WO2021175343A2 - 一种基于无人机的室外天线四维方向图测量方法及装置 - Google Patents
一种基于无人机的室外天线四维方向图测量方法及装置 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
- G01R29/08—Measuring electromagnetic field characteristics
- G01R29/10—Radiation diagrams of antennas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
- G05D1/0022—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement characterised by the communication link
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0094—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
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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]
- G08G5/003—Flight plan management
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2201/00—UAVs characterised by their flight controls
- B64U2201/10—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
- B64U2201/104—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS] using satellite radio beacon positioning systems, e.g. GPS
Definitions
- the invention relates to the technical field of antennas, in particular to a method for measuring a four-dimensional pattern of an outdoor antenna based on an unmanned aerial vehicle and a device for measuring the four-dimensional pattern of an outdoor antenna based on an unmanned aerial vehicle.
- Antennas are an important part of application equipment in the fields of broadcasting, television, communications, radar, navigation, electronic countermeasures, remote sensing, and radio astronomy.
- the antenna pattern directly reflects the ability of the antenna to radiate signals, and whether the measurement result of the antenna radiation characteristic is accurate not only involves the verification of antenna performance indicators, but also relates to the overall system performance. Therefore, the accurate measurement of the antenna pattern is an extremely important part of the performance measurement of hardware equipment.
- the radiation field around the antenna is divided into a near-field area and a far-field area.
- the antenna pattern is also divided into two methods: near-field measurement and far-field measurement.
- the near-field measurement and the far-field measurement of a small-aperture antenna are usually carried out indoors using a microwave anechoic chamber.
- a microwave anechoic chamber is a special room formed by a metal shield.
- outdoor antenna far-field measurement is divided into elevated antenna test field, oblique antenna test field and UAV-based test method.
- elevated antenna test field For antennas with larger apertures (such as short-wave antennas), the space required for far-field measurement is relatively large, and it is difficult to achieve the limited space of microwave anechoic chambers.
- outdoor antenna far-field measurement is divided into elevated antenna test field, oblique antenna test field and UAV-based test method.
- the use of the elevated antenna test field and the oblique antenna test field for outdoor testing requires tall buildings or insulating towers.
- the construction cost is relatively high, and the antenna to be tested needs to be installed on it, but for large and medium-diameter antennas , Installation is quite time-consuming and laborious.
- the measurement error cannot be estimated at all.
- the conventional outdoor test field is also helpless for the far-field measurement of large and medium-sized antennas.
- the installation, debugging, and use environment of the antenna have a greater impact on the radiation pattern of the antenna under actual working conditions, resulting in inconsistencies between the measurement results at the test site and the actual working results, and the performance evaluation that affects the entire system is performed.
- the UAV test method it is not necessary to move the antenna position, and the outdoor antenna pattern can be directly tested.
- the existing method is only for the three-dimensional pattern measurement, and the test efficiency is low, and the method of eliminating system errors is not fully considered.
- the purpose of the present invention is to provide a four-dimensional pattern measurement method and device for outdoor antennas based on unmanned aerial vehicles, to solve the problems of low efficiency and poor accuracy in the existing outdoor antenna pattern measurement, and to complete the four-dimensional pattern including space and frequency factors.
- the pattern test also uses interference background cancellation technology to effectively improve the test accuracy.
- an embodiment of the present invention provides a method for measuring a four-dimensional pattern of an outdoor antenna based on a drone, and the measuring method includes:
- the flight of the drone is performed according to the optimal measurement flight trajectory, and the collection of multiple sets of data and the multiple sets of data are completed by the drone Sending to the ground data processing unit, wherein during the flight of the drone, the directional antenna of the drone points to the antenna phase center, and one set of data in the multiple sets of data includes one flight of the drone
- the ground data processing unit converts the GPS position data into a sampling position in a spherical coordinate system relative to the antenna phase center, and processes the signal data to obtain the original data of the antenna under test and the reference antenna Reference data, wherein the original data and the reference data respectively include the received signal strength corresponding to the frequency point at each sampling position;
- the original data and the reference data are corrected by the ground data processing unit, and the corrected original data is calibrated by the corrected reference data to obtain discrete pattern data;
- Interpolation is performed on the discrete pattern data by the ground data processing unit to obtain the spatial frequency four-dimensional pattern data of the antenna to be tested.
- the calculation of the optimal measurement flight trajectory of the UAV based on the user input information of the antenna to be tested includes:
- the measured path planning unit calculates the optimal measurement flight trajectory of the UAV through the Riemannian manifold based on the user input information, and generates the attitude command and GPS trajectory data of the UAV.
- the data instruction processing unit forms a speed instruction based on the received signal strength in the currently collected signal data and the GPS trajectory data;
- the UAV platform unit adjusts the flying speed of the UAV based on the speed instruction, and points the directional antenna of the UAV to the antenna phase center based on the attitude instruction and the direction of the pan/tilt.
- executing the flight of the UAV according to the optimal measurement flight trajectory includes:
- the signal data is the measurement data of the antenna to be tested
- the conversion of the GPS position data by the ground data processing unit into a sampling position in spherical coordinates relative to the antenna phase center includes:
- the local rectangular coordinates are converted into spherical coordinates of a spherical coordinate system with the antenna phase center as the origin, and the spherical coordinates are used as the sampling position.
- the signal data is processed by the ground data processing unit to obtain the original data corresponding to the measurement data of the antenna to be tested, the reference data corresponding to the measurement data of the reference antenna, and the measurement of interference with the background The interference data corresponding to the data.
- the correction of the original data and the reference data by the ground data processing unit includes:
- R′ t ( ⁇ ,i), ⁇ ( ⁇ ,i), R′ b ( ⁇ ,i) are the i-th sampling position
- the frequency point is the three received signal strengths of ⁇ and the unit is dBm
- the three received signal strengths are the original data R′ t ( ⁇ , i), the interference data ⁇ ( ⁇ , i), and the reference data R′ b ( ⁇ , i)
- the two received signal strengths at the frequency point ⁇ and the unit is dBm
- the two received signal strengths are the original data after the background interference is eliminated and the results
- the reference data after the background interference is described.
- the correction of the original data and the reference data by the ground data processing unit further includes:
- m is the total number of sampling positions and is a positive integer
- the two normalized signal intensities are the original data after the background interference is eliminated and the normalized processing is eliminated
- the Baseline data after background interference and normalization
- the calibration of the corrected original data through the corrected reference data to obtain the discrete pattern data includes:
- the frequency point is the normalized signal strength of ⁇
- R t ( ⁇ ,i) is the spatial frequency discrete pattern of the antenna under test
- the frequency point is the normalized signal intensity of ⁇
- R t ( ⁇ , i) is used as the discrete pattern data.
- the discrete pattern data is interpolated and completed via a deep neural network, where:
- the depth of the neural network is the neural network depth of two A (n
- n is a random variable that obeys the standard Gaussian distribution p n (n)
- c is the spatial frequency discrete pattern data used for training and the distribution of the spatial frequency discrete pattern data is p data (c)
- d is the network A(n
- ⁇ a and ⁇ b are optimization parameters used for iteration through the cost function.
- the embodiment of the present invention also provides a UAV-based outdoor antenna four-dimensional pattern measurement device, the measurement device includes:
- the measurement path planning unit is used to calculate the flight trajectory of the UAV based on the user input information of the antenna to be tested;
- UAV platform unit used to control the flight of the UAV based on the flight trajectory and also used to collect GPS location data
- the radiation signal acquisition unit is used to receive the signals emitted by the antenna to be tested and the reference antenna in each switch state;
- a data instruction processing unit for adjusting the flight of the drone based on the received signal so that the directional antenna of the drone points to the antenna phase center and also for collecting signal data;
- the ground data processing unit is used to convert the GPS position data into the sampling position in the spherical coordinate system, and process the collected signal data into the original data of the antenna to be tested and the reference data of the reference antenna, and also used to Obtaining spatial frequency four-dimensional pattern data from the original data and the reference data;
- the measurement path planning unit, the radiation signal acquisition unit and the data instruction processing unit are suspended on the UAV platform unit through a pod.
- the measurement path planning unit includes a user input module, a path calculation module, and a control instruction module;
- the user input module is used to obtain user input information
- the path calculation module is used to calculate the optimal measurement flight trajectory of the UAV and the attitude direction at each time based on the user input information
- the control instruction module is used to direct the optimal measured flight trajectory and the attitude to form an attitude instruction.
- the UAV platform unit includes a GPS module, a flight control module, and a pan/tilt control module;
- the data instruction processing unit includes a speed adjustment module and a data sending module
- the data sending module is used to encapsulate the real-time GPS position data collected by the GPS module and the demodulated data of the signal received by the radiation signal collection unit into a data frame, and send it to the ground data processing via a wireless link unit;
- the pan/tilt control module is used to receive the attitude instruction, and the speed adjustment module receives the optimal measured flight trajectory;
- the flight control module is configured to receive a speed command formed by the speed adjustment module based on the signal strength sent by the radiation signal acquisition unit;
- the flight control module is configured to control the flight speed and direction of the UAV based on the speed command received in real time;
- the pan/tilt control module is configured to control the attitude or direction of the directional antenna on board the drone in real time based on the GPS position data sent by the GPS module 1-9 and the attitude instruction;
- the radiation signal collection unit includes the directional antenna and a broadband signal receiver, and the broadband signal receiver is used to demodulate the signal received by the directional antenna.
- the ground data processing unit includes a data receiving module, a data processing module, a data correction module, and a pattern generation module;
- the data processing module is configured to receive a signal with signal data and GPS location data sent by the data sending module through the data receiving module;
- the data processing module performs signal demodulation on the signal sent by the data sending module, and the demodulated data is coordinate transformed and transferred to the data correction module;
- the data correction module performs background interference cancellation and data calibration and then transmits it to the pattern generation module;
- the pattern generation module calculates the antenna pattern data of the E-plane and the H-plane of the antenna to be tested, and reconstructs the spatial frequency four-dimensional antenna pattern data based on the antenna pattern data of the E-plane and the H-plane.
- the invention can realize the high-efficiency and accurate measurement of outdoor antennas, especially large-aperture outdoor antennas, and spatial frequency (spatial and frequency) four-dimensional directional patterns; the invention uses radiation sweep signal measurement, discrete position measured data complement and other means to greatly improve Test efficiency, while using radiated background interference cancellation, reference antenna calibration and other means to greatly improve the test accuracy.
- FIG. 1 is a schematic diagram of the structure of an exemplary antenna pattern measurement device according to an embodiment of the present invention
- FIG. 2 is a schematic flow chart of an exemplary antenna pattern measurement method according to an embodiment of the present invention.
- FIG. 3 is a schematic diagram of a brief flow chart of data processing of exemplary measurement data according to an embodiment of the present invention.
- the embodiment of the present invention provides an outdoor antenna four-dimensional pattern measurement device based on a drone, as shown in Figure 1.
- the measurement device may include a measurement path planning unit 1-1, a drone platform unit 1-2, and a radiation signal acquisition unit 1 -3, the data instruction processing unit 1-4 and the ground data processing unit 1-5, the measurement path planning unit 1-1, the radiation signal acquisition unit 1-3 and the data instruction processing unit 1-4 are suspended from the ground via a pod Man-machine platform unit 1-2.
- the unmanned aerial vehicle may include a shell and an unmanned aerial vehicle platform unit 1-2 in the shell, and the shell may have the aforementioned pod.
- the measurement path planning unit 1-1 may include a user input module 1-6, a path calculation module 1-7, and a control instruction module 1-8.
- the user can input the measurement path through the user input module 1-6.
- the user input information such as the specific position, diameter, type and frequency range of the directional pattern of the antenna, the path calculation module 1-7 calculates the optimal measured flight trajectory and the attitude direction at each moment, and the control command module 1-8 will be optimal Measure the flight trajectory and the corresponding attitude to form an attitude command to the gimbal control module 1-11, and at the same time transmit the flight trajectory data to the speed adjustment module 1-14.
- the UAV platform unit 1-2 may include a GPS (Global Positioning System, GPS) module 1-9, a flight control module 1-10, and a pan/tilt control module 1-11.
- GPS Global Positioning System
- the GPS module 1-9 and data transmission Modules 1-15 are connected, and the real-time collected UAV position data is transmitted to the ground control unit through the data sending module 1-15;
- the flight control module 1-10 receives the speed command from the speed adjustment module 1-14 in real time, and This controls the flying speed and direction of the drone;
- the PTZ control module 1-11 controls the attitude or direction of the airborne antenna in real time according to the position data and attitude commands sent by the GPS module 1-9.
- the radiation signal acquisition unit 1-3 may include a broadband signal receiver 1-12 and a directional antenna 1-13.
- the directional antenna 1-13 collects signals radiated by the ground antenna under test from different positions and directions, and the broadband signal receiver 1- 12 Demodulate the received signal, extract information such as signal strength, and pass it to the speed adjustment module 1-14.
- the data instruction processing unit 1-4 may include a speed adjustment module 1-14 and a data sending module 1-15.
- the data sending module 1-15 receives the real-time position and radiation signal acquisition unit 1-3 received by the GPS module 1-9.
- the collected signal information is encapsulated into a data frame and sent to the data receiving module 1-16 through the wireless link, and the speed adjustment module 1-14 according to the trajectory data sent by the control instruction module 1-8 and the signal sent by the radiation signal acquisition unit 1-3
- the intensity formation speed command is transmitted to the flight control module.
- the ground data processing unit 1-5 includes a data receiving module 1-16, a data processing module 1-17, a data correction module 1-18, and a direction map generating module 1-19.
- the data receiving module 1-16 and data processing Modules 1-17 are connected to receive the signal and position measurement data (signal data and GPS position data) sent by the data sending module 1-15, and pass them to the data processing module 1-17.
- the data processing module 1-17 responds to the received The data undergoes signal demodulation (demodulation, decapsulation, etc.), coordinate conversion and transfer to the data correction module 1-18.
- the data correction module 1-18 performs electromagnetic environment background interference cancellation and signal data calibration and then transfers to the pattern generation module 1-19.
- the pattern generation module 1-19 calculates the antenna pattern data of the E-plane and the H-plane of the antenna to be tested, and reconstructs space and frequency four-dimensional antenna pattern data accordingly. It needs to be pointed out that in some cases, the aforementioned modules or units can be used in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), chip It is implemented in a system on a system (SoC), a load programmable logic device (CPLD), computer hardware, firmware, software, and/or a combination thereof.
- FPGA field programmable gate arrays
- ASIC application-specific integrated circuits
- ASSP application-specific standard products
- SoC system on a system
- CPLD load programmable logic device
- computer hardware firmware, software, and/or a combination thereof.
- the embodiment of the present invention also provides a four-dimensional pattern measurement method of an outdoor antenna based on a drone under the same inventive concept, and the measurement method may include:
- the flight of the drone is performed according to the optimal measurement flight trajectory, and the collection of multiple sets of data and the multiple sets of data are completed by the drone Sending to the ground data processing unit, wherein during the flight of the drone, the directional antenna of the drone points to the antenna phase center, and one set of data in the multiple sets of data includes one flight of the drone
- the ground data processing unit converts the GPS position data into a sampling position in a spherical coordinate system relative to the antenna phase center, and processes the signal data to obtain the original data of the antenna under test and the reference antenna Reference data, wherein the original data and the reference data respectively include the received signal strength corresponding to the frequency point at each sampling position;
- the original data and the reference data are corrected by the ground data processing unit, and the corrected original data is calibrated by the corrected reference data to obtain discrete pattern data;
- Interpolation is performed on the discrete pattern data by the ground data processing unit to obtain the spatial frequency four-dimensional pattern data of the antenna to be tested.
- the user inputs the specific location, diameter, type, and pattern of the antenna to be tested, and the measurement frequency range of the pattern, and the measurement path planning unit 1-1 calculates the unmanned
- the optimal measurement flight trajectory of the aircraft is generated, and the corresponding attitude commands and GPS trajectory data (belonging to the optimal measurement flight trajectory) are generated at each time.
- the speed adjustment module 1-14 forms the speed command according to the currently collected signal strength data and trajectory data.
- the aircraft platform adjusts the flight speed according to the speed command, and makes the directional antenna 1-13 point to the antenna phase center according to the attitude command and the direction of the gimbal.
- the antenna phase center is the area where the antenna radiates signals outward.
- D is the antenna aperture (unit: m)
- f max is the highest frequency (unit: Hz) of the pattern measurement frequency band
- c is the speed of light.
- the hemispherical surface can be defined by the Riemannian manifold geometry, that is, its surface is defined by the hemispherical manifold
- the geodesic distance determines the measurement of the movement track.
- the hemispherical manifold The parameter space of can be expressed as:
- Equation (2) shows that the hemispherical surface Is a three-dimensional Euclidean space Embedded submanifolds, namely Therefore, the Euclidean inner product can be used to define the hemispherical manifold
- the Riemann metric namely:
- Hemisphere according to The distance from the above geodesic line is divided into N ⁇ N (N is a positive integer) grids of equal area, and the center coordinate of each grid is used as a node u of the dendrogram.
- the set of all nodes is V, and the set V is the above A subset of the hemispherical manifold, namely The node in the grid center adjacent to the node u is the child node of the node, and the root node
- the set of all parent nodes of a node u k of order K is W, and the calculation formula for the length s of the side of its child nodes is:
- p k is the node other than the parent node of node u k The directed path to this child node.
- the set of directional paths connected by nodes is the flight trajectory. Among them, in order to ensure the search efficiency, the search path needs to meet the constraint of non-repetitive nodes, and the flight trajectory of the drone can be obtained.
- the UAV performs three flights and completes the data collection task according to the planned flight trajectory, corresponding to the three switch states of the ground transmitting antenna (the state of starting and/or closing any of the aforementioned antennas), which can be the antenna to be tested.
- the ground transmitting antenna the state of starting and/or closing any of the aforementioned antennas
- the reference antenna emit linear frequency sweep signals
- the electromagnetic environment background interference data without any antenna radiation signal is collected, and the collected data is recorded as background interference measurement
- the data ⁇ ( ⁇ ,i) is sent to the data receiving module 1-16 through the data sending module 1-15.
- the data receiving module 1-16 transfers the three sets of data to the data processing module 1-17.
- the data processing module 1-17 demodulates the received data and converts the GPS coordinates of the position data into a ball relative to the antenna phase center. The coordinates are passed to the data correction module 1-18.
- (X, Y, Z) is the geocentric space rectangular coordinates
- (X 0 , Y 0 , Z 0 ) is the geocentric space rectangular origin coordinates
- (B, L, H) is the geocentric geodetic coordinates.
- ⁇ is the pitch angle relative to the origin
- the data correction module 1-18 performs abnormal value elimination, electromagnetic environment background interference (ie background interference) cancellation (or elimination) and data calibration, and then transmits it to the pattern generation module 1-19.
- the specific implementation is as follows:
- R′ t ( ⁇ ,i), ⁇ ( ⁇ ,i), R′ b ( ⁇ ,i) is the i-th sampling position, and the frequency point is the received signal strength of ⁇ (unit: dBm)
- R′ t ( ⁇ ,i), ⁇ ( ⁇ ,i), R′ b ( ⁇ ,i) are respectively the original data R′ t ( ⁇ ,i), the interference data ⁇ ( ⁇ ,i) and the reference data R′ b ( ⁇ ,i)
- the frequency point is the received signal strength of ⁇ (unit: dBm)
- They are the original data after the background interference is eliminated and the reference data after the background interference is eliminated.
- m is the total number of sampling points, Represents the i-th sampling position, the normalized signal strength of frequency point ⁇ , The following are the original data after the background interference is eliminated and the normalized processing, the reference data after the background interference is eliminated, and the normalized processing.
- the standard antenna pattern of the reference antenna corresponds to the i-th sampling position
- the frequency point is the normalized signal strength of ⁇
- R t ( ⁇ , i) is the spatial frequency (space and frequency) discrete pattern data.
- the pattern generation module 1-19 uses the neural network A(n
- n is a random variable that obeys the standard Gaussian distribution p n (n)
- c is the spatial frequency discrete pattern data used for training (distributed by p data (c))
- d is the network A(n
- the output of ⁇ a ) or continuous pattern data (distributed as p data (d)) used for training, and ⁇ a and ⁇ b are the parameters to be optimized of the respective corresponding networks.
- the training objectives of these two deep neural networks are to optimize ⁇ a and ⁇ b to satisfy the following formula:
- V(A,B) is the cost function during deep neural network training
- ⁇ is the Hadamard product
- F( ⁇ ) is the output of the network A(n
- di ,j is the distance between the i-th sampling position and the j-th sampling position
- ⁇ 1 and ⁇ 2 are the weights of their respective parts.
- the relative magnitude relationship between ⁇ 1 and ⁇ 2 needs to be determined by using prior information such as the sampling location of the drone, outdoor weather environment, etc., that is, the prior information will determine part of the model of the interpolation algorithm based on deep learning.
- c; ⁇ b ) are trained for several iterations, the network A(n
- the time-frequency four-dimensional pattern of the antenna is obtained instead of the traditional spatial three-dimensional pattern.
- a half-wave symmetrical array antenna with a latitude of 31.93°, a longitude of 118.79°, an antenna phase center height of 5m, and an aperture of 6m is taken as an example below.
- the measurement frequency band is an antenna of 40MHz-50MHz.
- the user inputs information such as the location, diameter, type, and measurement frequency range of the antenna to be tested, and the measurement path planning unit 1-1 calculates the optimal measurement flight trajectory of the UAV based on this, and generates the corresponding attitude command and GPS trajectory data ,
- the speed adjustment module 1-14 forms a speed command according to the currently collected signal strength data and trajectory data.
- the UAV platform adjusts the flight speed according to the speed command, and makes the directional antenna 1-13 point to the antenna phase according to the attitude command and the direction of the pan/tilt. center.
- the GPS position of the antenna under test is (31.93,118.79,5), and the GPS coordinates (B, L, H) of the flight trajectory can be obtained by using equations (5), (6) and the GPS position of the antenna under test.
- the UAV performs three flights and completes the data collection task according to the planned flight trajectory, corresponding to the three states of the ground transmitting antenna, the antenna under test emits a linear frequency sweep signal, and the electromagnetic environment background interference when the antenna under test is closed And the reference antenna transmit a linear frequency sweep signal, and send the three sets of collected data to the ground data receiving module 1-16 in turn, the specific implementation is as follows:
- the electromagnetic environment background interference data without any antenna radiation signal is collected, and the collected data is recorded as background interference measurement
- the data ⁇ ( ⁇ ,i) is sent to the data receiving module 1-16 through the data sending module 1-15.
- the data receiving module 1-16 transfers the three sets of data to the data processing module 1-17.
- the data processing module 1-17 demodulates the received data and converts the GPS coordinates of the position data into a ball relative to the antenna phase center. The coordinates are passed to the data correction module 1-18.
- the data correction module 1-18 performs abnormal value elimination, electromagnetic environment background interference cancellation and data calibration on the data and then transmits it to the pattern generation module 1-19.
- the specific implementation is as follows:
- the fifth step, the pattern generation module 1-19 uses the neural network A(n
- the program is stored in a storage medium and includes several instructions to enable the single-chip microcomputer, chip or processor (processor) Execute all or part of the steps of the method described in each embodiment of the present application.
- the aforementioned storage medium may be non-transitory.
- the storage medium may include: U disk, hard disk, read-only memory (ROM, Read-Only Memory), flash memory (Flash memory), magnetic disk or optical disk, etc., which can store program code. medium.
Abstract
本发明提供一种基于无人机的室外天线四维方向图测量方法及装置，属于天线技术领域。所述测量装置包括测量路径规划单元，无人机平台单元，辐射信号采集单元，数据指令处理单元以及地面数据处理单元，所述测量路径规划单元，辐射信号采集单元和数据指令处理单元通过吊舱悬挂于无人机平台单元。本发明可用于室外天线方向图测量。
Description
本发明涉及天线技术领域，具体地涉及一种基于无人机的室外天线四维方向图测量方法和一种基于无人机的室外天线四维方向图测量装置。
天线是广播、电视、通信、雷达、导航、电子对抗、遥感、射电天文等领域应用设备的重要组成部分。天线的方向图直接体现了天线辐射信号的能力，而天线辐射特性的测量结果是否精确，不仅涉及天线性能指标的验证，更关系到整体系统的工作性能。所以，天线方向图的精确测量是硬件设备性能测量极其重要的一个环节。
天线周围的辐射场分为近场区和远场区，二者以第一菲涅尔半径r＝2D
2/λ为分界，其中，D为天线口径，单位：米(m)，λ为天线工作最高频率的波长，单位：米(m)。在进行天线方向图测量时，也分为近场测量和远场测量两种方式。其中，近场测量和小口径天线的远场测量通常利用微波暗室在室内进行。微波暗室是金属屏蔽体组建的特殊房间,当电磁波入射到墙面、天棚、地面时，绝大部分电磁波被吸收，而透射、反射极少，近似满足“自由空间”条件。
对于口径较大的天线(如短波天线)而言，其远场测量需要的空间较大，微波暗室空间有限难以实现。目前，室外天线远场测量分为 高架天线测试场、斜天线测试场和基于无人机的测试法。其中，利用高架天线测试场和斜天线测试场进行室外测试，都需要有高大的建筑物或建立绝缘塔，建设成本较大，并且需要把待测天线安装在上面，但对于大中口径天线搬运、安装都相当耗时费力。此外，受到大地反射等因素的影响，测量误差根本无法估算，因此常规的室外测试场对于大中型天线的远场测量也无能为力。特别地，天线的安装、调试和使用环境对于天线实际工作状态下的辐射方向图影响较大，导致在测试场测量结果和实际工作时结果不一致，进行影响整个系统的性能评估。对于无人机测试法，不需要移动天线位置，可以直接进行室外天线方向图的测试，然而，现有方法只针对三维方向图测量，并且测试效率低，也没有充分考虑系统误差的消除方法。
发明内容
本发明的目的是提供一种基于无人机的室外天线四维方向图测量方法及装置，解决现有室外天线方向图测量存在的效率低、精度差等问题，进而完成包含空间和频率因素的四维方向图测试，同时利用干扰背景抵消技术，有效提高测试精度。
为了实现上述目的，本发明实施例提供一种基于无人机的室外天线四维方向图测量方法，该测量方法包括：
基于待测天线的用户输入信息，计算无人机的最优测量飞行轨迹；
基于所述待测天线和基准天线的开关状态，按照所述最优测量飞行轨迹分别执行所述无人机的飞行，并经所述无人机完成多组数据的 采集及所述多组数据至地面数据处理单元的发送，其中，在所述无人机的飞行过程中所述无人机的定向天线指向天线相位中心，所述多组数据中一组数据包括所述无人机一次飞行中采集的信号数据和相应的GPS位置数据；
经所述地面数据处理单元转换所述GPS位置数据为相对所述天线相位中心的球坐标系下的采样位置，并处理所述信号数据得到所述待测天线的原始数据和所述基准天线的基准数据，其中，所述原始数据和所述基准数据分别包括各个采样位置上与频点对应的接收信号强度；
经所述地面数据处理单元修正所述原始数据和所述基准数据，并通过修正后的基准数据标定修正后的原始数据，获得离散方向图数据；
经所述地面数据处理单元对所述离散方向图数据进行内插补全，获得所述待测天线的空间频率四维方向图数据。
具体的，所述基于待测天线的用户输入信息，计算无人机的最优测量飞行轨迹，包括：
经测量路径规划单元基于所述用户输入信息，通过黎曼流形计算无人机的最优测量飞行轨迹，并生成所述无人机的姿态指令和GPS轨迹数据。
具体的，在所述无人机的飞行过程中，
经数据指令处理单元基于当前采集到的信号数据中接收信号强度和所述GPS轨迹数据形成速度指令；
经无人机平台单元基于所述速度指令调整所述无人机的飞行速 度，并基于所述姿态指令和云台指向，将所述无人机的定向天线指向天线相位中心。
具体的，基于所述待测天线和基准天线的开关状态，按照所述最优测量飞行轨迹分别执行所述无人机的飞行，包括：
启动所述待测天线，经所述待测天线发射测试频段的线性扫频信号，按照所述最优测量飞行轨迹执行所述无人机的第一次飞行，其中，此次飞行中采集的信号数据为所述待测天线的测量数据；
关闭所述待测天线，按照所述最优测量飞行轨迹执行所述无人机的第二次飞行，其中，此次飞行中采集的信号数据为背景干扰的测量数据；
在所述待测天线附近位置放置基准天线，启动所述基准天线，经所述基准天线发射所述测试频段的线性扫频信号，按照所述最优测量飞行轨迹执行所述无人机的第三次飞行，其中，此次飞行中采集的信号数据为所述基准天线的测量数据。
具体的，所述经所述地面数据处理单元转换所述GPS位置数据为相对所述天线相位中心的球坐标下的采样位置，包括：
将所述GPS位置数据中GPS坐标转化为地心空间直角坐标系的坐标；
将所述地心空间直角坐标转化为以所述天线相位中心为原点的当地直角坐标；
将所述当地直角坐标转化为以所述天线相位中心为原点的球坐标系的球坐标，所述球坐标作为采样位置。
具体的，经所述地面数据处理单元处理所述信号数据得到与所述待测天线的测量数据对应的原始数据、与所述基准天线的测量数据对应的基准数据和与所述背景干扰的测量数据对应的干扰数据。
具体的，所述经所述地面数据处理单元修正所述原始数据和所述基准数据，包括：
以下式剔除所述原始数据和所述基准数据中的干扰数据：
式中，R′
t(ζ,i),σ(ζ,i),R′
b(ζ,i)为第i个采样位置，频点为ζ的三个接收信号强度且单位为dBm，所述三个接收信号强度依次为所述原始数据R′
t(ζ,i)、所述干扰数据σ(ζ,i)和所述基准数据R′
b(ζ,i)，
为消除所述背景干扰后的第i个采样位置，频点为ζ的两个接收信号强度且单位为dBm，所述两个接收信号强度依次为消除所述背景干扰后的原始数据和消除所述背景干扰后的基准数据。
具体的，所述经所述地面数据处理单元修正所述原始数据和所述基准数据，还包括：
以下式对消除所述背景干扰后的原始数据和消除所述背景干扰后的基准数据分别进行归一化：
式中，m为采样位置总数且为正整数，
表示第i个 采样位置，频点为ζ的两个归一化信号强度，所述两个归一化信号强度依次为消除所述背景干扰后和归一化处理后的原始数据、消除所述背景干扰后和归一化处理后的基准数据。
具体的，所述通过修正后的基准数据标定修正后的原始数据，获得离散方向图数据，包括：
以下式利用消除所述背景干扰后和归一化处理后的基准数据对消除所述背景干扰后和归一化处理后的原始数据进行标定，获得离散方向图数据：
式中，
为与所述基准天线的标准天线方向图对应的第i个采样位置，频点为ζ的归一化信号强度，R
t(ζ,i)为与所述待测天线的空间频率离散方向图对应的第i个采样位置，频点为ζ的归一化信号强度，R
t(ζ,i)作为离散方向图数据。
具体的，经深度神经网络对所述离散方向图数据进行内插补全，其中，
所述深度神经网络为两个深度神经网络A(n|c；θ
a)和B(d|c；θ
b)经若干次迭代训练后的A(n|c；θ
a)，
n为服从标准高斯分布p
n(n)的随机变量，c为用于训练的空间频率离散方向图数据且该空间频率离散方向图数据的分布为p
data(c)，d为网络A(n|c；θ
a)的输出或用于训练的连续方向图数据且该连续方向图数据的分布为p
data(d)，θ
a和θ
b为用于经代价函数迭代的优化参数。
本发明实施例还提供一种基于无人机的室外天线四维方向图测 量装置，该测量装置包括：
测量路径规划单元，用于基于待测天线的用户输入信息，计算无人机的飞行轨迹；
无人机平台单元，用于基于所述飞行轨迹控制所述无人机的飞行以及还用于采集GPS位置数据；
辐射信号采集单元，用于接收待测天线和基准天线在各个开关状态下发射的信号；
数据指令处理单元，用于基于接收的信号调整所述无人机的飞行以使得所述无人机的定向天线指向天线相位中心以及还用于采集信号数据；
地面数据处理单元，用于转换所述GPS位置数据为球坐标系下的采样位置，并将采集的信号数据处理为所述待测天线的原始数据和基准天线的基准数据，以及还用于基于所述原始数据和所述基准数据，获得空间频率四维方向图数据；
所述测量路径规划单元、辐射信号采集单元和数据指令处理单元通过吊舱悬挂于无人机平台单元。
具体的，所述测量路径规划单元包括用户输入模块、路径计算模块和控制指令模块；
所述用户输入模块，用于获得用户输入信息；
所述路径计算模块，用于基于所述用户输入信息，计算无人机的最优测量飞行轨迹和各个时刻的姿态指向，
所述控制指令模块，用于将所述最优测量飞行轨迹及所述姿态指 向形成姿态指令。
具体的，所述无人机平台单元包括GPS模块、飞行控制模块和云台控制模块；
所述数据指令处理单元包括速度调节模块和数据发送模块；
所述数据发送模块用于将所述GPS模块采集到的实时的GPS位置数据、所述辐射信号采集单元接收的信号的解调数据封装成数据帧，通过无线链路发送给所述地面数据处理单元；
所述云台控制模块用于接收所述姿态指令，同时所述速度调节模块接收所述最优测量飞行轨迹；
所述飞行控制模块用于接收由所述速度调节模块基于所述辐射信号采集单元发送的信号强度所形成的速度指令；
所述飞行控制模块用于基于实时接收的速度指令，控制所述无人机的飞行速度和方向；
所述云台控制模块用于基于所述GPS模块1-9发送的GPS位置数据和所述姿态指令实时控制所述无人机机载的定向天线的姿态或方向；
所述辐射信号采集单元包括所述定向天线和宽带信号接收机，所述宽带信号接收机用于解调所述定向天线接收的信号。
具体的，所述地面数据处理单元包括数据接收模块、数据处理模块、数据修正模块和方向图生成模块；
所述数据处理模块用于通过所述数据接收模块接收所述数据发送模块发送的具有信号数据和GPS位置数据的信号；
所述数据处理模块对所述数据发送模块发送的信号进行信号解调、解调的数据经坐标转化并传递给所述数据修正模块；
所述数据修正模块进行背景干扰消除和数据标定后传递给所述方向图生成模块；
所述方向图生成模块计算所述待测天线的E面和H面的天线方向图数据，并基于所述E面和H面的天线方向图数据，重构出空间频率四维天线方向图数据。
本发明可以实现室外天线，特别是大口径的室外天线，空间频率(空间和频率的)四维方向图的高效精确测量；本发明利用辐射扫频信号测量、离散位置实测数据补全等手段大大提高测试效率，同时采用辐射背景干扰抵消、基准天线标定等手段大大提升测试精度。
本发明实施例的其它特征和优点将在随后的具体实施方式部分予以详细说明。
附图是用来提供对本发明实施例的进一步理解，并且构成说明书的一部分，与下面的具体实施方式一起用于解释本发明实施例，但并不构成对本发明实施例的限制。在附图中：
图1为本发明实施例的示例性天线方向图测量装置组成架构示意图；
图2为本发明实施例的示例性天线方向图测量方法简要流程示意图；
图3为本发明实施例的示例性测量数据的数据处理简要流程示意图。
以下结合附图对本发明实施例的具体实施方式进行详细说明。应当理解的是，此处所描述的具体实施方式仅用于说明和解释本发明实施例，并不用于限制本发明实施例。
实施例1
本发明实施例提供了基于无人机的室外天线四维方向图测量装置，如图1，该测量装置可以包括测量路径规划单元1-1，无人机平台单元1-2，辐射信号采集单元1-3，数据指令处理单元1-4以及地面数据处理单元1-5，所述测量路径规划单元1-1，辐射信号采集单元1-3和数据指令处理单元1-4通过吊舱悬挂于无人机平台单元1-2。无人机可以包括壳体和壳体内的无人机平台单元1-2，壳体可有前述的吊舱。
在一些具体实施中，所述测量路径规划单元1-1可以包括用户输入模块1-6、路径计算模块1-7和控制指令模块1-8，用户可以通过用户输入模块1-6输入待测天线的具体位置、口径、类型和方向图测量频段范围等用户输入信息，路径计算模块1-7据此计算最优测量的飞行轨迹和各个时刻的姿态指向，控制指令模块1-8将最优测量飞行轨迹及对应姿态形成姿态指令传递给云台控制模块1-11，同时将飞行轨迹数据传递给速度调节模块1-14。
所述无人机平台单元1-2可以包括GPS(Global Positioning System，GPS)模块1-9、飞行控制模块1-10和云台控制模块1-11，所述GPS模块1-9与数据发送模块1-15相连，将实时采集无人机的位置数据通过数据发送模块1-15传输到地面控制单元；所述飞行控制模块1-10实时接收速度调节模块1-14的速度指令，并据此控制无人机的飞行速度和方向；所述云台控制模块1-11根据GPS模块1-9发送的位置数据和姿态指令实时控制机载天线的姿态或方向。
所述辐射信号采集单元1-3可以包括宽带信号接收机1-12和定向天线1-13，定向天线1-13从不同位置和方向采集地面待测天线辐射的信号，宽带信号接收机1-12将接收信号解调，提取信号强度等信息，并传递给速度调节模块1-14。
所述数据指令处理单元1-4可以包括速度调节模块1-14和数据发送模块1-15，数据发送模块1-15将GPS模块1-9接收到的实时位置、辐射信号采集单元1-3采集的信号信息封装成数据帧，通过无线链路发送给数据接收模块1-16，速度调节模块1-14根据控制指令模块1-8发送的轨迹数据和辐射信号采集单元1-3发送的信号强度形成速度指令传输给飞行控制模块。
所述地面数据处理单元1-5包括数据接收模块1-16、数据处理模块1-17、数据修正模块1-18和方向图生成模块1-19，所述数据接收模块1-16与数据处理模块1-17相连，接收数据发送模块1-15发送的信号和位置测量数据(信号数据和GPS位置数据)，并将其传递给数据处理模块1-17，数据处理模块1-17对接收的数据进行信号解调 (解调、解封装等处理)、坐标转化并传递给数据修正模块1-18，数据修正模块1-18进行电磁环境背景干扰抵消和信号数据标定后传递给方向图生成模块1-19，所述方向图生成模块1-19计算待测天线E面和H面的天线方向图数据，并据此重构出空间和频率的四维天线方向图数据。需要提出的是，在一些情况中，前述的模块或单元可以在数字电子电路系统、集成电路系统、现场可编程门阵列(FPGA)、专用集成电路(ASIC)、专用标准产品(ASSP)、芯片上系统的系统(SoC)、负载可编程逻辑设备(CPLD)、计算机硬件、固件、软件、和/或它们的组合中实现。
本发明实施例还提供了属于同一发明构思下的基于无人机的室外天线四维方向图测量方法，该测量方法可以包括：
基于待测天线的用户输入信息，计算无人机的最优测量飞行轨迹；
基于所述待测天线和基准天线的开关状态，按照所述最优测量飞行轨迹分别执行所述无人机的飞行，并经所述无人机完成多组数据的采集及所述多组数据至地面数据处理单元的发送，其中，在所述无人机的飞行过程中所述无人机的定向天线指向天线相位中心，所述多组数据中一组数据包括所述无人机一次飞行中采集的信号数据和相应的GPS位置数据；
经所述地面数据处理单元转换所述GPS位置数据为相对所述天线相位中心的球坐标系下的采样位置，并处理所述信号数据得到所述待测天线的原始数据和所述基准天线的基准数据，其中，所述原始数据和所述基准数据分别包括各个采样位置上与频点对应的接收信号 强度；
经所述地面数据处理单元修正所述原始数据和所述基准数据，并通过修正后的基准数据标定修正后的原始数据，获得离散方向图数据；
经所述地面数据处理单元对所述离散方向图数据进行内插补全，获得所述待测天线的空间频率四维方向图数据。
在一些具体实施中，如图2和图3，第一步，用户输入待测天线的具体位置、口径、类型和方向图测量频段范围等信息，测量路径规划单元1-1据此计算无人机的最优测量飞行轨迹，生成各个时刻对应姿态指令和GPS轨迹数据(属于最优测量飞行轨迹)，速度调节模块1-14根据当前采集到的信号强度数据和轨迹数据形成速度指令，无人机平台根据速度指令调整飞行速度，根据姿态指令和云台指向，使定向天线1-13指向天线相位中心，天线相位中心是天线向外辐射信号的区域。
进一步地，测量飞行轨迹具体计算如下：
1)无人机飞行轨迹在以天线相位中心为原点的半球面上，半径利用如下公式计算：
r＝2D
2/λ，λ＝c/f
max (1)
式中D为天线口径(单位：m)，f
max为方向图测量频段最高频率(单位：Hz)，c为光速。
2)建立以天线相位中心为原点的球坐标系，半球面可由黎曼流形几何结构定义，即其表面由半球面流形
的测地线距离确定移动轨迹的度量。此时，半球面流形
的参数空间可表示为：
其中，θ为相对原点的俯仰角，
为相对原点的方位角。式(2)表明，半球面
是三维欧氏空间
的嵌入子流形，即
因此，可以使用欧氏内积来定义该半球面流形
的黎曼度量，即：
<ξ,η>
u:＝ξ
Tη (3)
式中，
表示流形上的点u的切向量。
将半球面
按
和上述测地线距离划分为N×N(N为正整数)个等面积网格，每一个网格中心坐标作为树状图的一个节点u，所有节点的集合为V，该集合V为上述半球面流形的子集，即
与节点u相邻网格中心的节点为该节点的子节点，其中根节点
阶度为K的节点u
k所有父节点的集合为W,与其子节点的边的长度s的计算公式为：
式中，p
k为其他非节点u
k父节点的节点
到该子节点的有向路径。
选择从根节点到阶度为0.5N
2的节点边长和最短的路径。节点相连的有向路径构成的集合为飞行轨迹。其中，为保证搜索效率，搜索路径需满足不重复节点的约束，可以得到无人机的飞行轨迹
3)令待测天线的GPS位置为(B
0,L
0,H
0)，B
0,L
0,H
0分别为待测天线的纬度、经度与高度，飞行轨迹相对于天线的大地坐标标可利用如下公式计算
将(B
0,L
0,H
0)和(ΔB,ΔL,ΔH)进行叠加，即可获得测量飞行轨迹的任意位置GPS坐标(B,L,H)。
第二步，无人机依据规划的飞行轨迹，进行三次飞行并完成数据采集任务，对应地面发射天线的三种开关状态(启动和/或关闭前述任意天线的状态)，具体可以是待测天线发射线性扫频信号、待测天线关闭时的电磁环境背景干扰和基准天线发射线性扫频信号，并将三组采集到的离散数据依次发送给地面数据接收模块1-16，具体实现如下：
1)启动待测天线发射测试频段的线性扫频信号，无人机按规划轨迹进行飞行，飞行速度由轨迹数据和实时采集的信号强度变化速率决定，飞行姿态由实时的位置数据和预设的姿态指令决定，采集数据记为待测天线测量数据R′
t(ζ,i)，通过数据发送模块1-15发送给数据接收模块1-16。
2)关闭待测天线，无人机按规划轨迹进行飞行，不同时刻飞行速度与姿态和上次测试保持一致，采集无任何天线辐射信号时的电磁环境背景干扰数据，采集数据记为背景干扰测量数据σ(ζ,i)，通过数据发送模块1-15发送给数据接收模块1-16。
3)在待测天线附近(附近是指处于指定距离范围以内，视为是附近，如距待测天线1米以内、2米以内、10米以内等相对待测天线尺寸而言合适的距离范围)放置一个基准天线，并启动基准天线发射测试频段的线性扫频信号，无人机按规划轨迹进行飞行，不同时刻飞行速度与姿态和上次测试保持一致，采集数据记为基准天线测量数据R′
b(ζ,i)通过数据发送模块1-15发送给数据接收模块1-16。
第三步，数据接收模块1-16将三组数据传递给数据处理模块1-17，数据处理模块1-17对接收数据进行解调，并将位置数据GPS坐标转化为相对天线相位中心的球坐标并传递给数据修正模块1-18。
进一步地，GPS坐标转化具体方法如下：
1)将位置数据GPS坐标转化为地心空间直角坐标系的坐标，转换方法如下
式中
a＝6378137m,b＝6356752m，B,L,H分别为纬度、经度与高度。
2)将地心空间直角坐标转化为以天线相位中心为原点的当地直角坐标，转换方法如下：
式中(X,Y,Z)为地心空间直角坐标,(X
0,Y
0,Z
0)为地心空间直角原点坐标，(B,L,H)为地心大地坐标。
3)将当地直角坐标转化为以天线相位中心为原点的球坐标，转换方法如下：
式中r为当地直角坐标系点(X
p,Y
p,Z
p)与原点距离，θ为相对原点的俯仰角，
为相对原点的方位角。
第四步，数据修正模块1-18对数据进行异常值剔除、电磁环境背景干扰(即背景干扰)抵消(或消除)和数据标定后传递给方向图生成模块1-19，具体实现如下：
1)剔除原始数据和基准数据中明显异常的值，同时剔除相同位置的电磁环境背景干扰数据，方法如下：
式中，R′
t(ζ,i)，σ(ζ,i)，R′
b(ζ,i)为第i个采样位置，频点为ζ的接收信号强度(单位：dBm)，R′
t(ζ,i)，σ(ζ,i)，R′
b(ζ,i)依次分别为原始数据R′
t(ζ,i)、干扰数据σ(ζ,i)和基准数据R′
b(ζ,i)，
为消除电磁环境背景干扰后第i个采样位置，频点为ζ的接收信号强度(单位：dBm)，
依次分别为消除背景干扰后的原始数据和消除背景干扰后的基准数据。
2)对消除电磁环境背景干扰的两组数据分别进行归一化，方法如下：
式中，m为采样点的总数，
表示第i个采样位置，频点为ζ的归一化信号强度，
依次为消除所述背景干扰后和归一化处理后的原始数据、消除所述背景干扰后和归一化处理后的基准数据。
3)利用排除电磁干扰和归一化处理后的基准数据对排除电磁干扰和归一化处理后的原始数据进行标定，方法如下
式中，
为基准天线的标准天线方向图对应第i个采样位置，频点为ζ的归一化信号强度，R
t(ζ,i)为空间频率(空间和频率的)离散方向图数据。
第五步，方向图生成模块1-19利用基于深度学习的数据生成算法训练的神经网络A(n|c；θ
a)对空间频率离散方向图数据R
t(ζ,i)进行内插补全，获得待测天线的空间频率四维方向图数据R(f,r)。
利用与待测天线相同类型的天线四维方向图连续数据和空间频率离散方向图数据训练两个深度神经网络，分别记为：A(n|c；θ
a)和B(d|c；θ
b)，其中
n为服从标准高斯分布p
n(n)的随机变量，c为用于训练的(分布为p
data(c)的)空间频率离散方向图数据，d为网络A(n|c；θ
a)的输出或用于训练的(分布为p
data(d)的)连续方向图数据，而θ
a和θ
b为各自对应网络的待优化参数。具体而言，这两个深度神经网络的训练目标为优化θ
a和θ
b，以满足下式：
式中，V(A,B)为深度神经网络训练时的代价函数，⊙为Hadamard积，F(·)为根据空间频率离散方向图数据采样情况对网络A(n|c；θ
a)输出进行相同采样的采样函数，而权重W
c的第i个元素：
式中，d
i,j为第i个采样位置和第j个采样位置间的距离，而λ
1和λ
2为各自部分的权重。进一步地，λ
1和λ
2的相对大小关系需要利用无人机采样位置、室外天气环境等先验信息来决定，即这些先验信息将决定该基于深度学习的插值算法的部分模型。待网络A(n|c；θ
a)和B(d|c；θ
b)若干次迭代训练后，可使用此时的网络A(n|c；θ
a)对空间频率离散方向图数据R
t(ζ,i)进行内插补全，生成天线四维(连续)方向图数据R(f,r)。
本发明实施例有以下优点：
(1)根据天线的位置和类型等特性，自主规划最优的飞行测量路径，并将实时的飞行位置回传给地面数据处理单元1-5进行校正，大大降低飞行轨迹偏差带来的影响；
(2)通过测量待测天线发射的宽带扫频信号，一次性测量获得特定频段范围的所有方向图，而传统方法一次测量仅能获得单一频点的方向图；
(3)利用电磁环境背景干扰测量和数据标定，使测量结果更加精准；
(4)根据四维天线方向图生成算法，得到天线的时间频率四维方向图而不是传统的空间三维方向图。
在本公开的一种示例性具体实施中，下面以纬度31.93°，经度为118.79°，天线相位中心高度为5m，口径为6m的半波对称阵子天线为例，测量频段为40MHz-50MHz的天线方向图，需要说明的是，此例并不作为本发明实施例的限定实施方式。
第一步，用户输入待测天线的位置、口径、类型和测量频段范围等信息，测量路径规划单元1-1据此计算无人机的最优测量飞行轨迹，生成对应姿态指令和GPS轨迹数据，速度调节模块1-14根据当前采集到的信号强度数据和轨迹数据形成速度指令，无人机平台根据速度指令调整飞行速度，根据姿态指令和云台指向，使定向天线1-13指向天线相位中心。
进一步地，第一步测量飞行轨迹具体计算如下：
1)无人机测量飞行路径包括E面和H面，二者都以待测天线为原点，将参数代入式(1)，可得半径r＝12m；
2)根据所述算法得到无人机飞行轨迹的球坐标
3)待测天线的GPS位置为(31.93,118.79,5)，利用式(5)、式(6)和待测天线GPS位置即可获得飞行轨迹的GPS坐标(B,L,H)。
第二步，无人机依据规划的飞行轨迹，进行三次飞行并完成数据采集任务，对应地面发射天线的三种状态，待测天线发射线性扫频信 号、待测天线关闭时的电磁环境背景干扰和基准天线发射线性扫频信号，并将三组采集数据依次发送给地面数据接收模块1-16，具体实现如下：
1)启动待测天线发射测试频段的线性扫频信号，无人机按规划轨迹进行飞行，飞行速度由轨迹数据和实时采集的信号强度变化速率决定，飞行姿态由实时的位置数据和预设的姿态指令决定，采集数据记为待测天线测量数据R′
t(ζ,i)，通过数据发送模块1-15发送给数据接收模块1-16。
2)关闭待测天线，无人机按规划轨迹进行飞行，不同时刻飞行速度与姿态和上次测试保持一致，采集无任何天线辐射信号时的电磁环境背景干扰数据，采集数据记为背景干扰测量数据σ(ζ,i)，通过数据发送模块1-15发送给数据接收模块1-16。
3)在待测天线附近放置一个基准天线，并启动基准天线发射测试频段的线性扫频信号，无人机按规划轨迹进行飞行，不同时刻飞行速度与姿态和上次测试保持一致，采集数据记为基准天线测量数据R′
b(ζ,i)通过数据发送模块1-15发送给数据接收模块1-16。
第三步，数据接收模块1-16将三组数据传递给数据处理模块1-17，数据处理模块1-17对接收数据进行解调，并将位置数据GPS坐标转化为相对天线相位中心的球坐标并传递给数据修正模块1-18。
利用式(7)、式(8)、式(9)将位置数据GPS坐标转化为以天线相位中心为原点的球坐标。
第四步，数据修正模块1-18对数据进行异常值剔除、电磁环境 背景干扰抵消和数据标定后传递给方向图生成模块1-19，具体实现如下：
1)利用式(10)和(11)剔除原始数据和基准数据中明显异常的值，同时剔除相同GPS位置的电磁环境背景干扰数据，例如，R′
t(ζ,2)＝20dBm，σ(ζ,2)＝10dBm，则
2)利用式(12)和式(13)对消除电磁环境背景干扰后的两组数据分别进行归一化，
例如，
则
3)利用式(14)排除电磁干扰和归一化处理后的基准数据对排除电磁干扰和归一化处理后的原始数据进行标定，例如
则R
t(ζ,i)＝-21dBm。
第五步，方向图生成模块1-19利用基于深度学习的数据生成算法训练的神经网络A(n|c；θ
a)对最终空间频率离散方向图数据进行内插补全，获得待测天线的空间频率四维方向图数据R(f,r)。
以上结合附图详细描述了本发明实施例的可选实施方式，但是，本发明实施例并不限于上述实施方式中的具体细节，在本发明实施例的技术构思范围内，可以对本发明实施例的技术方案进行多种简单变型，这些简单变型均属于本发明实施例的保护范围。
另外需要说明的是，在上述具体实施方式中所描述的各个具体技术特征，在不矛盾的情况下，可以通过任何合适的方式进行组合。为了避免不必要的重复，本发明实施例对各种可能的组合方式不再另行 说明。
本领域技术人员可以理解实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得单片机、芯片或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质可以是非瞬时的，存储介质可以包括：U盘、硬盘、只读存储器(ROM，Read-Only Memory)、闪存(Flash memory)、磁碟或者光盘等各种可以存储程序代码的介质。
此外，本发明实施例的各种不同的实施方式之间也可以进行任意组合，只要其不违背本发明实施例的思想，其同样应当视为本发明实施例所公开的内容。
Claims (14)
- 一种基于无人机的室外天线四维方向图测量方法，其特征在于，该测量方法包括：基于待测天线的用户输入信息，计算无人机的最优测量飞行轨迹；基于所述待测天线和基准天线的开关状态，按照所述最优测量飞行轨迹分别执行所述无人机的飞行，并经所述无人机完成多组数据的采集及所述多组数据至地面数据处理单元的发送，其中，在所述无人机的飞行过程中所述无人机的定向天线指向天线相位中心，所述多组数据中一组数据包括所述无人机一次飞行中采集的信号数据和相应的GPS位置数据；经所述地面数据处理单元转换所述GPS位置数据为相对所述天线相位中心的球坐标系下的采样位置，并处理所述信号数据得到所述待测天线的原始数据和所述基准天线的基准数据，其中，所述原始数据和所述基准数据分别包括各个采样位置上与频点对应的接收信号强度；经所述地面数据处理单元修正所述原始数据和所述基准数据，并通过修正后的基准数据标定修正后的原始数据，获得离散方向图数据；经所述地面数据处理单元对所述离散方向图数据进行内插补全，获得所述待测天线的空间频率四维方向图数据。
- 根据权利要求1所述的基于无人机的室外天线四维方向图测量方法，其特征在于，所述基于待测天线的用户输入信息，计算无人机 的最优测量飞行轨迹，包括：经测量路径规划单元基于所述用户输入信息，通过黎曼流形计算无人机的最优测量飞行轨迹，并生成所述无人机的姿态指令和GPS轨迹数据。
- 根据权利要求2所述的基于无人机的室外天线四维方向图测量方法，其特征在于，在所述无人机的飞行过程中，经数据指令处理单元基于当前采集到的信号数据中接收信号强度和所述GPS轨迹数据形成速度指令；经无人机平台单元基于所述速度指令调整所述无人机的飞行速度，并基于所述姿态指令和云台指向，将所述无人机的定向天线指向天线相位中心。
- 根据权利要求1所述的基于无人机的室外天线四维方向图测量方法，其特征在于，基于所述待测天线和基准天线的开关状态，按照所述最优测量飞行轨迹分别执行所述无人机的飞行，包括：启动所述待测天线，经所述待测天线发射测试频段的线性扫频信号，按照所述最优测量飞行轨迹执行所述无人机的第一次飞行，其中，此次飞行中采集的信号数据为所述待测天线的测量数据；关闭所述待测天线，按照所述最优测量飞行轨迹执行所述无人机的第二次飞行，其中，此次飞行中采集的信号数据为背景干扰的测量数据；在所述待测天线附近位置放置基准天线，启动所述基准天线，经所述基准天线发射所述测试频段的线性扫频信号，按照所述最优测量飞行轨迹执行所述无人机的第三次飞行，其中，此次飞行中采集的信号数据为所述基准天线的测量数据。
- 根据权利要求1所述的基于无人机的室外天线四维方向图测量方法，其特征在于，所述经所述地面数据处理单元转换所述GPS位置数据为相对所述天线相位中心的球坐标下的采样位置，包括：将所述GPS位置数据中GPS坐标转化为地心空间直角坐标系的坐标；将所述地心空间直角坐标转化为以所述天线相位中心为原点的当地直角坐标；将所述当地直角坐标转化为以所述天线相位中心为原点的球坐标系的球坐标，所述球坐标作为采样位置。
- 根据权利要求4所述的基于无人机的室外天线四维方向图测量方法，其特征在于，经所述地面数据处理单元处理所述信号数据得到与所述待测天线的测量数据对应的原始数据、与所述基准天线的测量数据对应的基准数据和与所述背景干扰的测量数据对应的干扰数据。
- 根据权利要求6所述的基于无人机的室外天线四维方向图测量 方法，其特征在于，所述经所述地面数据处理单元修正所述原始数据和所述基准数据，包括：以下式剔除所述原始数据和所述基准数据中的干扰数据：
式中，R′ t(ζ,i),σ(ζ,i),R′ b(ζ,i)为第i个采样位置，频点为ζ的三个接收信号强度且单位为dBm，所述三个接收信号强度依次为所述原始数据R′ t(ζ,i)、所述干扰数据σ(ζ,i)和所述基准数据R′ b(ζ,i)，为消除所述背景干扰后的第i个采样位置，频点为ζ的两个接收信号强度且单位为dBm，所述两个接收信号强度依次为消除所述背景干扰后的原始数据和消除所述背景干扰后的基准数据。
- 根据权利要求7所述的基于无人机的室外天线四维方向图测量方法，其特征在于，所述经所述地面数据处理单元修正所述原始数据和所述基准数据，还包括：以下式对消除所述背景干扰后的原始数据和消除所述背景干扰后的基准数据分别进行归一化：
式中，m为采样位置总数且为正整数，表示第i个 采样位置，频点为ζ的两个归一化信号强度，所述两个归一化信号强度依次为消除所述背景干扰后和归一化处理后的原始数据、消除所述背景干扰后和归一化处理后的基准数据。
- 根据权利要求8所述的基于无人机的室外天线四维方向图测量方法，其特征在于，所述通过修正后的基准数据标定修正后的原始数据，获得离散方向图数据，包括：以下式利用消除所述背景干扰后和归一化处理后的基准数据对消除所述背景干扰后和归一化处理后的原始数据进行标定，获得离散方向图数据：
式中，为与所述基准天线的标准天线方向图对应的第i个采样位置，频点为ζ的归一化信号强度，R t(ζ,i)为与所述待测天线的空间频率离散方向图对应的第i个采样位置，频点为ζ的归一化信号强度，R t(ζ,i)作为离散方向图数据。
- 根据权利要求9所述的基于无人机的室外天线四维方向图测量方法，其特征在于，经深度神经网络对所述离散方向图数据进行内插补全，其中，所述深度神经网络为两个深度神经网络A(n|c；θ a)和B(d|c；θ b)经若干次迭代训练后的A(n|c；θ a)，n为服从标准高斯分布p n(n)的随机变量，c为用于训练的空间频 率离散方向图数据且该空间频率离散方向图数据的分布为p data(c)，d为网络A(n|c；θ a)的输出或用于训练的连续方向图数据且该连续方向图数据的分布为p data(d)，θ a和θ b为用于经代价函数迭代的优化参数。
- 一种基于无人机的室外天线四维方向图测量装置，其特征在于，该测量装置包括：测量路径规划单元，用于基于待测天线的用户输入信息，计算无人机的飞行轨迹；无人机平台单元，用于基于所述飞行轨迹控制所述无人机的飞行以及还用于采集GPS位置数据；辐射信号采集单元，用于接收待测天线和基准天线在各个开关状态下发射的信号；数据指令处理单元，用于基于接收的信号调整所述无人机的飞行以使得所述无人机的定向天线指向天线相位中心以及还用于采集信号数据；地面数据处理单元，用于转换所述GPS位置数据为球坐标系下的采样位置，并将采集的信号数据处理为所述待测天线的原始数据和基准天线的基准数据，以及还用于基于所述原始数据和所述基准数据，获得空间频率四维方向图数据；所述测量路径规划单元、辐射信号采集单元和数据指令处理单元通过吊舱悬挂于无人机平台单元。
- 根据权利要求11所述的基于无人机的室外天线四维方向图测量装置，其特征在于，所述测量路径规划单元包括用户输入模块、路径计算模块和控制指令模块；所述用户输入模块，用于获得用户输入信息；所述路径计算模块，用于基于所述用户输入信息，计算无人机的最优测量飞行轨迹和各个时刻的姿态指向，所述控制指令模块，用于将所述最优测量飞行轨迹及所述姿态指向形成姿态指令。
- 根据权利要求12所述的基于无人机的室外天线四维方向图测量装置，其特征在于，所述无人机平台单元包括GPS模块、飞行控制模块和云台控制模块；所述数据指令处理单元包括速度调节模块和数据发送模块；所述数据发送模块用于将所述GPS模块采集到的实时的GPS位置数据、所述辐射信号采集单元接收的信号的解调数据封装成数据帧，通过无线链路发送给所述地面数据处理单元；所述云台控制模块用于接收所述姿态指令，同时所述速度调节模块接收所述最优测量飞行轨迹；所述飞行控制模块用于接收由所述速度调节模块基于所述辐射信号采集单元发送的信号强度所形成的速度指令；所述飞行控制模块用于基于实时接收的速度指令，控制所述无人机的飞行速度和方向；所述云台控制模块用于基于所述GPS模块1-9发送的GPS位置数据和所述姿态指令实时控制所述无人机机载的定向天线的姿态或方向；所述辐射信号采集单元包括所述定向天线和宽带信号接收机，所述宽带信号接收机用于解调所述定向天线接收的信号。
- 根据权利要求13所述的基于无人机的室外天线四维方向图测量装置，其特征在于，所述地面数据处理单元包括数据接收模块、数据处理模块、数据修正模块和方向图生成模块；所述数据处理模块用于通过所述数据接收模块接收所述数据发送模块发送的具有信号数据和GPS位置数据的信号；所述数据处理模块对所述数据发送模块发送的信号进行信号解调、解调的数据经坐标转化并传递给所述数据修正模块；所述数据修正模块进行背景干扰消除和数据标定后传递给所述方向图生成模块；所述方向图生成模块计算所述待测天线的E面和H面的天线方向图数据，并基于所述E面和H面的天线方向图数据，重构出空间频率四维天线方向图数据。
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| CN114184852A (zh) * | 2021-11-30 | 2022-03-15 | 南京理工大学 | 一种基于空中平台的天线方向图主被动复合式测量系统 |
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| CN114184852A (zh) * | 2021-11-30 | 2022-03-15 | 南京理工大学 | 一种基于空中平台的天线方向图主被动复合式测量系统 |
| CN114756045A (zh) * | 2022-05-18 | 2022-07-15 | 电子科技大学 | 一种用于气象雷达标定的无人机控制方法 |
| CN116527169A (zh) * | 2023-04-28 | 2023-08-01 | 哈尔滨工程大学 | 一种低人口密度区域无线信号强度检测系统及方法 |
| CN116527169B (zh) * | 2023-04-28 | 2024-02-02 | 哈尔滨工程大学 | 一种低人口密度区域无线信号强度检测系统及方法 |
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