CN116524763B - Data acquisition method for jointly optimizing flight trajectory and ground node transmitting power of unmanned aerial vehicle - Google Patents

Data acquisition method for jointly optimizing flight trajectory and ground node transmitting power of unmanned aerial vehicle Download PDF

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CN116524763B
CN116524763B CN202310553944.0A CN202310553944A CN116524763B CN 116524763 B CN116524763 B CN 116524763B CN 202310553944 A CN202310553944 A CN 202310553944A CN 116524763 B CN116524763 B CN 116524763B
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CN116524763A (en
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李敏
王洪
刘潇
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Chongqing University of Post and Telecommunications
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0043—Traffic management of multiple aircrafts from the ground
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/06—Traffic control systems for aircraft, e.g. air-traffic control [ATC] for control when on the ground
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention relates to a data acquisition method for jointly optimizing flight trajectory and ground node transmitting power of an unmanned aerial vehicle, and belongs to the field of unmanned aerial vehicle auxiliary wireless communication. According to the method, the acquisition track of the unmanned aerial vehicle is discretized, so that the initial node acquisition sequence with the shortest acquisition track is obtained; according to the initial node acquisition sequence, controlling node transmitting power according to the energy of each ground node and the data quantity to be transmitted, and sequentially obtaining the flight acquisition track of each node; under the condition of considering node energy and throughput, the flight track and the node transmitting power of the unmanned aerial vehicle are jointly optimized, and the flight time of the unmanned aerial vehicle data acquisition task is minimized. The invention has the advantages of practicality, simple and efficient implementation and low complexity, and is suitable for the auxiliary data acquisition of the actual unmanned aerial vehicle.

Description

Data acquisition method for jointly optimizing flight trajectory and ground node transmitting power of unmanned aerial vehicle
Technical Field
The invention belongs to the field of unmanned aerial vehicle auxiliary wireless communication, and relates to a data acquisition method for jointly optimizing flight track of an unmanned aerial vehicle and ground node transmitting power
Background
In recent years, unmanned aerial vehicles have been widely used in many fields such as air patrol, photography, parcel delivery, and air communication platforms. Unmanned aerial vehicles are able to perform tasks autonomously or semi-autonomously by configuring software programs, which is very attractive for some dangerous or urgent tasks, as no personnel involvement is required. Through the advantages of good visual link, high mobility and the like, the unmanned aerial vehicle can serve the nodes of the Internet of things in a short distance, and has higher line-of-sight channel probability, so that the communication quality and the service life of the wireless sensor nodes are improved.
Despite the many advantages of using unmanned aerial vehicle assisted wireless sensor networks, the problem of limited time of flight is still faced. The current research work has great guiding value for the application of unmanned aerial vehicle in reducing the flight time and assisting the communication of the ground nodes of the Internet of things. However, these studies do not adequately account for the energy of the ground nodes, and it is believed that the nodes can maintain a fixed maximum power transmission state to fulfill the upload throughput requirements. The larger the node transmitting power is, the shorter the unmanned aerial vehicle data acquisition time is, but the limited energy of the node limits the maximum transmitting power.
Disclosure of Invention
In view of the above, the invention aims to provide a data acquisition method for jointly optimizing the flight track of an unmanned aerial vehicle and the transmitting power of ground nodes, which aims at the limited energy of the ground nodes, increases the transmitting power of the nodes on the basis of ensuring that data can be transmitted, reduces the data acquisition time of the unmanned aerial vehicle, and shortens the task time of the unmanned aerial vehicle for serving the whole area.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a data acquisition method for jointly optimizing the flight trajectory of an unmanned aerial vehicle and the emission power of a ground node comprises the following steps:
s1, determining a node acquisition sequence S which enables an initial acquisition track of the unmanned aerial vehicle to be shortest according to ground node coordinates w ；
S2, establishing an unmanned aerial vehicle acquisition throughput maximization problem under two modes of flight acquisition and flight hover acquisition, and solving and obtaining a maximum throughput threshold under the two modes;
s3, judging a node acquisition sequence S according to the data quantity to be uploaded and the obtained throughput threshold value of each node w Whether each node can completely transmit data under the energy limit of the node; if not, the unmanned plane gives up the data acquisition of the node and goes to the next node; if yes, judging an acquisition mode of the unmanned aerial vehicle;
s4, according to the selected acquisition mode, jointly optimizing the transmitting power of the node and the track of the unmanned aerial vehicle, and minimizing the task completion time of the unmanned aerial vehicle;
s5, according to the node acquisition sequence S w And the acquisition tracks of all the nodes are sequentially connected, so that the unmanned aerial vehicle flight track with the minimum acquisition time is obtained, and the unmanned aerial vehicle completes data acquisition according to the flight track flight.
Further, the step S1 specifically includes: when determining the node acquisition sequence which enables the initial acquisition track of the unmanned aerial vehicle to be shortest, not considering the data acquisition task;
the number of the ground nodes is recorded as N, and the node acquisition sequence S w ＝(s w1 ,s w2 ,…,s wN ) Corresponding to the acquisition sequenceThe node coordinates are sequentially connected to obtain an initial acquisition track, and the total flight time T corresponding to the initial acquisition track is as follows:
in the method, in the process of the invention,the node coordinates arranged according to the acquisition sequence are represented, and v represents the speed of the unmanned aerial vehicle; converting the initial trajectory minimization problem of the unmanned aerial vehicle into a time-of-flight minimization problem:
converting the flight time minimization problem into a travel business problem and solving the travel business problem through a genetic algorithm to obtain a node acquisition sequence S w 。
Further, the step S2 specifically includes: when the unmanned aerial vehicle collects data, the unmanned aerial vehicle passes through the circle centers and the hovering point is positioned at the circle center of each circle (under the overlooking condition, the data transmission range of the nodes is a circle), namely, the unmanned aerial vehicle flies through and the hovering point is positioned right above each node, at the moment, the distance between the unmanned aerial vehicle and the ground nodes is minimum, the collection rate is maximum, and the unmanned aerial vehicle can obtain the maximum collection throughput; therefore, the problem of maximum throughput optimization of the unmanned aerial vehicle in the non-overlapping hovering acquisition mode of the node i is established, as follows:
s.t.R i (t)＝Wlog 2 (1+γ i (t)) (4)
in U i (t) represents the trajectory of the unmanned plane serving node i in time slot t, taken by the starting point SP i Entry point FIP i Hover point OH i And exit point FOP i Connection is formed;representing the center of a circle of a node i; />And->Respectively representing the transmitting power and the signal processing power of the node i; />Representing the total energy of the node i; p (P) min And P max Representing the minimum and maximum transmit powers of the nodes, respectively; r is R i (t) represents the transmission rate of the unmanned aerial vehicle in the time slot tW represents the channel bandwidth, gamma i (t) represents the signal to noise ratio between the drone and the node,represents the path loss, delta represents the path fading factor, < ->A signal-to-noise ratio threshold representing successful communication between the drone and the node; and->Respectively representing the flight time, the flight acquisition time and the hovering acquisition time of the unmanned aerial vehicle service node i;
solving the optimization problem by adopting a sequence least square method to obtain the maximum throughput, namely the maximum throughput of the unmanned aerial vehicle in a non-overlapping hovering acquisition mode
Similarly, when the unmanned aerial vehicle does not hover and collect above the node, the unmanned aerial vehicle is led toObtaining the maximum throughput in the non-overlapping flight acquisition mode by solving the throughput maximization problem>
Further, in step S3, according to the remaining energy of node iSelecting an acquisition mode:
1) When (when)In the case of->A non-overlapping hover acquisition mode is employed, and there are constraints: hover point OH i Fixed to GN i Directly above, i.e.)>If->Then further according to GN i -FIP i I and I GN i -SP i Judging the acquisition mode according to the magnitude of I; wherein C is i Indicating the amount of data to be transmitted for node i, GN i Representing coordinates of node i;
when GN i -FIP i ||＞||GN i -SP i When I, select overlapping flight acquisition mode, and SP i ＝FIP i ＝FOP i-1 ，When GN i -FIP i ||≤||GN i -SP i When I, select non-overlapping flight acquisition mode, and +.>
2) When (when)In the case of->An overlapping hover acquisition mode is employed, and there are constraints: SP (service provider) i ＝FIP i ＝FOP i-1 Hover point OH i Fixed to GN i Directly above, i.e.)>If->Then further according to GN i -FIP i I and I GN i -SP i Judging the acquisition mode according to the magnitude of I;
when GN i -FIP i ||＞||GN i -SP i When I, selecting an overlapped flight acquisition mode; when GN i -FIP i ||≤||GN i -SP i And selecting a non-overlapping flight acquisition mode when the flight is in the same state.
Further, step S4 specifically includes: for node i, according to the acquisition mode selected by the node and the corresponding FIP in the acquisition mode i 、OH i Andthe task completion time minimization problem is established:
R i (t)＝Wlog 2 (1+γ i (t)) (14)
according to the constraint, the transmitting power of the node i and the acquisition track of the unmanned aerial vehicle are obtained through a sequence least square method.
Further, when the overlapping flight acquisition mode or the non-overlapping flight acquisition mode is selected, if the FIP is solved i →OH i →FOP i The track is a straight line, whether the data throughput obtained by the unmanned aerial vehicle is larger than the data quantity to be uploaded by the node i is judged, and if so, the node transmitting power is further optimized:
let GN i -OH i The I is the minimum transmission radius, and the transmission power corresponding to the radiusFor minimum transmission power, i.e.)>At this time, the node transmit power is at +.>A section, the section is replaced by the restriction condition of the node transmitting power of the formula (17), and the formula (17) is changed to +>And then adopting a binary search method to solve the problem of minimizing the task completion time again to obtain a new FIP i And FOP i Points to further optimize task completion time.
The invention has the beneficial effects that: according to the invention, under the limited energy limit of the ground node, the node transmitting power can be increased on the basis of ensuring that data can be transmitted, the data acquisition time of the unmanned aerial vehicle is reduced, and the task time of the unmanned aerial vehicle serving the whole area is shortened.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
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For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of a model of an unmanned aerial vehicle collecting data for ground limited energy nodes;
fig. 2 is a flight trajectory diagram corresponding to different transmitting powers when an unmanned aerial vehicle collects single node data;
FIG. 3 is a schematic diagram of an overlapping hover mode and a non-overlapping hover mode of the drone.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1 to 3, a method for acquiring data by jointly optimizing flight trajectory of an unmanned aerial vehicle and ground node transmitting power specifically includes:
a single unmanned aerial vehicle is arranged to collect data for N nodes on the ground, and the ground nodes i (i epsilon [1, N)]) With limited energyAnd the data quantity C to be uploaded i The nodes can transmit data when the signal-to-noise ratio between the unmanned aerial vehicle and the nodes exceeds a threshold value, and the unmanned aerial vehicle planning track acquires ground node data, so that the data acquisition task completion time is minimized.
And when the node acquisition sequence enabling the initial acquisition track of the unmanned aerial vehicle to be shortest is determined, the acquisition task is not considered in the initial track. Let unmanned aerial vehicle serve N nodes on ground, let omega i (i∈[1,N]) The labels are arranged for the nodes, and the acquisition sequence is S w ＝(s w1 ,s w2 ,…,s wN ) For example S w = (2, n, …,1, 3). Sequentially connecting the coordinates of each node to obtain an initial track, converting the initial track minimization problem of the unmanned aerial vehicle into the flight time minimization problem, and representing the initial track minimization problem as:
in the method, in the process of the invention,and the coordinates of the nodes i and i-1 are respectively represented, and v represents the flying speed of the unmanned aerial vehicle. The problems are converted into travel business problems and solved through genetic algorithm, and the node acquisition sequence S is obtained w 。
After determining the unmanned aerial vehicle acquisition node sequence, the unmanned aerial vehicle's trajectory may be discretized into the service trajectories of the N nodes. When the unmanned aerial vehicle collects data, the unmanned aerial vehicle passes through the circle center, the hovering point is located at the circle center of each circle, namely, the unmanned aerial vehicle flies over, and the hovering point is located right above each node, at this time, the distance between the unmanned aerial vehicle and the ground node is minimum, the collection rate is maximum, and the unmanned aerial vehicle can obtain the maximum collection throughput. Therefore, the problem of maximum throughput optimization of the unmanned aerial vehicle in the non-overlapping hovering acquisition mode of the node i is established, as follows:
s.t.R i (t)＝Wlog 2 (1+γ i (t))
in U i (t) represents the trajectory of the unmanned plane serving node i in time slot t, taken by the starting point SP i Entry point FIP i Hover point OH i And exit point FOP i Connection is formed;representing the center of a circle of a node i; />And->Respectively representing the transmitting power and the signal processing power of the node i; />Representing the total energy of the node i; p (P) min And P max Representing the minimum and maximum transmit powers of the nodes, respectively; r is R i (t) represents the transmission rate of the unmanned aerial vehicle in the time slot t, W represents the channel bandwidth, gamma i (t) represents the signal-to-noise ratio between the drone and the node,>represents the path loss, delta represents the path fading factor, < ->A signal-to-noise ratio threshold representing successful communication between the drone and the node; /> And->Respectively representing the flight time, the flight acquisition time and the hovering acquisition time of the service node i of the unmanned aerial vehicle.
As shown in fig. 2, the unmanned plane is in the transmission range D of node i i Internal signal to noise ratio gamma i Will exceed the signal-to-noise thresholdWhen the transmission range of the node increases, OH i Farther from the node, SP i →FIP i ，FOP i →EP i Is shortened and is filled with>For exiting the point, the distance of the unmanned aerial vehicle flying into the node transmission range is reduced, FIP i →OH i →FOP i The acquisition path of (1) is shortened and the flight time is similarly shortenedAcquisition time->And hover acquisition time->And also becomes less.
The optimization problem is solved through a sequence least square method, and the obtained maximum throughput is the maximum throughput of the unmanned aerial vehicle in the non-overlapping hovering acquisition modeSimilarly, when the unmanned aerial vehicle only flies and gathers, the unmanned aerial vehicle is not suspended above the nodeWhen stopping collection, let ∈ ->Obtaining the maximum throughput in the non-overlapping flight acquisition mode by solving the throughput maximization problem>
Comparing the data quantity C to be transmitted of the node i i Andif->The unmanned aerial vehicle is indicated to be unable to collect the data of the node under the energy limit of the node, and the unmanned aerial vehicle gives up the data collection of the node i and flies to the next node; otherwise, the unmanned aerial vehicle can collect data, and then the unmanned aerial vehicle is selected to collect the mode according to the following steps.
Based on the corresponding track at maximum throughput in non-overlapping hover acquisition mode, FOP of node i-1 is used i-1 (SP i ) As a reference entry point, in SP i -GN i Node transmitting power with I being transmission radius is used as transmitting powerCalculating the remaining energy of node i +.>
As shown in fig. 3, according to the remaining energyThe acquisition mode is selected as follows:
1) When (when)In the case of->The method has the advantages that the data quantity to be uploaded by the node i is large, the unmanned aerial vehicle can complete the acquisition task only by hovering for a period of time besides flight acquisition, and a non-overlapping hovering acquisition mode is adopted. In this mode, there are the following constraints: hover point OH i Fixed to GN i Directly above, i.e.)>
When (when)During the process, the data volume to be uploaded by the node i is smaller, and the unmanned aerial vehicle does not need to hover, namely +.>Further according to GN i -FIP i I and I GN i -SP i The magnitude of I judges whether the node tracks overlap: if GN i -FIP i ||＞||GN i -SP i Selecting an overlapping flight acquisition mode in which: SP (service provider) i ＝FIP i ＝FOP i-1 ，/>Otherwise, selecting a non-overlapping flight acquisition mode in which: />
2) When (when)In the case of->Illustrating the energy of a nodeThe rest is left, the emission power can be continuously increased, and an overlapped hovering acquisition mode is adopted; in this mode, there are the following constraints: SP (service provider) i ＝FIP i ＝FOP i-1 Hover point OH i Fixed to GN i Directly above, i.e.)>
If it isThe data quantity is smaller, hovering is not needed, and the method is based on GN i -FIP i I and I GN i -SP i The magnitude of i selects the acquisition mode: when GN i -FIP i ||＞||GN i -SP i Selecting an overlapping flight acquisition mode; otherwise, a non-overlapping flight acquisition mode is selected.
After the specific acquisition mode of the node i is selected, according to the selected mode and the corresponding FIP in the mode i 、OH i Andthe task completion time minimization problem is established:
R i (t)＝Wlog 2 (1+γ i (t))
and obtaining the transmitting power of the node i and the acquisition track of the unmanned aerial vehicle by a sequence least square method.
Furthermore, when node i selects either the overlapping or non-overlapping flight acquisition mode, the FIP is solved i →OH i →FOP i When the track is in a straight line, judging whether the data throughput obtained by the unmanned aerial vehicle is larger than the data quantity to be uploaded by the node i, if so, indicating that the current transmitting power is overlarge, wasting redundant energy and further optimizing the transmitting power of the node. At this time, let GN i -OH i The I is the minimum transmission radius and the corresponding transmitting powerFor minimum transmission power, i.e.)>At this time, the node transmit power is at +.>The interval is used for replacing the node transmitting power limiting condition, and then a binary search method is used for solving the problem of minimizing the task completion time again to obtain a new FIP i And FOP i And (3) further optimizing the task completion time.
When the service of each node of the unmanned plane is found (FIP i ,OH i ,FOP i ) After the position, the flight path with the minimum completion time of the unmanned aerial vehicle is obtained as follows: FOP (FOP) 0 →FIP 1 →OH 1 →FOP 1 →FIP 2 →…→FOP N →FOP 0 Wherein FOP 0 Is the starting point of the unmanned aerial vehicle.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.

Claims (2)

1. A data acquisition method for jointly optimizing the flight trajectory of an unmanned aerial vehicle and the emission power of a ground node is characterized by comprising the following steps of: the method comprises the following steps:
s1, determining a node acquisition sequence S which enables an initial acquisition track of the unmanned aerial vehicle to be shortest according to ground node coordinates w ；
S2, establishing an unmanned aerial vehicle acquisition throughput maximization problem under two modes of flight acquisition and flight hover acquisition, and solving to obtain a maximum throughput threshold under the two modes, wherein the method comprises the following steps:
when the unmanned aerial vehicle collects data, the unmanned aerial vehicle passes through the circle centers and the hovering points are positioned at the circle centers of the circles, namely, the unmanned aerial vehicle flies through and the hovering points are positioned right above the nodes, at the moment, the distance between the unmanned aerial vehicle and the ground nodes is minimum, the collection rate is maximum, and the unmanned aerial vehicle can obtain the maximum collection throughput; therefore, the problem of maximum throughput optimization of the unmanned aerial vehicle in the non-overlapping hovering acquisition mode of the node i is established, as follows:
s.t.R i (t)＝Wlog 2 (1+γ i (t))
in U i (t) represents the trajectory of the unmanned plane serving node i in time slot t, taken by the starting point SP i Entry point FIP i Hover point OH i And exit point FOP i Connection is formed;representing the center of a circle of a node i; />And->Respectively representing the transmitting power and the signal processing power of the node i; />Representing the total energy of the node i; p (P) min And P max Representing the minimum and maximum transmit powers of the nodes, respectively; r is R i (t) represents the transmission rate of the unmanned aerial vehicle in the time slot t, W represents the channel bandwidth, gamma i (t) represents the signal to noise ratio between the drone and the node,represents the path loss, delta represents the path fading factor, < ->A signal-to-noise ratio threshold representing successful communication between the drone and the node; and->Respectively representing the flight time, the flight acquisition time and the hovering acquisition time of the unmanned aerial vehicle service node i; v represents the unmanned aerial vehicle speed;
solving the optimization problem by adopting a sequence least square method to obtain the maximum throughput, namely the maximum throughput of the unmanned aerial vehicle in a non-overlapping hovering acquisition mode
Similarly, when the unmanned aerial vehicle does not hover and collect above the node, the unmanned aerial vehicle is led toObtaining the maximum throughput in the non-overlapping flight acquisition mode by solving the throughput maximization problem>
S3, according toJudging the acquisition sequence S of the nodes according to the data quantity to be uploaded and the obtained throughput threshold value of each node w Whether each node can completely transmit data under the energy limit of the node; if not, the unmanned plane gives up the data acquisition of the node and goes to the next node; if yes, judging an acquisition mode of the unmanned aerial vehicle;
wherein, according to the residual energy of the node iSelecting an acquisition mode of the unmanned aerial vehicle:
1) When (when)In the case of->A non-overlapping hover acquisition mode is employed, and there are constraints: hover point OH i Fixed to GN i Directly above, i.e.)>If->Then further according to GN i -FIP i I and I GN i -SP i Judging the acquisition mode according to the magnitude of I; wherein C is i Indicating the amount of data to be transmitted for node i, GN i Representing coordinates of node i;
when GN i -FIP i ||＞||GN i -SP i When I, select overlapping flight acquisition mode, and SP i ＝FIP i ＝FOP i-1 ，When GN i -FIP i ||≤||GN i -SP i When I, select non-overlapping flight acquisition mode, and +.>
2) When (when)In the case of->An overlapping hover acquisition mode is employed, and there are constraints: SP (service provider) i ＝FIP i ＝FOP i-1 Hover point OH i Fixed to GN i Directly above, i.e.)>If->Then further according to GN i -FIP i I and I GN i -SP i Judging the acquisition mode according to the magnitude of I;
when GN i -FIP i ||＞||GN i -SP i When I, selecting an overlapped flight acquisition mode; when GN i -FIP i ||≤||GN i -SP i Selecting a non-overlapping flight acquisition mode when the number is I;
s4, according to the selected acquisition mode, jointly optimizing the transmitting power of the node and the track of the unmanned aerial vehicle, and minimizing the task completion time of the unmanned aerial vehicle;
for node i, according to the acquisition mode selected by the node and the corresponding FIP in the acquisition mode i 、OH i Andthe task completion time minimization problem is established:
R i (t)＝Wlog 2 (1+γ i (t))
according to the constraint, acquiring the transmitting power of the node i and the acquisition track of the unmanned aerial vehicle by a sequence least square method;
if the FIP is solved when the overlapping flight acquisition mode or the non-overlapping flight acquisition mode is selected i →OH i →FOP i The track is a straight line, whether the data throughput obtained by the unmanned aerial vehicle is larger than the data quantity to be uploaded by the node i is judged, and if so, the node transmitting power is further optimized:
let GN i -OH i The I is the minimum transmission radius, and the transmission power corresponding to the radiusFor minimum transmission power, i.eAt this time, the node transmit power is at +.>Interval, replacing the constraint condition of node transmitting power in constraint condition of the interval, and adopting a binary search method to solve the task completion time minimization problem again to obtain a new FIP i And FOP i A point to further optimize task completion time;
s5, according to the node acquisition sequence S w And the acquisition tracks of all the nodes are sequentially connected, so that the unmanned aerial vehicle flight track with the minimum acquisition time is obtained, and the unmanned aerial vehicle completes data acquisition according to the flight track flight.
2. The data acquisition method of claim 1, wherein: the step S1 specifically comprises the following steps: when determining the node acquisition sequence which enables the initial acquisition track of the unmanned aerial vehicle to be shortest, not considering the data acquisition task;
the number of the ground nodes is recorded as N, and the node acquisition sequence S w ＝(s w1 ,s w2 ,…,s wN ) Sequentially connecting the node coordinates corresponding to the acquisition sequence to obtain an initial acquisition track, wherein the total flight time T corresponding to the initial acquisition track is as follows:
in the method, in the process of the invention,the node coordinates arranged according to the acquisition sequence are represented, and v represents the speed of the unmanned aerial vehicle; converting the initial trajectory minimization problem of the unmanned aerial vehicle into a time-of-flight minimization problem:
converting the flight time minimization problem into a travel business problem and solving the travel business problem through a genetic algorithm to obtain the node acquisition orderSequence S w 。
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113179116A (en) * 2021-04-20 2021-07-27 南通大学 Joint optimization method for transmission power and flight trajectory of unmanned aerial vehicle relay system
CN113518361A (en) * 2021-06-18 2021-10-19 中南林业科技大学 Trajectory optimization method, device and medium for unmanned aerial vehicle-assisted wireless communication
US11164464B1 (en) * 2018-10-08 2021-11-02 Facebook, Inc. Optimizing trajectory of unmanned aerial vehicles
CN113885566A (en) * 2021-10-21 2022-01-04 重庆邮电大学 V-shaped track planning method for minimizing data acquisition time of multiple unmanned aerial vehicles
CN114884829A (en) * 2022-05-05 2022-08-09 福州大学 Unmanned aerial vehicle assisted WPCN resource allocation method based on MCR-WPT

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20220415187A1 (en) * 2019-12-04 2022-12-29 Ge Aviation Systems Llc Apparatus, system, and method of providing a trajectory planning engine for unmanned aircraft

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11164464B1 (en) * 2018-10-08 2021-11-02 Facebook, Inc. Optimizing trajectory of unmanned aerial vehicles
CN113179116A (en) * 2021-04-20 2021-07-27 南通大学 Joint optimization method for transmission power and flight trajectory of unmanned aerial vehicle relay system
CN113518361A (en) * 2021-06-18 2021-10-19 中南林业科技大学 Trajectory optimization method, device and medium for unmanned aerial vehicle-assisted wireless communication
CN113885566A (en) * 2021-10-21 2022-01-04 重庆邮电大学 V-shaped track planning method for minimizing data acquisition time of multiple unmanned aerial vehicles
CN114884829A (en) * 2022-05-05 2022-08-09 福州大学 Unmanned aerial vehicle assisted WPCN resource allocation method based on MCR-WPT

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
无人机全双工双向中继的资源及轨迹优化设计;周理辉 等;《北京邮电大学学报》;第46卷(第1期);第77-83页 *

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