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

Abstract

The application relates to the technical field of communication, and provides a flight vehicle path planning method, device and equipment based on communication optimization and a medium. On the one hand, a Berkeley packet filter is used to assist in collecting mobile communication data of a monitoring area, and a nanosecond timestamp label can be realized, so that the time delay measurement precision is improved. On the other hand, during the flight, a mobile communication service quality three-dimensional heat map of the monitoring area is generated based on a height attenuation factor and the mobile communication data, the mobile communication service quality of a three-dimensional space can be accurately predicted, and accurate real-time obstacle avoidance decision basis is provided for subsequent flight vehicle path planning. On the other hand, the generation cost of each candidate path is calculated, the candidate path with the lowest generation cost is selected as a target path, and the target flight vehicle is controlled to fly to a flight end point according to the target path. More accurate three-dimensional path planning can be realized by introducing the path generation cost, so that the success rate of the flight vehicle quickly and safely reaching the end point is higher.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a communication optimization-based aircraft path planning method, device, equipment and medium. BACKGROUND

[0002] With the continuous development of low-altitude economy, how to accurately monitor the mobile communication service quality of the aircraft during flight and scientifically plan the flight path based thereon has become a problem to be solved.

[0003] To solve the above problems, the prior art mainly has the following problems:

[0004] (1) The prior art usually measures the delay by using the application layer RTT (Round-Trip Time), which needs to wait for the TCP ACK (Transmission Control Protocol Acknowledgment) confirmation mechanism, resulting in a minimum measurement interval ≥ 200 ms, which cannot capture the burst microsecond-level jitter (such as <10 ms instantaneous packet loss caused by 5G (the 5th Generation Mobile Communication Technology) base station switching);

[0005] (2) The prior art mainly relies on MAC (Media Access Control) layer RSRP (Reference Signal Received Power) measurement, and the two-dimensional plane signal strength map cannot reflect the multipath interference distribution in the three-dimensional space below 120 meters;

[0006] (3) The prior art mainly uses traditional NetFlow (network flow) to collect data, with a sampling rate ≤ 1%, resulting in a packet loss rate calculation error > 300%, a heat map update delay > 5 seconds, and the inability to support real-time obstacle avoidance decision-making of aircraft such as unmanned aerial vehicles. SUMMARY

[0007] In view of the above, it is necessary to provide a communication optimization-based aircraft path planning method, device, equipment and medium, which aims to solve the problem of poor aircraft path planning due to inaccurate and untimely monitoring of low-altitude economy mobile communication service quality.

[0008] A communication optimization-based aircraft path planning method, the communication optimization-based aircraft path planning method comprising:

[0009] In response to a path planning instruction for a target aircraft, a monitoring area from a flight starting point to a flight ending point is obtained;

[0010] collecting mobile communication data of the monitoring area by using a Berkeley packet filter;

[0011] generating a three-dimensional heat map of mobile communication service quality of the monitoring area based on a height attenuation factor and the mobile communication data during the flight;

[0012] determining a plurality of candidate paths according to the three-dimensional heat map of mobile communication service quality;

[0013] calculating a value of each candidate path, and selecting a candidate path with the lowest value as a target path from the plurality of candidate paths;

[0014] controlling the target aircraft to fly to the flight end point according to the target path.

[0015] According to the preferred embodiment of the present application, after the monitoring area between the flight start point and the flight end point is obtained, the method further comprises:

[0016] establishing an offline three-dimensional elevation database;

[0017] preprocessing terrain features of the monitoring area according to the offline three-dimensional elevation database.

[0018] According to the preferred embodiment of the present application, the collecting mobile communication data of the monitoring area by using a Berkeley packet filter comprises:

[0019] labeling a sending time of each packet by using the Berkeley packet filter;

[0020] obtaining a time when each packet arrives at a corresponding receiving end as an arrival time of each packet through a bypass mirror port;

[0021] calculating a difference between the arrival time and the corresponding sending time of each packet to obtain a one-way delay of each packet;

[0022] calculating a packet loss rate of the monitoring area by using a sliding window;

[0023] calculating a jitter of the monitoring area;

[0024] determining the one-way delay of each packet, the packet loss rate and the jitter as the mobile communication data.

[0025] According to the preferred embodiment of the present application, the generating a three-dimensional heat map of mobile communication service quality of the monitoring area based on a height attenuation factor and the mobile communication data during the flight comprises:

[0026] performing three-dimensional grid division on the monitoring area according to a preset grid unit to obtain a plurality of grids;

[0027] The initial mobile communication service quality of each grid is calculated by the following formula: QoS = w1*exp(-Latency / τ) + w2*(1-Jitter / J max )+w3*(1-LossRate); wherein, QoS represents the initial mobile communication service quality of each grid; w1, w2, w3 represent weight coefficients; Latency represents the one-way latency of each grid; τ represents the latency decay coefficient of each grid; Jitter represents the jitter of each grid, J max represents the maximum tolerable jitter of each grid; LossRate represents the packet loss rate of each grid;

[0028] The height decay factor is constructed by the following formula: (h) = 1 / (1+p*(h-h ref ) 2 ); wherein, (h) represents the height decay factor of the target aircraft at the real-time flight height h; p represents the decay coefficient; h ref represents the base station antenna height;

[0029] The initial mobile communication service quality of each grid is multiplied by the corresponding height decay factor to obtain the target mobile communication service quality of each grid;

[0030] The mobile communication service quality three-dimensional heat map is generated according to the mapping rule of the mobile communication service quality and the color.

[0031] According to the preferred embodiment of the present application, the calculation of the candidate path value of each candidate path comprises:

[0032] The sub-paths of each candidate path are obtained:

[0033] The path cost of each sub-path is calculated by the constructed path cost function: ; wherein, represents the path cost of the current node n where the target aircraft is located; k is a constant, used to adjust the weight of the path cost function; represents the x-axis distance from the flight starting point to the current node n; represents the y-axis distance from the flight starting point to the current node n; represents the z-axis distance from the flight starting point to the current node n; represents the height change penalty coefficient;

[0034] The heuristic cost of each sub-path is calculated by the constructed heuristic function: ; wherein, represents the heuristic cost of the current node n, used to measure the heuristic estimated total length from the current node n to the end point 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;

[0035] 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;

[0036] 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.

[0037] The second weighting coefficient is calculated using the following formula: Where β represents the second weighting coefficient;

[0038] 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.

[0039] 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.

[0040] According to a preferred embodiment of the present invention, the method further includes:

[0041] 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

[0042] switch to a message queue telemetry transport degradation mode to only transmit core control and status data, avoid the area where the real-time mobile communication service quality is less than the first threshold value by means of deceleration and / or hovering, suspend high-bandwidth applications, buffer non-real-time data, and issue a low mobile communication service quality warning when it is detected that the real-time mobile communication service quality is less than a first threshold value and the continuous mobile communication service quality in a preset time length is less than a second threshold value; wherein the second threshold value is greater than the first threshold value; or

[0043] switch to a backup channel and transmit a simplified status package in the backup channel every preset time interval, start autonomous return or safe hovering, record logs, and issue an emergency warning when it is detected that the real-time mobile communication service quality is less than a third threshold value or the communication interruption time length is greater than a time length threshold value; wherein the third threshold value is less than the first threshold value.

[0044] According to a preferred embodiment of the present application, after the control unit controls the target aircraft to fly to the flight endpoint according to the target path, the method further comprises:

[0045] storing the flight endpoint and the flight endpoint in a hash table.

[0046] A communication optimization-based aircraft path planning device, comprising:

[0047] an acquisition unit configured to acquire a monitoring area between a flight starting point and a flight endpoint in response to a path planning instruction for a target aircraft;

[0048] a collection unit configured to collect mobile communication data of the monitoring area with the aid of a Berkeley packet filter;

[0049] a generation unit configured to generate a mobile communication service quality three-dimensional heat map of the monitoring area based on a height attenuation factor and the mobile communication data during flight;

[0050] a determination unit configured to determine a plurality of candidate paths according to the mobile communication service quality three-dimensional heat map;

[0051] a selection unit configured to calculate a generation value of each candidate path and select a candidate path with the lowest generation value from the plurality of candidate paths as a target path;

[0052] a control unit configured to control the target aircraft to fly to the flight endpoint according to the target path.

[0053] A computer device, comprising:

[0054] a memory configured to store at least one instruction; and

[0055] a processor executing instructions stored in the memory to implement the method of communication-optimized aircraft path planning.

[0056] a computer-readable storage medium having stored therein at least one instruction to be executed by a processor in a computer device to implement the method of communication-optimized aircraft path planning.

[0057] As can be seen from the above technical solutions, on the one hand, the Berkeley packet filter is used to assist in collecting mobile communication data of a monitoring area, so that a nanosecond-level timestamp can be marked, thereby improving the time delay measurement accuracy; on the other hand, during flight, a mobile communication service quality three-dimensional heat map of the monitoring area is generated based on a height attenuation factor and the mobile communication data, so that the mobile communication service quality of a three-dimensional space can be accurately predicted, thereby providing an accurate real-time obstacle avoidance decision basis for subsequent aircraft path planning; and on the other hand, the generation cost of each candidate path is calculated, the candidate path with the lowest generation cost is selected as a target path, and the target aircraft is controlled to fly to a flight end point according to the target path, so that more accurate three-dimensional path planning can be realized by introducing the path generation cost, thereby making the success rate of the aircraft quickly and safely reaching the end point higher. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 is a flowchart of a preferred embodiment of the method of communication-optimized aircraft path planning of the present application;

[0059] Figure 2 is a functional module diagram of a preferred embodiment of the device for communication-optimized aircraft path planning of the present application;

[0060] Figure 3 is a structural schematic diagram of a computer device of a preferred embodiment of the present application for implementing the method of communication-optimized aircraft path planning. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described in detail below in combination with the drawings and specific embodiments.

[0062] As Figure 1 shown, is a flowchart of a preferred embodiment of the method of communication-optimized aircraft path planning of the present application. The order of the steps in the flowchart can be changed according to different needs, and some steps can be omitted.

[0063] The communication optimization-based aircraft path planning method is applied to one or more computer devices, which is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions. The hardware thereof includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0064] The computer device can be any electronic product capable of human-computer interaction with the user, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive Internet Protocol Television (IPTV), a smart wearable device, etc.

[0065] The computer device can also include a network device and / or a user device. The network device includes but is not limited to a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing.

[0066] The server can be a standalone server or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and basic cloud computing services such as big data and artificial intelligence platforms.

[0067] Artificial intelligence (AI) is the use of digital computers or computer-controlled machines to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results.

[0068] The basic technology of artificial intelligence generally includes technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. The software technology of artificial intelligence mainly includes computer vision technology, robot technology, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning, etc.

[0069] The network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), and the like.

[0070] S10, in response to the path planning instruction of the target aircraft, obtaining a monitoring area from a flight starting point to a flight ending point.

[0071] In the embodiment, the target aircraft can be an aircraft in the low-altitude economic field such as a drone.

[0072] In the embodiment, the path planning instruction can be automatically triggered when the target aircraft starts, so as to realize real-time monitoring and optimization of the whole flight process of the target aircraft.

[0073] In the embodiment, after the monitoring area from the flight starting point to the flight ending point is obtained, the method further includes:

[0074] establishing an offline three-dimensional elevation database;

[0075] performing terrain feature preprocessing on the monitoring area according to the offline three-dimensional elevation database.

[0076] Through the above embodiment, accurate terrain data can be provided for subsequent processing, so as to improve the accuracy of calculation.

[0077] S11, collecting mobile communication data of the monitoring area by using a Berkeley packet filter (BPF).

[0078] In the embodiment, the Berkeley packet filter can improve the time delay measurement accuracy based on the nanosecond-level timestamp marking technology, and the accuracy can be improved by 1000 times compared with the application layer scheme.

[0079] In the embodiment, the mobile communication data can include index data such as time delay, packet loss rate, and jitter of a mobile communication network such as 5G (the 5th Generation Mobile Communication Technology).

[0080] In the embodiment, the collecting of the mobile communication data of the monitoring area by using the Berkeley packet filter includes:

[0081] marking the sending time of each packet by using the Berkeley packet filter;

[0082] obtaining the arrival time of each packet at the corresponding receiving end as the arrival time of each packet by using a bypass mirror port;

[0083] Calculate the difference between the arrival time and the corresponding sending time of each packet to obtain the one-way delay of each packet;

[0084] Calculate the packet loss rate of the monitoring area using a sliding window;

[0085] Calculate the jitter of the monitoring area;

[0086] Determine the one-way delay of each packet, the packet loss rate, and the jitter as the mobile communication data.

[0087] For example, a BPF program can be injected at the Linux kernel data link layer of the target aircraft, and each TCP (Transport Control Protocol) or UDP (User Datagram Protocol) packet can be marked with an accurate sending time t1. The actual arrival time t2 at the receiving end can be obtained through a bypass mirror port, and the one-way delay (t2-t1) can be calculated.

[0088] For another example, the number of sent packets Nsent and the number of received packets Nreceived in the last 1 second can be counted using a sliding window, so as to dynamically update the packet loss rate: (Nsent-Nreceived) / Nsent.

[0089] For another example, assume that ΔDi=|D(i)-D(i-1)|; where D(i) represents the one-way delay of the i-th packet; D(i-1) represents the one-way delay of the (i-1)-th packet; and the reference jitter , specifically, the reference jitter Jitterbase can be calculated using the first 100 packets, and the relative value can be calculated subsequently; then the jitter ; where represents a smoothing factor (0.9), which is used to suppress transient fluctuations; and Jitterprev represents the jitter obtained by the last calculation.

[0090] In this embodiment, FPGA (Field-Programmable Gate Array) hardware acceleration can be used to process data packets, thereby improving the data acquisition efficiency.

[0091] S12, during the flight, generate a mobile communication service quality three-dimensional heat map of the monitoring area based on the height attenuation factor and the mobile communication data.

[0092] In this embodiment, generating a mobile communication service quality three-dimensional heat map of the monitoring area based on the height attenuation factor and the mobile communication data includes: ​

[0093] According to the preset grid unit, the monitoring area is stereoscopic grid divided, and a plurality of grids are obtained;

[0094] The initial mobile communication service quality of each grid is calculated by using the following formula: QoS=w1*exp(-Latency / τ)+w2*(1-Jitter / J max )+w3*(1-LossRate); wherein, QoS represents the initial mobile communication service quality of each grid; w1, w2, w3 represent weight coefficients; Latency represents the one-way delay of each grid; τ represents the delay attenuation coefficient of each grid; Jitter represents the jitter of each grid, J max represents the maximum tolerable jitter of each grid; and LossRate represents the packet loss rate of each grid.

[0095] The height attenuation factor is constructed by using the following formula: (h)=1 / (1+p*(h-h ref ) 2 ); wherein, (h) represents the height attenuation factor of the target aircraft at the real-time flight height h; p represents an attenuation coefficient; h ref represents the height of the base station antenna.

[0096] The product of the initial mobile communication service quality of each grid and the corresponding height attenuation factor is calculated to obtain the target mobile communication service quality of each grid.

[0097] According to the mapping rule of the mobile communication service quality and the color, the three-dimensional heat map of the mobile communication service quality is generated.

[0098] The preset grid unit can be configured according to actual needs, for example: the preset grid unit can be 1m×1m×0.5m.

[0099] For example: τ=20ms, J max =50ms, w1+w2+w3=1, and p=0.05 / m².

[0100] For example: the mapping rule can be represented as follows:

[0101] Red (QoS<60): indicating a high risk area of communication interruption;

[0102] Yellow (60≤QoS<80): indicating that the flight speed needs to be reduced to pass through;

[0103] Green (QoS≥80): indicating an optimal passing area.

[0104] In the embodiment, WebGL 2.0 (Web Graphics Library 2.0) can be used to realize browser-side rendering, and 2 million meshes can be updated in real time, so as to realize the visualization engine.

[0105] In the embodiment, Three.js (Three JavaScript) and other visualization technologies can also be used to realize browser-side rendering, so as to support the visualization display of the mobile communication service quality three-dimensional heat map, and facilitate user analysis and viewing.

[0106] In the above embodiment, the height attenuation factor can be introduced to generate a more accurate heat map, thereby providing a high-quality data basis for subsequent path planning.

[0107] In other embodiments, the height attenuation factor can also only act on the 10 meters around the aircraft, thereby reducing the calculation amount.

[0108] In the embodiment, the mobile communication service quality three-dimensional heat map can reflect the multipath interference distribution of the low-altitude three-dimensional space, and in combination with the efficient and accurate data collection, the heat map can be updated within 20 ms, thereby solving the heat map update delay problem caused by low data sampling rate, and supporting real-time obstacle avoidance decision of the aircraft.

[0109] S13, determining a plurality of candidate paths according to the mobile communication service quality three-dimensional heat map.

[0110] In the embodiment, the plurality of candidate paths can be determined by comprehensively considering path length, real-time weather data and other environmental factors.

[0111] S14, calculating the generation value of each candidate path, and selecting a candidate path with the lowest generation value from the plurality of candidate paths as a target path.

[0112] In the embodiment, the calculation of the generation value of each candidate path includes:

[0113] obtaining a sub-path of each candidate path:

[0114] calculating the path cost of each sub-path by using the constructed path cost function: ; wherein, denotes the path cost of the current node n where the target aircraft is located; k is a constant, used to adjust the weight of the path cost function; denotes the x-axis distance from the flight starting point to the current node n; denotes the y-axis distance from the flight starting point to the current node n; denotes the z-axis distance from the flight starting point to the current node n; denotes a height change penalty coefficient;

[0115] The heuristic cost of each sub-path is calculated by using the constructed heuristic function: ; wherein, denotes the heuristic cost of the current node n, which is used to measure the heuristic estimated total length from the current node n to the end point of each sub-path; denotes the x-axis coordinate value of the end point of each sub-path; denotes the x-axis coordinate value of the current node n; denotes the y-axis coordinate value of the end point of each sub-path; denotes the y-axis coordinate value of the current node n; denotes the z-axis coordinate value of the end point of each sub-path; denotes the z-axis coordinate value of the current node n;

[0116] The communication cost of each sub-path is calculated by using the constructed communication quality factor function: ; wherein, denotes the communication cost of the current node n; denotes the target mobile communication service quality of the current node n; t denotes the current time; denotes the timeliness decay coefficient of the mobile communication service quality;

[0117] The first weight coefficient is calculated by using the following formula: ; wherein, denotes the first weight coefficient; d denotes the path length of each sub-path; D denotes the heuristic estimated total length of each sub-path;

[0118] The second weight coefficient is calculated by using the following formula: ; wherein, β denotes the second weight coefficient;

[0119] The path cost of each sub-path is calculated by using the following formula: ; wherein, f(n) denotes the value of each sub-path; γ denotes the third weight coefficient, and the value of γ is adjusted according to the emphasis on the communication quality in the current scenario;

[0120] The sum of the value of each sub-path corresponding to each candidate path is calculated to obtain the value of each candidate path.

[0121] Wherein, since the flight path is not necessarily a straight line, one candidate path can be composed of multiple connected sub-paths. For example, when the flight starting point is A and the flight ending point is C, there can be an intermediate node B between A and C, that is, the candidate path AC is composed of the sub-path AB and the sub-path BC.

[0122] Wherein, for any node (x, y, z), the x / y axis corresponds to the latitude and longitude, and the z axis corresponds to the altitude.

[0123] Wherein, Can take the value of 2.

[0124] Wherein, the heuristic estimated total length can be the Euclidean distance estimation from the current node to the end point of each sub-path.

[0125] Wherein, Can take the value of 5s.

[0126] Wherein, α, β, γ are dynamic weight coefficients, which can assist in achieving the balance between exploration and development.

[0127] Wherein, the value of γ can be defaulted to 1. And in order to facilitate parameter tuning, the sum of α, β, and γ can be fixed to 3, so as to facilitate debugging and optimization, and limit the deviation caused by too large or too small weight.

[0128] In the above embodiment, by introducing the generation value, more accurate three-dimensional path planning can be achieved.

[0129] S15, control the target aircraft to fly to the flight ending point according to the target path.

[0130] In the embodiment, the method further comprises:

[0131] In the process of controlling the target aircraft to fly to the flight ending point according to the target path, when it is detected that the real-time mobile communication service quality decline rate is greater than the decline threshold, the current position of the target aircraft is obtained, and path planning is re-performed according to the current position, and the non-critical data transmission frequency is reduced, the transmission data packet is compressed, and the modulation mode is optimized; or

[0132] switch to a Message Queuing Telemetry Transport (MQTT) degraded mode to transmit only core control and status data, avoid the area where the real-time mobile communication service quality is less than the first threshold value by means of deceleration and / or hovering, suspend high-bandwidth applications, buffer non-real-time data, and issue a warning of low mobile communication service quality when it is detected that the real-time mobile communication service quality is less than a first threshold value and the continuous mobile communication service quality in a preset time length is less than a second threshold value; wherein the second threshold value is greater than the first threshold value; or

[0133] switch to a backup channel and transmit a simplified status packet in the backup channel at a preset time interval, start autonomous return or safe hovering, record logs, and issue an emergency warning when it is detected that the real-time mobile communication service quality is less than a third threshold value or the communication interruption time length is greater than a time length threshold value; wherein the third threshold value is less than the first threshold value.

[0134] For example, the deceleration threshold value can be configured as 20% / s, the first threshold value can be configured as 60, the preset time length can be configured as 5s, the second threshold value can be configured as 75, the third threshold value can be configured as 30, the time length threshold value can be configured as 2s, and the preset time interval can be configured as 10s.

[0135] In the path planning according to the current position, a high-QoS path can be searched preferentially, such as a green area with a QoS of 80 or more, and areas marked as impassable are avoided. If there is no path with a QoS of 80 or more, temporary passage through a yellow area with a QoS of 60 to less than 80 is allowed, but the flight speed needs to be reduced (e.g., to 50% of the original flight speed).

[0136] The non-critical data can be video.

[0137] The MQTT degraded mode can have a minimum guaranteed rate of 512 bps.

[0138] The backup channel can be a LoRa (Long Range) channel.

[0139] The simplified status packet refers to a data packet related to the state of the system, software, or data, which is optimized to remove redundant information, unnecessary functions or files, to achieve the purpose of reducing size and improving performance.

[0140] In the autonomous return or safe hovering mode, only a high-QoS path can be used.

[0141] Through the above embodiment, the path can be dynamically adjusted according to the real-time mobile communication service quality change in the flight process, so as to further ensure the flight safety.

[0142] In the embodiment, after the target aircraft is controlled to fly to the flight end point along the target path, the method further comprises:

[0143] The target path is recorded to a path pool, and the flight start point and the flight end point are stored by using a hash table.

[0144] Through the above embodiment, the reuse of the historical optimal path can be supported, and the repeated path planning of the same flight start point and flight end point can be avoided, so as to improve the path planning efficiency.

[0145] In the embodiment, the GPU (Graphics Processing Unit, graphics processor) parallel computing capability can be used to accelerate the above data processing and analysis process.

[0146] It can be seen from the above technical solutions that, on the one hand, the Berkeley packet filter is used to assist in collecting mobile communication data of the monitoring area, so as to realize nanosecond-level timestamp marking and improve the time delay measurement accuracy; on the other hand, during the flight process, the mobile communication service quality three-dimensional heat map of the monitoring area is generated based on the height attenuation factor and the mobile communication data, so as to accurately predict the mobile communication service quality of the three-dimensional space and provide accurate real-time obstacle avoidance decision basis for subsequent aircraft path planning; on the other hand, the generation cost of each candidate path is calculated, the candidate path with the lowest generation cost is selected as the target path, and the target aircraft is controlled to fly to the flight end point along the target path, so that more accurate three-dimensional path planning can be realized by introducing the path generation cost, so that the success rate of the aircraft quickly and safely reaching the end point is higher.

[0147] As Figure 2 shown is a functional module diagram of a preferred embodiment of an aircraft path planning device based on communication optimization of the application. The aircraft path planning device based on communication optimization 11 comprises 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. The module / unit referred to by the application refers to a series of computer program segments that can be executed by a processor and can complete a fixed function, which are stored in a memory. In the embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0148] The acquisition unit 110 is configured to acquire a monitoring area between a flight start point and a flight end point in response to a path planning instruction of a target aircraft.

[0149] The collection unit 111 is configured to collect the mobile communication data of the monitoring area by using a Berkeley packet filter.

[0150] The generation unit 112 is configured to generate a mobile communication service quality three-dimensional heat map of the monitoring area based on a height attenuation factor and the mobile communication data during flight.

[0151] The determination unit 113 is configured to determine a plurality of candidate paths according to the mobile communication service quality three-dimensional heat map.

[0152] The selection unit 114 is configured to calculate a cost value of each candidate path, and select a candidate path with the lowest cost value from the plurality of candidate paths as a target path.

[0153] The control unit 115 is configured to control the target aircraft to fly to the flight end point according to the target path.

[0154] According to the above technical solution, on one hand, the Berkeley packet filter is used to assist in collecting the mobile communication data of the monitoring area, so that the nanosecond timestamp marking can be realized, and the time delay measurement accuracy is improved; on the other hand, the mobile communication service quality three-dimensional heat map of the monitoring area is generated based on the height attenuation factor and the mobile communication data during flight, so that the mobile communication service quality of the three-dimensional space can be accurately predicted, and accurate real-time obstacle avoidance decision basis is provided for subsequent aircraft path planning; 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 the aircraft to quickly and safely reach the end point is higher.

[0155] As shown in Figure 3 FIG. 1 is a structural schematic diagram of a computer device according to a preferred embodiment of the present application.

[0156] The computer device 1 can include a memory 12, a processor 13 and a bus (the arrow in the figure is the bus), and can further include a computer program stored in the memory 12 and executable on the processor 13, such as an aircraft path planning program based on communication optimization.

[0157] Those skilled in the art can understand that the schematic diagram is only an example of the computer device 1, and does not limit the computer device 1, which can be a bus type structure or a star type structure, and the computer device 1 can further include more or less other hardware or software, or different component arrangements, such as the computer device 1 can further include an input / output device, a network access device, etc.

[0158] It should be noted that the computer device 1 is only an example, and other existing or future electronic products can also be applicable to the present application and should be included in the protection scope of the present application by reference.

[0159] The memory 12 includes at least one type of readable storage medium, such as a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 12 can be an internal storage unit of the computer device 1 in some embodiments, such as a mobile hard disk of the computer device 1. The memory 12 can also be an external storage device of the computer device 1 in other embodiments, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 1. Further, the memory 12 can include both an internal storage unit and an external storage device of the computer device 1. The memory 12 can be used to store application software and various data installed on the computer device 1, such as the code of the communication-optimized aircraft path planning program, and can also be used to temporarily store data that has been output or will be output.

[0160] The processor 13 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of a central processing unit (CPU), a microprocessor, a digital processing chip, a graphics processor, and various control chips, etc. The processor 13 is a control unit of the computer device 1, which connects various components of the computer device 1 through various interfaces and lines, executes programs or modules stored in the memory 12 (e.g., the communication-optimized aircraft path planning program, etc.), and calls data stored in the memory 12 to perform various functions and process data of the computer device 1.

[0161] The processor 13 executes an operating system and various application programs installed on the computer device 1. The processor 13 executes the application programs to implement the steps in each of the above communication-optimized aircraft path planning methods, such as the steps shown in the above embodiments. Figure 1 The steps shown in the above embodiments.

[0162] By way of example, the computer program can be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to accomplish the present application. The one or more modules / units can be a series of computer-readable instruction segments capable of accomplishing a specific function, which are used to describe the execution process of the computer program in the computer device 1. For example, the computer program can 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.

[0163] The integrated units implemented in the form of software functional modules can be stored in a computer-readable storage medium. The software functional modules stored in a storage medium include a number of instructions for causing a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to execute part of the communication optimization-based aircraft path planning method described in the embodiments of the present application.

[0164] The modules / units integrated in the computer device 1, if implemented in the form of software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the present application can also be implemented by instructing the relevant hardware devices to complete all or part of the processes of the above-mentioned embodiments by means of a computer program, which can be stored in a computer-readable storage medium and executed by a processor.

[0165] The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording media, U disks, mobile hard disks, magnetic disks, optical disks, computer memories, read-only memories (ROM), random access memories, and the like.

[0166] Further, the computer-readable storage medium can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, and the like; and the data storage area can store data created according to the use of the blockchain node, and the like.

[0167] The blockchain referred to in the present application is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm. The blockchain is essentially a decentralized database, and is a series of data blocks associated using cryptographic methods. Each data block contains information about a batch of network transactions, and is used to verify the validity of the information (anti-fake) and generate the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer.

[0168] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one straight line is used in the Figure 3 , but it does not mean that there is only one bus or one type of bus. The bus is arranged to enable connection and communication between the memory 12, the at least one processor 13, and the like.

[0169] Although not shown, the computer device 1 can also include a power supply (such as a battery) for powering the various components. Preferably, the power supply can be logically connected to the at least one processor 13 through a power management device, so that the power management device can realize functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more direct current or alternating current power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and the like. The computer device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, and the like, which will not be described here.

[0170] Further, the computer device 1 can also include a network interface. Optionally, the network interface can include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the computer device 1 and other computer devices.

[0171] Optionally, the computer device 1 can further comprise a user interface, which can be a display, an input unit such as a keyboard, and optionally a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED touch, etc. The display can also be appropriately referred to as a display screen or a display unit, for displaying information processed in the computer device 1 and for displaying a visualized user interface.

[0172] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by the structure.

[0173] Those skilled in the art can understand that, Figure 3 The structure shown does not constitute a limitation on the computer device 1, which can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0174] In combination Figure 1 The memory 12 in the computer device 1 stores a plurality of instructions to implement a communication optimization-based aircraft path planning method, and the processor 13 can execute the plurality of instructions to implement:

[0175] In response to a path planning instruction for a target aircraft, a monitoring area between a flight starting point and a flight ending point is acquired;

[0176] Mobile communication data of the monitoring area is collected with the aid of a Berkeley packet filter;

[0177] During flight, a mobile communication service quality three-dimensional heat map of the monitoring area is generated based on a height attenuation factor and the mobile communication data;

[0178] A plurality of candidate paths are determined according to the mobile communication service quality three-dimensional heat map;

[0179] The cost value of each candidate path is calculated, and the candidate path with the lowest cost value is selected as a target path from the plurality of candidate paths;

[0180] The target aircraft is controlled to fly to the flight ending point according to the target path.

[0181] Specifically, the specific implementation method of the processor 13 for the above instructions can refer to Figure 1 the description of related steps in the corresponding embodiments, which will not be repeated here.

[0182] It should be noted that the data involved in the case are all legally obtained. The non-company software tools or components appearing in the embodiments of the application are only used for example introduction, and do not represent actual use.

[0183] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented by other manners. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and another division manner can be used in actual implementation.

[0184] The application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The application can also be practiced in a distributed computing environment in which tasks are performed by remote processing devices connected by a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0185] The modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical units, i.e. they can be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0186] In addition, the functional modules in each embodiment of the application can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software function modules.

[0187] It is obvious for those skilled in the art that the application is not limited to the details of the above exemplary embodiments, and the application can be implemented in other specific forms without departing from the spirit or essential characteristics of the application.

[0188] Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are intended to be embraced therein. No reference is intended to be made to any disclaimer or disclaimer to limit the claims notwithstanding anything to the contrary contained in this patent or any patent accompanying drawing.

[0189] Furthermore, the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural, and vice-versa, unless the context clearly requires that. The indefinite articles "a" or "an" do not exclude a plurality, and the definite articles "the" or "that" do not exclude "the other", similarly hereinafter. The word "comprising" is used to mean "including" but not "consisting of".

[0190] Finally, it should be noted that the above-mentioned embodiments illustrate rather than limit the application, since the scope of the application is determined by the appended claims.

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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