CN117674938A - Unmanned aerial vehicle direction modulation design method based on single carrier - Google Patents
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Abstract
The invention discloses a single carrier-based unmanned aerial vehicle direction modulation design method, which comprises the following steps: establishing a communication system model between a single-carrier unmanned aerial vehicle and a ground user, wherein the unmanned aerial vehicle is provided with a single-carrier analog beam forming uniform linear array to transmit signals to the ground target single user; the expected beam response meets the single-user direction of the ground target, the beam amplitude is higher than signals in other directions, the phases of the signals in other directions are disordered, and the single-carrier unmanned aerial vehicle direction modulation design standard is met; converting the weight coefficient in the problem of minimizing the difference between the actual beam response and the expected beam response into a form conforming to the constant modulus constraint, and eliminating the constant modulus constraint; converting the magnitude in the problem of minimizing the difference between the actual beam response and the desired beam response to a mathematical expression of the minimum user-implemented transmission rate, eliminating the minimum user-implemented transmission rate constraint; an artificial bee colony algorithm is adopted to solve the problem of minimizing the difference between the actual beam response and the expected beam response, and the expected beam response is obtained.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle direction modulation, and particularly relates to an unmanned aerial vehicle direction modulation design method based on single carrier waves.
Background
In recent years, unmanned aerial vehicles are widely applied in the fields of military, agriculture, weather, water conservancy and the like due to the characteristics of strong maneuverability, high safety, low cost and the like. In the background of the 5G age, with the proliferation of the number of wireless network access devices, the potential of the unmanned aerial vehicle in the wireless communication field is fully exploited. Compared with the traditional wireless communication, the unmanned aerial vehicle wireless communication can be rapidly deployed in areas without infrastructure coverage as an air infrastructure by virtue of the maneuverability and controllability of the unmanned aerial vehicle wireless communication, so that the defect of ground infrastructure is overcome, and higher wireless connectivity is provided. Currently, a beam forming technology is mostly adopted to realize a high-capacity line-of-sight communication link with a ground terminal, and the transmission direction and range of radio waves can be controlled by adjusting the radiation direction and the intensity of an antenna, so that the transmission of the radio waves in a specific direction is more powerful and stable, and the quality and the reliability of communication are improved. Beamforming for millimeter wave communications may meet the requirements of the unmanned aerial vehicle base station for high data rates and flexible coverage. The prior art can significantly improve the expected data throughput of the unmanned aerial vehicle over the life expectancy of the unmanned aerial vehicle battery. In the prior art, a problem of maximizing the achievable transmission rate of all users is proposed, and an optimal relative position and a beam forming vector between the unmanned aerial vehicle base station and the target user are found. However, in the conventional beamforming-based wireless communication system, the same constellation mapping is generated in all directions, and even a signal located in an antenna sidelobe region may be captured by a highly sensitive eavesdropper, thereby causing information leakage. To avoid this, directional modulation techniques have evolved that maintain a known constellation in one or more desired directions while scrambling the constellation in the remaining directions, thereby improving the security of the communication. In the prior art, a genetic algorithm is also adopted to realize the directional modulation of the phased array. The existing unmanned aerial vehicle communication system design problem based on beam forming is mostly regarded as a problem of maximizing the achievable transmission rate of users, and the influence caused by the information safety of unexpected directions is ignored although the transmission rate of information is optimized to a certain extent. Based on the consideration of cost and unmanned aerial vehicle duration, the unmanned aerial vehicle transmitting end antenna array adopts an analog beam forming array. In an analog beamforming array, all antennas share a radio frequency chain and have a phase shifter with a power amplifier, while all power amplifiers are set to have the same scale factor, so the beamforming vector w needs to satisfy the constant modulus constraint. Furthermore, since the dimension of the beamforming vector w is high and each element of w has a constant modulus constraint, this results in a problem of non-convexity. Therefore, the high-dimensionality problem is usually solved by adopting a genetic algorithm to carry out calculation, so that the unmanned aerial vehicle direction modulation design is realized, but the traditional genetic algorithm also faces the problems of poor local searching capability, low convergence speed and the like.
Disclosure of Invention
In order to solve the technical problems, the invention provides a single carrier-based unmanned aerial vehicle direction modulation design method, which reduces the probability of unexpected direction information leakage by optimizing the weight coefficient of an unmanned aerial vehicle antenna array.
In order to achieve the above object, the present invention provides a method for designing unmanned aerial vehicle directional modulation based on single carrier, comprising:
establishing a communication system model between a single-carrier unmanned aerial vehicle and a ground user, wherein the unmanned aerial vehicle is provided with a single-carrier analog beam forming uniform linear array to transmit QPSK signals to the ground target single user;
the method comprises the steps of providing a problem of difference between an actual beam response and an expected beam response, wherein the difference is caused by constant mode constraint and a transmission rate constraint realized by a minimum user; the expected beam response meets the single-user direction of the ground target, the beam amplitude is higher than signals in other directions, the phases of the signals in other directions are disordered, and the single-carrier unmanned aerial vehicle direction modulation design standard is met;
converting the weight coefficient in the problem of minimizing the difference between the actual beam response and the expected beam response into a form conforming to the constant modulus constraint, and eliminating the constant modulus constraint; converting the magnitude in the problem of minimizing the difference between the actual beam response and the desired beam response to a mathematical expression of the minimum user achievable transmission rate, eliminating the minimum user achievable transmission rate constraint;
after the constant modulus constraint and the transmission rate constraint of the minimum user are eliminated, the problem of minimizing the difference between the actual beam response and the expected beam response is solved by adopting an artificial bee colony algorithm, the expected beam response is obtained, and the single-carrier unmanned aerial vehicle direction modulation design is realized.
Optionally, according to the unmanned aerial vehicle and ground user communication system model based on direction modulation, the steering vector of the array is expressed as:
wherein [ (S)] T To transpose operation, phi U Is the cosine of the steering angle, j is the imaginary number N Is the number of array antennas.
Optionally, the optimizing bosh problem of eliminating the constant modulus constraint includes:
s.t.R≥r
wherein,is->K is the phase number modulated by the phase shift keying modulation technique, a is the guiding vector, H is the conjugate transpose, N is the array antenna number, a H To perform conjugate transposition on the steering vector, j is imaginary +> Phase shift angle for weight coefficient, +.>For the phase shift caused by the weight coefficient, l is the amplitude of the expected response, C k For the desired vector->The k-th element of (a).
Optionally, in the unmanned plane direction modulation design problem, the achievable transmission rate R is a non-negligible important factor for the target user, expressed as
Wherein P is the transmitting power delta of the unmanned aerial vehicle 2 Is Gaussian white noise power of a user, lambda is channel gain coefficient, a H To perform conjugate transposition on the steering vector, w is a weight coefficient.
Optionally, a matrix Φ is first initialized as an initial search location, where each row represents a potential feasible solutionThe number of columns is the dimension of the optimization variable, namely the number of array elements of the unmanned aerial vehicle transmitting end antenna array.
Optionally, initializing the ith row and jth element of matrix phi to
Wherein i=1, 2, …, N S ,N S Is the number of sources, phi i,j ∈[0,1]Is a random number, and the code is a random number,is a potential feasible solution->Upper limit of (2 pi,) of +.>Is a potential feasible solution->And has a value equal to 0.
Optionally, the fitness function value F of the ith source i Is that
Wherein,for the i-th objective function value,/->For the ith row of the source matrix Φ, i.e., the ith potential feasible solution, abs () is the calculated absolute value.
Alternatively, each of the source matrices Φ is based on a random number γRandom sequential generation of new->The calculation of the ith source is
Wherein,is the ith row of the source matrix Φ, +.>For the a-th row of the source matrix phi, i is the sequential number of the selected source, gamma is a random number, and the value of the random number is within a set precision range (- Γ, Γ).
The invention has the technical effects that: the invention discloses a single carrier-based unmanned aerial vehicle direction modulation design method, which reduces the probability of unexpected direction information leakage by optimizing the weight coefficient of an unmanned aerial vehicle antenna array; the method has universality under the condition that users possibly appear at different angles, has faster convergence speed of the objective function compared with the traditional genetic algorithm, and has higher efficiency in solving the problems.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:
fig. 1 is a schematic diagram of a communication system between a unmanned aerial vehicle and a ground user based on direction modulation according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an array antenna according to an embodiment of the present invention;
fig. 3 is a schematic diagram of amplitude response and phase response of a single carrier based unmanned aerial vehicle direction modulation design with a desired direction of 60 ° according to an embodiment of the present invention;
fig. 4 is a schematic diagram of amplitude response and phase response of a single carrier based unmanned aerial vehicle direction modulation design with an expected direction of 90 ° according to an embodiment of the present invention;
FIG. 5 is a graph comparing the convergence curves of the genetic algorithm and the artificial bee colony algorithm according to the embodiment of the invention;
fig. 6 is a flow chart of a single carrier-based unmanned aerial vehicle direction modulation design method according to an embodiment of the invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
The invention considers a millimeter wave downlink single-user scenario in which an unmanned aerial vehicle base station equipped with an N-element uniform linear array (Antenna) serves a ground single-Antenna user, wherein the N-element uniform linear array model is shown in fig. 2. As shown in FIG. 1, a two-dimensional rectangular coordinate system is established in which individual users (User) are distributed on a horizontal plane with coordinates (x, 0), and unmanned aerial vehicle base stations (UAV-BS) are located at (0, h U ) Wherein h is U Is the height of the drone, x is the distance between the user and the projection of the drone on the ground.
As shown in fig. 6, in this embodiment, a method for designing unmanned aerial vehicle directional modulation based on single carrier is provided, including:
establishing a communication system model between a single-carrier unmanned aerial vehicle and a ground user, wherein the unmanned aerial vehicle is provided with a single-carrier analog beam forming uniform linear array to transmit QPSK signals to the ground target single user;
the method comprises the steps of providing a problem of difference between an actual beam response and an expected beam response, wherein the difference is caused by constant mode constraint and a transmission rate constraint realized by a minimum user; the expected beam response meets the signal phase confusion that the single-user direction beam amplitude of the ground target is higher than that of other directions, and meets the single-carrier unmanned aerial vehicle direction modulation design standard;
converting the weight coefficient in the problem of minimizing the difference between the actual beam response and the expected beam response into a form conforming to the constant modulus constraint, and eliminating the constant modulus constraint; converting the magnitude in the problem of minimizing the difference between the actual beam response and the desired beam response to a mathematical expression of the minimum user achievable transmission rate, eliminating the minimum user achievable transmission rate constraint;
after the constant modulus constraint and the transmission rate constraint of the minimum user are eliminated, the problem of minimizing the difference between the actual beam response and the expected beam response is solved by adopting an artificial bee colony algorithm, the expected beam response is obtained, and the single-carrier unmanned aerial vehicle direction modulation design is realized.
The invention considers millimeter wave downlink single-user scene, wherein an unmanned aerial vehicle base station provided with an N-element uniform linear array serves a ground single-antenna user, and utilizes the uniform linear array to realize multiphase phase shift keying direction modulation under K-system signals in an expected direction, and meanwhile, constellation diagrams of signals are received in other directions to be confused. In order to obtain the position and geometric relationship of the unmanned aerial vehicle/user, a two-dimensional rectangular coordinate system is firstly established, wherein single users are distributed on a horizontal plane, the coordinates are (x, 0), and the unmanned aerial vehicle base station is positioned at (0, h U ) Wherein h is U Is the height of the drone, x is the distance between the user and the projection of the drone on the ground.
The uniform linear array model provided with the drone base station employs an analog beamforming array in which all antennas share a radio frequency chain, each antenna employs an isotropic antenna, and has a phase shifter with a power amplifier. In order to avoid grating lobes and make full use of space, the antenna array is placed at half wavelength intervals. Since all power amplifiers have the same scale factor, the constant modulus constraint needs to be satisfied:n=1, …, N, where w n Is the weight coefficient of antenna n.
The method comprises the following specific steps:
step 1: according to the unmanned aerial vehicle and ground user communication system model based on direction modulation, the steering vector of the array can be expressed as
Wherein, [.] T To transpose operation, phi U Is within the range of [ -1,1]Expressed as
The drone direction modulation problem can thus be expressed initially as a problem of minimizing the difference between the actual and desired beam responses, i.e
R≥r
Wherein a is H w is the actual beam response, [] H Transposed by hermite, w= [ w ] 1 ,w 2 ,…,w N ] T A beamforming vector containing the weight coefficients for each antenna in the array. lC (l-C) k For the desired beam response, where l is the amplitude of the desired response, C k For the kth expected constellation point, R is the achievable transmission rate between the drone and the user, and R is the minimum transmission rate constraint of the user. To solve the problem of constant modulus constraint, the constraint is thatTransformation is performed, wherein w is expressed asThe optimization problem becomes
s.t.R≥r
Wherein,is->J=1, 2, …, N.
Step 2: in unmanned aerial vehicle direction modulation design, the achievable transmission rate R is a non-negligible important factor for the target user, expressed as
Wherein P is the transmitting power delta of the unmanned aerial vehicle 2 Is the gaussian white noise power of the user, and λ is the channel gain coefficient.
Wherein the method comprises the steps ofd is the propagation distance between the unmanned aerial vehicle base station and the user, expressed as +.>f is the carrier frequency of the transmitted signal, c is the speed of light, and α is the path loss index. In the optimization problem, it can be seen that in an ideal situation, i.e. +.>When the constraint R is more than or equal to R, the constraint R is further calculated
Obviously can be derived from this
Order theAnd referring to (7) to replace the amplitude l in the original objective function, the optimization problem is changed into
Step 3: compared with the traditional genetic algorithm, the artificial bee colony algorithm has great advantages in convergence speed and has strong capability of searching a local optimal solution and searching a global optimal solution. Therefore, the artificial bee colony algorithm is more suitable for solving the optimization problem with high-dimensional variables in the step (8). From this step on, a solution to problem (8) is performed using an artificial bee colony algorithm. First, a matrix Φ (i.e., source matrix) is initialized as an initial search location, wherein each row represents a potential feasible solution(i.e., one source), the number of columns is the dimension of the optimization variable, i.e., the number of array elements of the unmanned aerial vehicle transmitting end antenna array. Initializing the jth element of the ith row of matrix phi to
Where i=1, 2, …, N S ，j＝1,2,…,N，φ i,j ∈[0,1]Is a random number, N S Is the number of sources. The fitness function value F of the ith source (i.e. the solution vector of the ith row) i Is that
Wherein the method comprises the steps ofFor the ith objective function value, the ith row of the source matrix Φ, the potential feasible solution +.>Substituting formula (8) can obtain the objective function value +.>As can be seen from the formula +.>The smaller the value of (c), the larger the fitness function value representing the quality of the solution.
Step 4: from each within the source matrix Φ by a random number γRandom sequential generation of new->Wherein the random number gamma is within a set precision range (- Γ, Γ), the calculation formula of the ith source is
Wherein the method comprises the steps ofRow i, +.>Represents the a-th row of the source matrix phi, which is taken from any row in phi except the i-th row, wherein a=1, 2, …, N s And a+.i. If new source->The fitness value of (2) is greater than the source of the last iteration +.>Is the fitness value of new source->The source of the last iteration will be replaced +.>Otherwise keep +.>By doing so, a better source is obtained.
Step 5: and (4) repeatedly executing the step (4) until the maximum iteration number is reached, and ending the algorithm. And then, calculating the fitness value of each source, and finding the optimal solution vector from the matrix according to the fitness function value.
Step 6: because the unmanned aerial vehicle direction modulation problem that this patent solved, its expected response involves K constellation points of multiphase phase shift keying, therefore all need repeat step 3, step 4 and step 5 for the solution of every transmission signal, finally satisfy the sum minimization of the design response of K constellation points and the difference of expected response.
To demonstrate that this approach is universally applicable in situations where the user may be present at a number of different angles, the present invention gives an amplitude response plot and a phase response plot of the artificial bee colony algorithm in the direct direction, i.e. the 90 ° direction, and in the non-direct direction at 60 °, and employs Quadrature Phase Shift Keying (QPSK), i.e. a system model of k=4, with four symbols in the target direction having phase angles equal to 45 °,135 °, 45 ° and 135 °.
In the simulation comparison, the antenna number N=24 and the unmanned aerial vehicle height h are set U =200m, unmanned plane transmit power p=40dbm, gaussian white noise δ 2 = -100dbm, carrier frequency f=28 GHz, path loss index α=0.95, minimum transmission rate constraint is r b =4bps/Hz. As shown in fig. 3 and 4, these two sets of images illustrate two results of the artificial bee colony algorithm calculated in the direct and indirect directions. The beam patterns obtained by the artificial bee colony algorithm can be obviously seen through the two groups of images, the main lobe of the beam patterns points to the expected direction, and meanwhile, the side lobe amplitude is lower. In the contrast of the phase diagrams, the target direction phases of the phase diagrams meet the expected constellation points, and the rest direction phases are disordered, so that the method realizes direction modulation.
In order to embody the performance difference of the two algorithms under the constraint of the minimum transmission rate facing to the higher, the comparison is carried out by adopting the comparison graph of the convergence curves of the two algorithms, wherein r is g ＝r b =4bps/Hz. Since the Genetic Algorithm (GA) and the artificial swarm Algorithm (ABC) differ in the desired fitness function values, the fitness function values are normalized in order to facilitate comparison of iterative convergence rates. As can be seen from the comparison of the fitness function value convergence curves of FIG. 5, the convergence speed of the artificial bee colony algorithm is significantly faster than that of the genetic algorithm. In fig. 5, it is also obvious that after up to 2000 iterations, the genetic algorithm still does not find the optimal solution with the fitness value of 0, which is caused by the slow convergence rate of the genetic algorithm, when the expected amplitude l in the objective function (3) is increased, i.e. the minimum transmission rate constraint r is increased, under the condition that the number of array antennas is unchanged, the requirement of local searching capability needed in solving the problem (3) is increased, and the artificial bee colony algorithm has better local searching capability than the genetic algorithm, so thatBetter efficiency is often achieved when computing such problems with high demands on local search capabilities.
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. The unmanned aerial vehicle direction modulation design method based on single carrier is characterized by comprising the following steps of:
establishing a communication system model between a single-carrier unmanned aerial vehicle and a ground user, wherein the unmanned aerial vehicle is provided with a single-carrier analog beam forming uniform linear array to transmit QPSK signals to the ground target single user;
the method comprises the steps of providing a problem of difference between an actual beam response and an expected beam response, wherein the difference is caused by constant mode constraint and a transmission rate constraint realized by a minimum user; the expected beam response meets the single-user direction of the ground target, the beam amplitude is higher than signals in other directions, the phases of the signals in other directions are disordered, and the single-carrier unmanned aerial vehicle direction modulation design standard is met;
converting the weight coefficient in the problem of minimizing the difference between the actual beam response and the expected beam response into a form conforming to the constant modulus constraint, and eliminating the constant modulus constraint; converting the magnitude in the problem of minimizing the difference between the actual beam response and the desired beam response to a mathematical expression of the minimum user achievable transmission rate, eliminating the minimum user achievable transmission rate constraint;
after the constant modulus constraint and the transmission rate constraint of the minimum user are eliminated, the problem of minimizing the difference between the actual beam response and the expected beam response is solved by adopting an artificial bee colony algorithm, the expected beam response is obtained, and the single-carrier unmanned aerial vehicle direction modulation design is realized.
2. The single carrier based unmanned aerial vehicle directional modulation design method of claim 1, wherein the steering vector of the array is expressed as:
wherein [ (S)] T To transpose operation, phi U Is the cosine of the steering angle, j is the imaginary numberN is the number of array antennas.
3. The single carrier based unmanned aerial vehicle directional modulation design method of claim 1, wherein optimizing the constant modulus constraint problem comprises:
s.t.R≥r
wherein,is->K is the phase number modulated by the phase shift keying modulation technique, a is the guiding vector, H is the conjugate transpose, N is the array antenna number, a H To perform conjugate transposition on the steering vector, j is imaginary +> Phase shift angle for weight coefficient, +.>For the phase shift caused by the weight coefficient, l is the amplitude of the expected response, C k Is the expected vectorThe k-th element of (a).
4. The method of designing single carrier based unmanned aerial vehicle directional modulation according to claim 1, wherein in unmanned aerial vehicle directional modulation design, the achievable transmission rate R is a non-negligible important factor for the target user, expressed as
Wherein P is the transmitting power delta of the unmanned aerial vehicle 2 Is Gaussian white noise power of a user, lambda is channel gain coefficient, a H To perform conjugate transposition on the steering vector, w is a weight coefficient.
5. The single carrier based unmanned aerial vehicle directional modulation design method of claim 1, wherein a matrix Φ is first initialized as an initial search location, wherein each row represents a potential feasible solutionThe number of columns is the dimension of the optimization variable, namely the number of array elements of the unmanned aerial vehicle transmitting end antenna array.
6. The method for designing single carrier based unmanned aerial vehicle directional modulation according to claim 5, wherein the j-th element of the i-th row of the matrix Φ is initialized to
Wherein i=1, 2, …, N S ,N S Is the number of sources, phi i,j ∈[0,1]Is a random number, and the code is a random number,is a potential feasible solution->Upper limit of (2 pi,) of +.>Is a potential feasible solution->And has a value equal to 0.
7. The method for designing directional modulation of a single carrier-based unmanned aerial vehicle according to claim 6, wherein the fitness function value F of the i-th source i Is that
Wherein,for the i-th objective function value,/->For the ith row of the source matrix Φ, i.e., the ith potential feasible solution, abs () is the calculated absolute value.
8. The single carrier based unmanned aerial vehicle directional modulation design method of claim 5, wherein each within the source matrix Φ is referenced by a random number γRandom sequential generation of new->The calculation of the ith source is
Wherein,is the ith row of the source matrix Φ, +.>For the a-th row of the source matrix phi, i is the sequential number of the selected source, gamma is a random number, and the value of the random number is within a set precision range (- Γ, Γ).
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180115065A1 (en) * | 2016-10-26 | 2018-04-26 | International Business Machines Corporation | In-field millimeter-wave phased array radiation pattern estimation and validation |
| CN110492911A (en) * | 2019-07-10 | 2019-11-22 | 鹰潭泰尔物联网研究中心 | A kind of beam tracking method and system for UAV Communication |
| CN112346030A (en) * | 2020-10-30 | 2021-02-09 | 西安电子科技大学 | Super-resolution direction-of-arrival estimation method for unmanned aerial vehicle cluster |
| CN112636804A (en) * | 2020-11-12 | 2021-04-09 | 北京航空航天大学 | Multi-unmanned aerial vehicle base station cooperative transmission method based on millimeter wave array |
| CN115765899A (en) * | 2022-08-25 | 2023-03-07 | 网络通信与安全紫金山实验室 | Unmanned aerial vehicle communication beam domain channel simulation method and device, electronic equipment and medium |
| WO2023123503A1 (en) * | 2021-12-31 | 2023-07-06 | 深圳市大疆创新科技有限公司 | Polarization direction control method, remote control device and storage medium |
-
2023
- 2023-12-07 CN CN202311671343.6A patent/CN117674938A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180115065A1 (en) * | 2016-10-26 | 2018-04-26 | International Business Machines Corporation | In-field millimeter-wave phased array radiation pattern estimation and validation |
| CN110492911A (en) * | 2019-07-10 | 2019-11-22 | 鹰潭泰尔物联网研究中心 | A kind of beam tracking method and system for UAV Communication |
| CN112346030A (en) * | 2020-10-30 | 2021-02-09 | 西安电子科技大学 | Super-resolution direction-of-arrival estimation method for unmanned aerial vehicle cluster |
| CN112636804A (en) * | 2020-11-12 | 2021-04-09 | 北京航空航天大学 | Multi-unmanned aerial vehicle base station cooperative transmission method based on millimeter wave array |
| WO2023123503A1 (en) * | 2021-12-31 | 2023-07-06 | 深圳市大疆创新科技有限公司 | Polarization direction control method, remote control device and storage medium |
| CN115765899A (en) * | 2022-08-25 | 2023-03-07 | 网络通信与安全紫金山实验室 | Unmanned aerial vehicle communication beam domain channel simulation method and device, electronic equipment and medium |
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