstacle avoidance decisions for aircraft.

[0049] S13, determine multiple candidate paths based on the three-dimensional heat map of mobile communication service quality.

[0050] In this embodiment, the multiple candidate paths can be determined by comprehensively considering environmental factors such as path length and real-time weather data.

[0051] S14, calculate the cost value of each candidate path, and select the candidate path with the lowest cost value from the multiple candidate paths as the target path.

[0052] In this embodiment, calculating the cost of each candidate path includes: Retrieve the subpaths of each candidate path: The path cost of each sub-path is calculated using the constructed path cost function: ;in, This represents the path cost of the current node n where the target aircraft is located; k is a constant used to adjust the weights of the path cost function. This represents the x-axis distance from the flight start point to the current node n; This represents the y-axis distance from the flight start point to the current node n; This represents the z-axis distance from the flight start point to the current node n; Indicates the penalty coefficient for height variation; The heuristic cost of each subpath is calculated using the constructed heuristic function: ;in, This represents the heuristic cost of the current node n, used to measure the heuristically estimated total length from the current node n to the end of each sub-path; This represents the x-axis coordinate of the endpoint of each sub-path; This represents the x-axis coordinate of the current node n; This represents the y-axis coordinate of the endpoint of each sub-path; This represents the y-axis coordinate of the current node n; This represents the z-axis coordinate of the endpoint of each sub-path; This represents the z-axis coordinate of the current node n; The communication cost of each sub-path is calculated using the constructed communication quality factor function: ;in, This represents the communication cost of the current node n; The target mobile communication service quality represents the current node n; t represents the current time. The time-degradation coefficient representing the quality of mobile communication services; The first weighting coefficient is calculated using the following formula: ;in, d represents the first weight coefficient; d represents the path length of each sub-path; D represents the heuristically estimated total length of each sub-path. The second weighting coefficient is calculated using the following formula: Where β represents the second weighting coefficient; The cost of each sub-path is calculated by weighting the path cost, heuristic cost, and communication cost together using the following formula: f(n) = α*g(n) + β*h(n) + γ*q(n); where f(n) represents the cost of traversing each sub-path from the current node n; γ represents the third weight coefficient, and the value of γ is adjusted according to the emphasis on communication quality in the current scenario. Calculate the sum of the cost values ​​of each sub-path corresponding to each candidate path to obtain the cost value of each candidate path.

[0053] Since the flight path is not necessarily a straight line, a candidate path may consist of multiple connected sub-paths. For example, when the flight start point is A and the flight end point is C, there may be an intermediate node B between A and C. That is to say, the candidate path AC consists of sub-paths AB and BC.

[0054] For any node (x, y, z), the x / y axes correspond to latitude and longitude, and the z-axis corresponds to altitude.

[0055] in, It can take the value 2.

[0056] The heuristic total length estimate can be the Euclidean distance estimate from the current node to the endpoint of each sub-path.

[0057] in, The value can be 5s.

[0058] Among them, α, β, and γ are dynamic weighting coefficients that can help achieve a balance between exploration and development.

[0059] The value of γ can be set to 1 by default. Furthermore, to facilitate parameter tuning, the sum of α, β, and γ can be fixed at 3, which facilitates debugging and optimization and limits deviations caused by excessively large or small weights.

[0060] In the above embodiments, by introducing cost, more accurate three-dimensional path planning can be achieved.

[0061] S15, control the target aircraft to fly to the flight destination along the target path.

[0062] In this embodiment, the method further includes: During the process of controlling the target aircraft to fly to the destination along the target path, when the rate of decline in real-time mobile communication service quality is detected to be greater than the deceleration threshold, the current position of the target aircraft is obtained, and the path is replanned based on the current position. Furthermore, the frequency of non-critical data transmission is reduced, data packets are compressed, and the modulation scheme is optimized; or When the real-time mobile communication service quality is detected to be lower than a first threshold, and the continuous mobile communication service quality within a preset duration is lower than a second threshold, the system switches to Message Queuing Telemetry Transport (MQTT) degradation mode to transmit only core control and status data. It avoids areas where the real-time mobile communication service quality is lower than the first threshold by slowing down and / or hovering, suspends high-bandwidth applications, caches non-real-time data, and issues a low mobile communication service quality warning; wherein the second threshold is greater than the first threshold; or When the real-time mobile communication service quality is detected to be less than the third threshold or the communication interruption duration is greater than the duration threshold, the system switches to a backup channel and transmits simplified status packets in the backup channel at preset time intervals, initiates autonomous return or safe hovering mode, records logs and issues an emergency alarm; wherein the third threshold is less than the first threshold.

[0063] For example, the deceleration threshold can be configured to 20% / s, the first threshold can be configured to 60, the preset duration can be configured to 5s, the second threshold can be configured to 75, the third threshold can be configured to 30, the duration threshold can be configured to 2s, and the preset time interval can be configured to 10s.

[0064] When replanning the route based on the current location, high QoS paths can be prioritized, such as exploring green areas with QoS ≥ 80, while avoiding areas marked as impassable. If no path with QoS ≥ 80 is available, temporary passage through yellow areas with QoS 60 ≤ QoS < 80 is permitted, but the flight speed must be reduced (e.g., to 50% of the original speed).

[0065] The non-critical data may be video.

[0066] The message queue telemetry transmission degradation mode can have a minimum guaranteed rate of 512bps.

[0067] The backup channel can be a LoRa (Long Range) channel.

[0068] The simplified state packet refers to a data packet obtained by optimizing the state data packet related to the system, software, or data, removing redundant information, unnecessary functions, or files, in order to reduce the size and improve performance.

[0069] Among them, when initiating autonomous return or safe hovering, only a high QoS path can be used.

[0070] Through the above embodiments, the flight path can be dynamically adjusted according to the real-time changes in mobile communication service quality during flight, thereby further ensuring flight safety.

[0071] In this embodiment, after controlling the target aircraft to fly to the flight destination along the target path, the method further includes: The target path is recorded in the path pool, and the flight start point and the flight destination are stored using a hash table.

[0072] The above embodiments enable the reuse of historical optimal paths, avoiding repeated path planning for the same flight start and end points, thereby improving path planning efficiency.

[0073] In this embodiment, the parallel computing capabilities of a GPU (Graphics Processing Unit) can be used to accelerate the aforementioned data processing and analysis process.

[0074] As can be seen from the above technical solutions, on the one hand, using Berkeley packet filters to assist in the collection of mobile communication data in the monitoring area can achieve nanosecond-level timestamp marking, thereby improving the accuracy of latency measurement; on the other hand, during flight, generating a three-dimensional heat map of mobile communication service quality in the monitoring area based on altitude attenuation factor and mobile communication data can accurately predict the mobile communication service quality in three-dimensional space, providing accurate real-time obstacle avoidance decision-making basis for subsequent aircraft path planning; furthermore, calculating the cost of each candidate path, selecting the candidate path with the lowest cost as the target path, and controlling the target aircraft to fly to the flight destination along the target path can achieve more accurate three-dimensional path planning by introducing path cost, thereby increasing the success rate of the aircraft reaching the destination quickly and safely.

[0075] like Figure 2 The diagram shown is a functional block diagram of a preferred embodiment of the communication-optimized aircraft path planning device of the present invention. The communication-optimized aircraft path planning device 11 includes an acquisition unit 110, a data collection unit 111, a generation unit 112, a determination unit 113, a selection unit 114, and a control unit 115. The module / unit referred to in this invention is a series of computer program segments that can be executed by a processor and perform a fixed function, stored in memory. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0076] The acquisition unit 110 is used to acquire the monitoring area from the flight start point to the flight end point in response to the path planning command of the target aircraft. The acquisition unit 111 is used to collect mobile communication data of the monitored area using a Berkeley packet filter; The generation unit 112 is used to generate a three-dimensional heat map of the mobile communication service quality of the monitored area based on the altitude attenuation factor and the mobile communication data during flight. The determining unit 113 is used to determine multiple candidate paths based on the three-dimensional heat map of mobile communication service quality. The selection unit 114 is used to calculate the cost value of each candidate path and select the candidate path with the lowest cost value from the plurality of candidate paths as the target path. The control unit 115 is used to control the target aircraft to fly to the flight destination along the target path.

[0077] As can be seen from the above technical solutions, on the one hand, using Berkeley packet filters to assist in the collection of mobile communication data in the monitoring area can achieve nanosecond-level timestamp marking, thereby improving the accuracy of latency measurement; on the other hand, during flight, generating a three-dimensional heat map of mobile communication service quality in the monitoring area based on altitude attenuation factor and mobile communication data can accurately predict the mobile communication service quality in three-dimensional space, providing accurate real-time obstacle avoidance decision-making basis for subsequent aircraft path planning; furthermore, calculating the cost of each candidate path, selecting the candidate path with the lowest cost as the target path, and controlling the target aircraft to fly to the flight destination along the target path can achieve more accurate three-dimensional path planning by introducing path cost, thereby increasing the success rate of the aircraft reaching the destination quickly and safely.

[0078] like Figure 3 The diagram shown is a schematic representation of the computer device that implements a preferred embodiment of the communication-optimized aircraft path planning method of the present invention.

[0079] The computer device 1 may include a memory 12, a processor 13, and a bus (the arrow in the figure represents the bus), and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a communication-optimized aircraft path planning program.

[0080] Those skilled in the art will understand that the schematic diagram is merely an example of computer device 1 and does not constitute a limitation on computer device 1. Computer device 1 can be either a bus topology or a star topology. Computer device 1 may also include more or fewer other hardware or software than shown in the diagram, or different component arrangements. For example, computer device 1 may also include input / output devices, network access devices, etc.

[0081] It should be noted that the computer device 1 described is merely an example. Other existing or future electronic products that are adaptable to this invention should also be included within the scope of protection of this invention and are incorporated herein by reference.

[0082] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the computer device 1, such as a portable hard drive of the computer device 1. In other embodiments, the memory 12 can be an external storage device of the computer device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the computer device 1. Furthermore, the memory 12 can include both internal and external storage units of the computer device 1. The memory 12 can be used not only to store application software and various types of data installed on the computer device 1, such as the code of a communication-optimized aircraft path planning program, but also to temporarily store data that has been output or will be output.

[0083] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the computer device 1, connecting various components of the computer device 1 via various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., executing a communication-optimized aircraft path planning program) and calls data stored in the memory 12 to perform various functions of the computer device 1 and process data.

[0084] The processor 13 executes the operating system of the computer device 1 and various installed applications. The processor 13 executes these applications to implement the steps in the various embodiments of the communication-optimized aircraft path planning method described above, for example... Figure 1 The steps are shown.

[0085] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present invention. The one or more modules / units may be a series of computer-readable instruction segments capable of performing a specific function, which describe the execution process of the computer program in the computer device 1. For example, the computer program may be divided into an acquisition unit 110, a collection unit 111, a generation unit 112, a determination unit 113, a selection unit 114, and a control unit 115.

[0086] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium. This software functional module, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute portions of the communication-optimized aircraft path planning method described in the various embodiments of this invention.

[0087] If the modules / units integrated in the computer device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware devices. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0088] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, etc.

[0089] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.

[0090] The blockchain referred to in this invention is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0091] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, in... Figure 3 The bus is represented by only one straight line, but this does not mean that there is only one bus or one type of bus. The bus is configured to enable communication between the memory 12 and at least one processor 13, etc.

[0092] Although not shown, the computer device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 13 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The computer device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0093] Furthermore, the computer device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the computer device 1 and other computer devices.

[0094] Optionally, the computer device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the computer device 1 and to display a visual user interface.

[0095] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0096] It will be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0097] Combination Figure 1 The memory 12 in the computer device 1 stores multiple instructions to implement a communication-optimized aircraft path planning method, and the processor 13 can execute the multiple instructions to achieve the following: In response to path planning instructions for the target aircraft, acquire the monitoring area from the flight start point to the flight end point; Berkeley packet filters were used to assist in the collection of mobile communication data in the monitored area. During flight, a three-dimensional heat map of the mobile communication service quality of the monitored area is generated based on the altitude attenuation factor and the mobile communication data. Multiple candidate paths are determined based on the three-dimensional heatmap of mobile communication service quality; Calculate the cost value of each candidate path, and select the candidate path with the lowest cost value from the multiple candidate paths as the target path; Control the target aircraft to fly to the flight destination along the target path.

[0098] Specifically, the processor 13's implementation method for the above instructions can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0099] It should be noted that all data involved in this case was legally obtained. Software tools or components not belonging to this company that appear in the embodiments of this application are merely illustrative examples and do not represent actual use.

[0100] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0101] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0102] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0103] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0104] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0105] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0106] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in this invention can also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A communication-optimized aircraft path planning method, characterized in that, The communication-optimized aircraft path planning method includes: In response to path planning instructions for the target aircraft, acquire the monitoring area from the flight start point to the flight end point; Berkeley packet filters were used to assist in the collection of mobile communication data in the monitored area. During flight, a three-dimensional heat map of the mobile communication service quality of the monitored area is generated based on the altitude attenuation factor and the mobile communication data. Multiple candidate paths are determined based on the three-dimensional heatmap of mobile communication service quality; Calculate the cost value of each candidate path, and select the candidate path with the lowest cost value from the multiple candidate paths as the target path; Control the target aircraft to fly to the flight destination along the target path.

2. The aircraft path planning method based on communication optimization as described in claim 1, characterized in that, After acquiring the monitoring area from the flight start point to the flight end point, the method further includes: Establish an offline 3D elevation database; The terrain features of the monitored area are preprocessed based on the offline 3D elevation database.

3. The aircraft path planning method based on communication optimization as described in claim 1, characterized in that, The use of Berkeley packet filters to assist in the collection of mobile communication data in the monitored area includes: The Berkeley packet filter is used to mark the transmission time of each message; The arrival time of each message is obtained by bypassing the mirror port and using the time when the message arrives at the corresponding receiver as the arrival time of each message. Calculate the difference between the arrival time and the corresponding sending time of each message to obtain the one-way delay of each message; The packet loss rate of the monitored area is calculated using a sliding window. Calculate the jitter in the monitored area; The one-way delay of each message, the packet loss rate, and the jitter are determined as the mobile communication data.

4. The aircraft path planning method based on communication optimization as described in claim 1, characterized in that, The process of generating a three-dimensional heat map of mobile communication service quality for the monitored area based on the height attenuation factor and the mobile communication data includes: The monitoring area is divided into multiple grids in a three-dimensional grid according to a preset grid unit. The initial mobile communication service quality for each grid is calculated using the following formula: QoS = w1 * exp(-Latency / τ) + w2 * (1 - Jitter / J max )+w3*(1-LossRate); where QoS represents the initial mobile communication service quality of each grid; w1, w2, and w3 represent weighting coefficients; Latency represents the one-way latency of each grid; τ represents the latency attenuation coefficient of each grid; Jitter represents the jitter of each grid, J max This represents the maximum tolerable jitter for each grid cell; LossRate represents the packet loss rate for each grid cell. The height attenuation factor is constructed using the following formula: (h)=1 / (1+p*(hh ref ) 2 );in, (h) represents the altitude attenuation factor of the target aircraft at a real-time flight altitude of h; p represents the attenuation coefficient; h ref Indicates the height of the base station antenna; The target mobile communication service quality for each grid is obtained by multiplying the initial mobile communication service quality for each grid with the corresponding height attenuation factor. The three-dimensional heatmap of mobile communication service quality is generated based on the mapping rules between mobile communication service quality and color.

5. The aircraft path planning method based on communication optimization as described in claim 4, characterized in that, The calculation of the cost of each candidate path includes: Get the subpaths of each candidate path: The path cost of each sub-path is calculated using the constructed path cost function: ;in, This represents the path cost of the current node n where the target aircraft is located; k is a constant used to adjust the weights of the path cost function. This represents the x-axis distance from the flight start point to the current node n; This represents the y-axis distance from the flight start point to the current node n; This represents the z-axis distance from the flight start point to the current node n; Indicates the penalty coefficient for height variation; The heuristic cost of each subpath is calculated using the constructed heuristic function: ;in, This represents the heuristic cost of the current node n, used to measure the heuristically estimated total length from the current node n to the end of each sub-path; This represents the x-axis coordinate of the endpoint of each sub-path; This represents the x-axis coordinate of the current node n; This represents the y-axis coordinate of the endpoint of each sub-path; This represents the y-axis coordinate of the current node n; This represents the z-axis coordinate of the endpoint of each sub-path; This represents the z-axis coordinate of the current node n; The communication cost of each sub-path is calculated using the constructed communication quality factor function: ;in, This represents the communication cost of the current node n; The target mobile communication service quality represents the current node n; t represents the current time. The time-degradation coefficient representing the quality of mobile communication services; The first weighting coefficient is calculated using the following formula: ;in, d represents the first weight coefficient; d represents the path length of each sub-path; D represents the heuristically estimated total length of each sub-path. The second weighting coefficient is calculated using the following formula: Where β represents the second weighting coefficient; The cost of each sub-path is calculated by weighting the path cost, heuristic cost, and communication cost together using the following formula: f(n) = α*g(n) + β*h(n) + γ*q(n); where f(n) represents the cost of traversing each sub-path from the current node n; γ represents the third weight coefficient, and the value of γ is adjusted according to the emphasis on communication quality in the current scenario. Calculate the sum of the cost values ​​of each sub-path corresponding to each candidate path to obtain the cost value of each candidate path.

6. The aircraft path planning method based on communication optimization as described in claim 1, characterized in that, The method further includes: During the process of controlling the target aircraft to fly to the destination along the target path, when the rate of decline in real-time mobile communication service quality is detected to be greater than the deceleration threshold, the current position of the target aircraft is obtained, and the path is replanned based on the current position. Furthermore, the frequency of non-critical data transmission is reduced, data packets are compressed, and the modulation scheme is optimized; or When the real-time mobile communication service quality is detected to be lower than a first threshold, and the continuous mobile communication service quality within a preset duration is lower than a second threshold, the system switches to message queue telemetry transmission degradation mode to transmit only core control and status data. It avoids areas where the real-time mobile communication service quality is lower than the first threshold by slowing down and / or hovering, suspends high-bandwidth applications, caches non-real-time data, and issues a low mobile communication service quality warning; wherein the second threshold is greater than the first threshold; or When the real-time mobile communication service quality is detected to be less than the third threshold or the communication interruption duration is greater than the duration threshold, the system switches to a backup channel and transmits simplified status packets in the backup channel at preset time intervals, initiates autonomous return or safe hovering mode, records logs and issues an emergency alarm; wherein the third threshold is less than the first threshold.

7. The aircraft path planning method based on communication optimization as described in claim 1, characterized in that, After controlling the target aircraft to fly along the target path to the flight destination, the method further includes: The target path is recorded in the path pool, and the flight start point and the flight destination are stored using a hash table.

8. A communication-optimized aircraft path planning device, characterized in that, The communication-optimized aircraft path planning device includes: The acquisition unit is used to acquire the monitoring area from the flight start point to the flight end point in response to the path planning command of the target aircraft; The acquisition unit is used to collect mobile communication data of the monitored area with the assistance of Berkeley packet filters; The generation unit is used to generate a three-dimensional heat map of the mobile communication service quality of the monitored area based on the altitude attenuation factor and the mobile communication data during flight. A determining unit is configured to determine multiple candidate paths based on the three-dimensional heatmap of mobile communication service quality. The selection unit is used to calculate the cost value of each candidate path and select the candidate path with the lowest cost value from the plurality of candidate paths as the target path. The control unit is used to control the target aircraft to fly to the flight destination along the target path.

9. A computer device, characterized in that, The computer device includes: Memory, storing at least one instruction; and The processor executes instructions stored in the memory to implement the communication-optimized aircraft path planning method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, which is executed by a processor in a computer device to implement the communication-optimized aircraft path planning method as described in any one of claims 1 to 7.

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