Unmanned aerial vehicle-based ground object scattering measurement system and method

Abstract

This invention discloses a UAV-based ground object scattering measurement system, comprising an aerial measurement system, a communication conversion module, and a ground radio frequency system. The aerial measurement system transmits radio frequency signals and receives echo signals; the communication conversion module converts signal types; and the ground radio frequency system generates radio frequency signals and processes echo signals. The invention also discloses a measurement method for this system. First, equipment is selected and interconnected according to the measurement target; then, UAV control and SAR imaging programs are written; finally, scattering measurements are performed and the results are analyzed. This invention's UAV-based ground object scattering measurement system has low construction costs, can process measurement data in real time, and its aerial measurement system is simple in structure, highly flexible, and can be dynamically adjusted according to the measurement task.

Description

Technical Field

[0001] This invention belongs to the field of electromagnetic scattering measurement technology, specifically relating to a ground object scattering measurement system based on an unmanned aerial vehicle (UAV), and also to a measurement method for the ground object scattering measurement system. Background Technology

[0002] Electromagnetic scattering measurement technology is an important means of studying the radar characteristics of targets. Conducting external electromagnetic scattering measurements has significant strategic importance. The key to external electromagnetic scattering measurements lies in the construction of the external electromagnetic scattering system. Conventional measurement systems are divided into shore-based measurement platforms and airborne measurement platforms. Among them, airborne measurement platforms can conduct ground observations and measure radar characteristics such as the scattering coefficient, one-dimensional image, and two-dimensional image of ground targets. They offer flexible testing and a large testing range. However, using airborne platforms for scattering measurements is costly and requires the mobilization of a large amount of measurement resources, which is unaffordable for conventional research institutions.

[0003] In recent years, with the rise of the drone industry, more and more high-payload and high-stability drones have emerged. Using drones for field scattering measurement has become a feasible solution, but there are very few related testing methods, and there is still a gap in how to use drones to achieve ground object scattering measurement. Summary of the Invention

[0004] The purpose of this invention is to provide a ground object scattering measurement system based on unmanned aerial vehicles (UAVs), which solves the problems of high cost, inability to process measurement data in real time, and inability to make timely dynamic adjustments of airborne measurement platforms in existing technologies.

[0005] Another object of the present invention is to provide a measurement method for the ground object scattering measurement system.

[0006] The technical solution adopted in this invention is a ground object scattering measurement system based on UAV, including an aerial measurement system, a communication conversion module, and a ground radio frequency system. The aerial measurement system is used to transmit radio frequency signals and receive echo signals; the communication conversion module is used to convert signal types; and the ground radio frequency system is used to generate radio frequency signals and process echo signals.

[0007] Another technical solution adopted in this invention is a ground object scattering measurement method based on UAVs, which is executed on a UAV-based ground object scattering measurement system, specifically implemented according to the following steps:

[0008] Step 1: Determine the measurement target;

[0009] Step 2: Equipment preparation, including selecting the appropriate equipment based on the measurement target and calibrating the vector network analyzer;

[0010] Step 3: Device interconnection, including connecting the operating computer to the vector network analyzer and the measurement system signal link connection;

[0011] Step 4: Write the UAV control program according to the measurement task, including the UAV trajectory flight control program and the gimbal control program;

[0012] Step 5: Write the SAR imaging program;

[0013] Step 6: Perform scattering measurements to obtain the initial measurement results;

[0014] Step 7: Repeat step 6 to obtain the final measurement result;

[0015] Step 8: Analyze the final measurement results.

[0016] The invention is further characterized in that,

[0017] The aerial measurement system includes a drone, which is equipped with a gimbal, a power amplifier, a transmitting antenna, and a receiving antenna.

[0018] The communication conversion module includes two sets of RF-fiber optic signal converters and fiber optic-RF signal converters connected by optical fibers. The RF-fiber optic signal converters include RF-fiber optic signal converter I and RF-fiber optic signal converter II, with RF-fiber optic signal converter I connected to a receiving antenna. The fiber optic-RF signal converters include fiber optic-RF signal converter I and fiber optic-RF signal converter II, with fiber optic-RF signal converter II connected sequentially to a power amplifier and a transmitting antenna. RF-fiber optic signal converters I and II are mounted on a pan-tilt unit, while RF-fiber optic signal converters II and fiber optic-RF signal converter I are mounted on the ground.

[0019] The ground-based radio frequency system includes a vector network analyzer and a low-noise amplifier. The output of the vector network analyzer is connected to an RF-to-fiber optic signal converter II, and the input of the vector network analyzer is connected in sequence to the low-noise amplifier and the fiber optic-to-RF signal converter I. The vector network analyzer is also connected to a power bank and an operating computer. The ground-based radio frequency system also includes UAV flight monitoring.

[0020] The specific steps for calibrating the vector network analyzer in step 2 are as follows:

[0021] Step 2-1b: Select the calibration kit according to the measurement cable specifications;

[0022] Step 2-2b: Set the calibration type to full 2-port calibration;

[0023] Step 2-3b: Connect one end of the measurement cable to test port 1 and the other end to the open circuit standard. Measure the open circuit calibration data at test port 1. The selected mark will be displayed on the left side of the "Port 1 Open" menu.

[0024] Step 2-4b: Using the same method as in step 2-3b, measure the short-circuit calibration data and load calibration data at test port 1;

[0025] Step 2-5b: Using the same method as in step 2-3b, measure the open-circuit calibration data, short-circuit calibration data, and load calibration data at test port 2;

[0026] Step 2-6b: Connect test port 1 and test port 2 and perform the calibration action. This completes the calibration of the vector network analyzer.

[0027] The specific steps for operating the computer-connected vector network analyzer in step 3 are as follows:

[0028] Step 3-1: Install Keysight IO Library Suite and Keysight Command Expert, and install the corresponding MATLAB library. Connect the network cable, set the IP address of the operating computer to be on the same subnet as the vector network analyzer, and use the ping command to check its connectivity.

[0029] Step 3-2: Use Keysight Command Expert to check if the connection is successful. After confirming a successful connection, begin Visa programming. The programming includes: clearing the port and then setting the measurement mode to NA, setting the measurement result to S21, and setting the start frequency, cutoff frequency, and number of sampling points to the input values ​​of the operating computer. At this point, the vector network analyzer settings are complete, and measurements can begin based on these settings.

[0030] The specific writing process for the UAV trajectory flight control program in step 4 is as follows:

[0031] Step 4-1a: Based on the UAV's preset flight path, break down the flight mission and determine the UAV waypoints in the path, the flight maneuvers corresponding to each waypoint, and the flight speed between waypoints.

[0032] Step 4-2a: Connect the operating computer and the drone to achieve real-time communication;

[0033] Step 4-3a: Set the waypoint mission information for the UAV, including mission ID, number of waypoints, number of mission repetitions, and actions after the waypoints are completed;

[0034] Step 4-4a: Set the waypoint information for the UAV, including basic parameters and optional parameters. Basic parameters include waypoint coordinates, waypoint type, heading type, and flight speed. Optional parameters include buffer distance, heading angle, turning mode, point of interest, maximum flight speed at a single point, and cruise speed at a single point.

[0035] Steps 4-5a: Set up new actions based on whether there are custom action requirements, and then set the waypoint action information of the UAV, including action ID, trigger and actuator;

[0036] Step 4-6a: Upload the waypoint mission information, waypoint information, and waypoint action information corresponding to steps 4-3a, 4-4a, and 4-5a to the UAV. After successful upload, you can obtain the UAV's real-time flight information and control and adjust the waypoint mission in real time through the designated interface.

[0037] The specific writing process for the gimbal control program in step 4 is as follows:

[0038] Step 4-1b: Initialize the PTZ control function module, including calling the PTZ control function class and creating a control object. After creating and specifying the control object, the PTZ status information can be obtained.

[0039] Step 4-2b: Control the gimbal's attitude through the interface specified in the Gimbal Manager Sync Sample, including three-axis absolute angles, rotation mode, and rotation speed. The three-axis absolute angles include the roll axis absolute angle, pitch axis absolute angle, and yaw axis absolute angle.

[0040] Step 4-3b: After the task is completed, choose whether to restore the gimbal as needed.

[0041] The specific writing process for the SAR imaging program in step 5 is as follows:

[0042] Step 5-1: Import raw echo data;

[0043] Step 5-2: Perform range compression on the original echo data based on the principle of matched filtering;

[0044] Step 5-3: Based on the stationary phase method, perform range migration correction using Fourier time-frequency transform of the orientation position and sinc interpolation;

[0045] Step 5-4: After the range migration correction is completed, further directional compression is performed based on the matched filtering principle, and then the directional Fourier time-frequency transform is performed to obtain the SAR imaging result.

[0046] Step 5-5: Output SAR imaging results and draw SAR imaging map.

[0047] The beneficial effects of this invention are:

[0048] (1) The present invention has built a complete ground object scattering measurement system based on UAVs. It can collect and accurately identify measurement targets, and the testing is flexible and low-cost, providing a way of thinking for the development of ground object scattering measurement in large-scale scenarios.

[0049] (2) The measurement system of the present invention adopts a communication conversion module, including two sets of radio frequency to fiber optic signal converters and fiber optic to radio frequency signal converters connected by optical fibers. By converting the optical fiber / radio frequency signal, the problem of excessive line loss of the radio frequency line in this application scenario is solved. At the same time, the optical fiber is lighter and can make the aerial measurement system more stable in flight.

[0050] (3) The measurement system of the present invention includes UAV flight control and gimbal control, which can adjust the measurement angle of the receiving or transmitting antenna by controlling the gimbal to meet the measurement requirements based on the automatic flight measurement of the UAV.

[0051] (4) The measurement system of the present invention can process measurement data in real time, and the aerial measurement system based on UAV has a simple structure and high flexibility, and can be dynamically adjusted in a timely manner according to the measurement task. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the structure of the ground object scattering measurement system based on UAV of the present invention;

[0053] Figure 2 This is a control flowchart of the ground object scattering measurement method based on UAV of the present invention;

[0054] Figure 3 This is a flowchart of the UAV trajectory control process in the UAV-based ground object scattering measurement method of the present invention;

[0055] Figure 4 This is a flowchart of the gimbal control process in the UAV-based ground object scattering measurement method of the present invention;

[0056] Figure 5 This is a schematic diagram of a SAR imaging measurement scenario for the UAV-based ground object scattering measurement method of the present invention;

[0057] Figure 6 This is a schematic diagram of the echo signal in the SAR imaging signal processing method of the UAV-based ground object scattering measurement method of the present invention;

[0058] Figure 7 This is a schematic diagram of the range compression result in the SAR imaging signal processing method of the UAV-based ground object scattering measurement method of the present invention;

[0059] Figure 8This is a schematic diagram of the range migration correction result in the SAR imaging signal processing method of the UAV-based ground object scattering measurement method of the present invention;

[0060] Figure 9 This is a schematic diagram of the directional position compression result in the SAR imaging signal processing method of the UAV-based ground object scattering measurement method of the present invention;

[0061] Figure 10 This is a flowchart of the SAR imaging program for the UAV-based ground object scattering measurement method of the present invention;

[0062] Figure 11 This is the one-dimensional distance image result of the midpoint group in Embodiment 1 of the present invention;

[0063] Figure 12 This is the midpoint group SAR imaging result of Embodiment 1 of the present invention;

[0064] Figure 13 This is the one-dimensional distance image result of the endpoint group in Embodiment 1 of the present invention;

[0065] Figure 14 This is the endpoint group SAR imaging result of Embodiment 1 of the present invention.

[0066] In the diagram: 1. UAV, 2. Gimbal, 3. Receiving antenna, 4. RF-to-fiber optic signal converter I, 5. Fiber optic-to-RF signal converter I, 6. Low-noise amplifier, 7. Vector network analyzer, 8. RF-to-fiber optic signal converter II, 9. Fiber optic-to-RF signal converter II, 10. Power amplifier, 11. Transmitting antenna, 12. Measurement target, 13. Power bank, 14. Operating computer, 15. UAV flight monitoring. Detailed Implementation

[0067] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0068] The structure of a UAV-based ground object scattering measurement system is as follows: Figure 1 It includes an airborne measurement system, a communication conversion module, and a ground radio frequency system.

[0069] The aerial measurement system is used to transmit radio frequency signals and receive echo signals, including a drone 1, a gimbal 2 mounted on the drone 1, and a power amplifier 10, a transmitting antenna 11, and a receiving antenna 3 mounted on the gimbal 2.

[0070] Because conventional RF lines have a high line loss of 3.7 dB / m at the measurement frequency of the measurement system of this invention, which is far from meeting the requirements for field testing using UAVs, this invention constructs a communication conversion module to reduce the line loss of ground-to-air communication. Measurements show that the line loss of the 35m optical fiber used in the measurement system of this invention is within 8 dB, meeting the requirement of less than 10 dB loss for field scattering measurements. The communication conversion module includes two sets of RF-fiber optic signal converters and fiber optic-RF signal converters connected by optical fibers. The RF-fiber optic signal converters can convert the input RF signal into an optical signal and output it, while the fiber optic-RF signal converters can convert the input optical signal into an RF signal and output it.

[0071] The radio frequency to fiber optic signal converter includes radio frequency to fiber optic signal converter I4 and radio frequency to fiber optic signal converter II8. Radio frequency to fiber optic signal converter I4 is connected to receiving antenna 3. The fiber optic to radio frequency signal converter includes fiber optic to radio frequency signal converter I5 and fiber optic to radio frequency signal converter II9. Fiber optic to radio frequency signal converter II9 is ​​connected to power amplifier 10 and transmitting antenna 11 in sequence. Among them, radio frequency to fiber optic signal converter I4 and fiber optic to radio frequency signal converter II9 are set on pan-tilt unit 2, and radio frequency to fiber optic signal converter II8 and fiber optic to radio frequency signal converter I5 are set on the ground.

[0072] The ground-based radio frequency system is used to generate radio frequency signals and process echo signals. It includes a vector network analyzer 7 and a low-noise amplifier 6. The output of the vector network analyzer 7 is connected to a radio frequency to fiber optic signal converter II 8. The input of the vector network analyzer 7 is connected in sequence to the low-noise amplifier 6 and the fiber optic to radio frequency signal converter I 5. The vector network analyzer 7 is also connected to a mobile power supply 13 and an operating computer 14. The ground-based radio frequency system also includes a UAV flight monitoring system 15.

[0073] The UAV-based ground object scattering measurement method is executed on the aforementioned measurement system, specifically including the following steps:

[0074] Step 1: Determine the measurement target 12;

[0075] Step 2, Equipment Preparation, including selecting the appropriate equipment based on measurement target 12 and calibrating the vector network analyzer 7:

[0076] (1) Equipment selection

[0077] Step 2-1a: Select the corresponding measurement frequency according to the measurement target 12 in Step 1;

[0078] Step 2-2a: Select the corresponding model of transmitting antenna 11, receiving antenna 3, vector network analyzer 7, power amplifier 10, low noise amplifier 6, power bank 13, RF-fiber optic signal converter, and fiber optic-RF signal converter according to the measurement frequency in Step 1, and prepare the operating computer 14 to check the working status of the above equipment; in addition, considering the carrying capacity of UAV 1, the size and weight of power amplifier 10, RF-fiber optic signal converter, and fiber optic-RF signal converter should be as small as possible; to ensure the flexibility of the measurement system setup, portable power bank 13 and vector network analyzer 7 should be selected; the operating gain of power amplifier 10 and low noise amplifier 6 should meet the requirements.

[0079] Steps 2-3a: Select the appropriate weight-bearing drone 1 based on the weight of the equipment mounted on the gimbal 2.

[0080] (2) Calibrate the vector network analyzer

[0081] To improve the accuracy of the experiment, the vector network analyzer needs to be calibrated. The specific steps are as follows:

[0082] Step 2-1b: Select a calibration kit suitable for the measurement cable. This invention selects calibration kit 85032F.

[0083] "Cal" > "Cal Kit" > 85032F

[0084] Step 2-2b: Set the calibration type to full 2-port calibration.

[0085] Calibrate > Calibrate > 2-Port Cal > Select Ports1-1-2

[0086] Step 2-3b: Connect one end of the measurement cable to test port 1 and the other end to the open circuit standard. Measure the open circuit calibration data at test port 1. The selected mark will be displayed on the left side of the "Port 1 Open" menu.

[0087] "Cal" > "Calibrate" > "2-Port Cal" > "Reflection" > "Port1 Open"

[0088] Step 2-4b: Using the same method as in step 2-3b, measure the short-circuit calibration data and load calibration data at test port 1.

[0089] Step 2-5b: Using the same method as in step 2-3b, measure the open-circuit calibration data, short-circuit calibration data, and load calibration data at test port 2.

[0090] Step 2-6b: Connect test port 1 and test port 2 and perform the calibration action. This completes the calibration of the vector network analyzer 7.

[0091] Step 3, Device Interconnection, including the interconnection of the operating computer 14 with the vector network analyzer 7 and the measurement system signal link connection:

[0092] (1) Operating the computer 14 interconnected vector network analyzer 7

[0093] Step 3-1: Install Keysight IO Library Suite and Keysight Command Expert, and install the corresponding MATLAB library. Connect the network cable, set the IP address of the operating computer 14 to be on the same subnet as the vector network analyzer 7, and use the ping command to check its connectivity.

[0094] Step 3-2: Use Keysight Command Expert to check if the connection is successful. After confirming a successful connection, begin Visa programming. The programming includes: clearing the port and then setting the measurement mode to NA, setting the measurement result to S21, and setting the start frequency, cutoff frequency, and number of sampling points to the input values ​​of the operating computer 14. At this point, the vector network analyzer 7 is set up, and measurement begins based on this setup.

[0095] (2) Measurement system signal link connection

[0096] The control flow of the UAV-based ground object scattering measurement method of this invention is as follows: Figure 2 As shown, combined with Figure 1 As shown in the schematic diagram of the measurement system, the measurement system of this invention includes a transmitting signal link and a receiving signal link. The transmitting signal link is as follows: the vector network analyzer 7 is interconnected with the operating computer 14 via IP. The operating computer 14 sets radio frequency (RF) signal commands and sends them to the vector network analyzer 7. The vector network analyzer 7 generates an RF signal, which is converted into an optical signal by an RF-to-fiber optic signal converter II 8. This optical signal is then transmitted through an optical fiber to the airborne measurement system. The signal is then converted back into an RF signal by an optical fiber-to-RF signal converter II 9, amplified by a power amplifier 10, and transmitted by the transmitting antenna 11. The receiving signal link is as follows: the receiving antenna 3 receives the echo signal, converts it into an optical signal by an RF-to-fiber optic signal converter I 4, transmits it through an optical fiber to the ground-based RF system, converts it back into an RF signal by an optical fiber-to-RF signal converter I 5, amplified by a low-noise amplifier 6, and transmitted to the vector network analyzer 7. The operating computer 14 reads and processes the echo signal received by the vector network analyzer 7.

[0097] Step 4: Write the UAV control program according to the measurement task, including the UAV flight control program and the gimbal control program. After completion, conduct flight tests and adjust the parameters.

[0098] (1) The writing process of the UAV trajectory flight control program is as follows: Figure 3 As shown, the specific steps include:

[0099] Step 4-1a: Based on the preset flight path of UAV 1, the flight mission is broken down, and the UAV waypoints in the path, the flight actions corresponding to each waypoint, and the flight speed between waypoints are determined.

[0100] Step 4-2a: Connect the operating computer 14 and the drone 1 to achieve real-time communication.

[0101] Step 4-3a: Set the waypoint mission information for UAV 1, including mission ID, number of waypoints, number of mission repetitions, and actions after the waypoints are completed.

[0102] Step 4-4a: Set the waypoint information for UAV 1, including basic parameters and optional parameters. The basic parameters include waypoint coordinates, waypoint type, heading type, and flight speed. The optional parameters include buffer distance, heading angle, turning mode, point of interest, maximum flight speed at a single point, and cruise speed at a single point.

[0103] Steps 4-5a: Set up new actions based on whether there are custom action requirements, and then set the waypoint action information of UAV 1, including action ID, trigger and actuator.

[0104] Step 4-6a: Upload the waypoint mission information, waypoint information and waypoint action information corresponding to steps 4-3a, 4-4a and 4-5a to UAV 1. After successful upload, you can obtain the real-time flight information of the UAV and control and adjust the waypoint mission in real time through the specified interface.

[0105] (2) This invention controls the gimbal 2 to ensure that the receiving antenna 3 and the transmitting antenna 11 adjust their angles according to measurement needs. The gimbal control task programming flow is as follows: Figure 4 As shown, the specific steps include:

[0106] Step 4-1b: Initialize the PTZ control function module, including calling the PTZ control function class and creating a control object. After creating and specifying the control object, the status information of PTZ 2 can be obtained.

[0107] Step 4-2b: Control the attitude of gimbal 2 through the interface specified in Gimbal Manager Sync Sample, including the three-axis absolute angles, namely the roll axis absolute angle, pitch axis absolute angle, and yaw axis absolute angle; rotation mode; and rotation speed.

[0108] Step 4-3b: After the task is completed, select whether to restore the gimbal 2 as needed.

[0109] If the measurement task does not require adjustment of the angles of receiving antenna 3 and transmitting antenna 11, the above gimbal control process can be skipped.

[0110] Step 5: Write the SAR imaging program.

[0111] To further clarify the scattering measurement results, in addition to the direct measurement results and the one-dimensional range image, this invention also includes a SAR imaging program written on the operating computer 14 according to the measurement task. The SAR imaging of this invention utilizes two-dimensional matched filtering to obtain high-resolution images; this operation processes the obtained echo signals in both the range and azimuth directions.

[0112] The SAR imaging measurement scenario of this invention is as follows: Figure 5 As shown, the airborne measurement system moves along the positive x-axis to perform SAR imaging of the measurement target 12. At this time, the azimuth direction is the flight direction of the airborne measurement system, and the range direction is the antenna scanning direction. Where β is the antenna beamwidth, L... s To determine the composite aperture length, the straight-line distance between the target 12 and the aerial measurement system is r(t), and the perpendicular distance between the target 12 and the moving path of the aerial measurement system is the center distance R. c .

[0113] On the one hand, in imaging, to increase the signal bandwidth of a typical radar, a narrower pulse signal must be transmitted. However, narrow pulse signals have low energy and short range, making it difficult to balance range resolution and detection range. Therefore, range compression is needed to resolve the contradiction between high resolution and range in synthetic aperture radar. This is achieved by using a wide pulse to transmit the signal, configuring a matching filter at the receiver, and then using pulse compression technology to obtain a narrow pulse, thus achieving high range resolution. The specific method for pulse compression in the range direction is as follows:

[0114] During the measurement process, there is a radar motion equation:

[0115]

[0116] Among them, R c denoted as the center distance, v and t represent the forward speed and time of the aerial measurement system, and x0 represents the initial coordinates corresponding to the target position.

[0117] echo signal such as Figure 6 As shown, it can be represented as:

[0118]

[0119] Where f0 is the carrier frequency, R c τ is the center distance, τ is the azimuth time, and K is the echo frequency.

[0120] The result obtained after distance-direction pulse compression is as follows: Figure 7 As shown, it can be represented as:

[0121]

[0122] Where λ is the operating wavelength.

[0123] Using the stationary phase method, the time-frequency relationship in the azimuth direction can be obtained as follows:

[0124] f a =K a t (4)

[0125] Among them, f a K is the Doppler frequency. a This is the frequency modulation for the Doppler echo.

[0126] Combining equations (3) and (4), the distance migration expression can be expressed as:

[0127]

[0128] In this invention, sinc interpolation is used for distance migration correction, and the distance migration correction result is as follows: Figure 8 As shown.

[0129] On the other hand, since the azimuth resolution in a radar system depends on the effective beamwidth of the antenna, targets can only be distinguished when the directional distance between two targets is greater than the antenna beamwidth; otherwise, they cannot. Because the antenna beamwidth is limited, a point target continuously illuminated by the beam during measurement will be imaged as a line target. Therefore, pulse compression is also performed in the azimuth direction. The principle of azimuth pulse compression is the same as that of the range imaging method, but there is a difference in the Doppler frequency. The Doppler frequency in azimuth compression is:

[0130]

[0131] Using the Doppler frequency obtained from equation (6) instead of the directional echo frequency, the impulse response of the directional matched filter is as follows:

[0132] h a =f d *(-t) (7)

[0133] At this point, the result obtained by directional compression is as follows: Figure 9 As shown, it can be represented as:

[0134] s d (t,τ)=ifft(fft(h a ,Length)'.*fftshift(sr(t,τ))) (8)

[0135] Where fft and ifft are Fourier transform and negative Fourier transform, fftshift is zero-frequency centering, and Length is the number of synthetic aperture sampling points.

[0136] Based on the above principles, a SAR imaging program was written, and the specific process is as follows: Figure 10 As shown, the specific steps include:

[0137] Step 5-1: Import raw echo data.

[0138] Step 5-2: Perform range compression on the original echo data based on the principle of matched filtering.

[0139] Step 5-3: Based on the stationary phase method, perform range migration correction using Fourier time-frequency transform of the orientation position and sinc interpolation.

[0140] Step 5-4: After the range migration correction is completed, further directional compression is performed based on the matched filtering principle, and then the directional Fourier time-frequency transform is performed to obtain the SAR imaging result.

[0141] Step 5-5: Output SAR imaging results and draw SAR imaging map.

[0142] Step 6: Perform scattering measurements to obtain the initial measurement results.

[0143] Select appropriate parameters and use the established scattering measurement system. Place the measurement target 12, execute the program, and enable the UAV 1 to automatically fly and complete the measurement task, displaying the initial measurement results in real time on the operating computer 14. During the measurement process, observe the flight status and imaging results of the UAV 1 in real time. If any abnormality is found, manually stop the measurement and make adjustments through the UAV flight monitoring 15.

[0144] Step 7: Repeat step 6 to obtain the final measurement result.

[0145] To minimize the interference of random factors on the measurement results, after the measurement in step 6 is completed, save the data and repeat step 6 while keeping all parameters unchanged. Compare the two measurement results. If there is no significant difference between the two measurement results, it indicates that the influence of random factors is small. Save and export the second measurement result as the final measurement result. If a significant difference is found, perform multiple measurements until there is no significant difference between the two measurements. Save and export the last measurement result as the final measurement result.

[0146] Step 8: Analyze the final measurement results.

[0147] The one-dimensional range profile and SAR imaging results of the final measurement results are analyzed to observe whether the imaging results can complete the following tasks: (1) identify whether a target exists; (2) accurately identify the target location; if the above requirements are met, the measurement task ends here.

[0148] Example 1

[0149] In this embodiment, a corner reflector with a side length of 20cm is selected as the measurement target 12 for testing, and the specific steps include:

[0150] Step 1: Select a corner reflector with a side length of 20cm as the measurement target 12;

[0151] Step 2, Equipment Preparation, including selecting the appropriate equipment based on measurement target 12 and calibrating the vector network analyzer 7:

[0152] (1) Equipment selection

[0153] Step 2-1a: Based on the measurement of the size of target 12 in Step 1, select a measurement frequency of 18-26.5GHz;

[0154] Step 2-2a: Based on the measurement frequency in Step 1, select a high-frequency receiving antenna 3 (18-26.5GHz) and a transmitting antenna 11; select an Agilent N9951A handheld microwave vector network analyzer 7; considering that the power amplifier 10 needs to be mounted on the UAV 1, select a power amplifier 10 that is usable in the 18-40GHz range, with dimensions of 10cm*6cm*4cm and a gain of over 30dB, which meets the usage requirements; the RF-fiber optic signal converter and the fiber optic-RF signal converter are only 8cm wide, which also meets the mounting requirements; the low-noise amplifier 6 has no mounting requirements, and the low-noise amplifier 6 selected in this embodiment has a gain greater than 20dB and a VSWR less than 2dB, which meets the usage requirements; in addition, the mobile power supply in this embodiment has a voltage / power of 220V / 1000W and a battery capacity of 5550Wh, which can meet the voltage and power supply required for measurement; the operating computer is a Dell 7540 series workstation. After inspection, all the above instruments are working normally.

[0155] Steps 2-3a: Select a suitable drone 1 based on the weight of the equipment mounted on gimbal 2. Measurements show that the equipment mounted on gimbal 2 carries a total weight of 3 kg. Therefore, in this embodiment, a DJI M600 series drone is selected, which can ensure stable flight under this load and is equipped with a drone flight monitoring system 15 to control the drone's flight path and gimbal movements.

[0156] (2) Calibrate the vector network analyzer

[0157] To improve the accuracy of the experiment, the vector network analyzer needs to be calibrated. The specific steps are as follows:

[0158] Step 2-1b: Select a calibration kit suitable for the measurement cable. In this embodiment, calibration kit 85032F is selected.

[0159] "Cal" > "Cal Kit" > 85032F

[0160] Step 2-2b: Set the calibration type to full 2-port calibration.

[0161] Calibrate > Calibrate > 2-Port Cal > Select Ports1-1-2

[0162] Step 2-3b: Connect one end of the measurement cable to test port 1 and the other end to the open circuit standard. Measure the open circuit calibration data at test port 1. The selected mark will be displayed on the left side of the "Port 1 Open" menu.

[0163] "Cal" > "Calibrate" > "2-Port Cal" > "Reflection" > "Port1 Open"

[0164] Step 2-4b: Using the same method as in step 2-3b, measure the short-circuit calibration data and load calibration data at test port 1.

[0165] Step 2-5b: Using the same method as in step 2-3b, measure the open-circuit calibration data, short-circuit calibration data, and load calibration data at test port 2.

[0166] Step 2-6b: Connect test port 1 and test port 2 and perform the calibration action. This completes the calibration of the vector network analyzer 7.

[0167] Step 3, Device Interconnection, including the interconnection of the operating computer 14 with the vector network analyzer 7 and the measurement system signal link connection:

[0168] (1) Operating the computer 14 interconnected vector network analyzer 7

[0169] Step 3-1: Install Keysight IO Library Suite and Keysight Command Expert, and install the corresponding MATLAB library. Connect the network cable, set the IP address of the operating computer 14 to be on the same subnet as the vector network analyzer 7, and use the ping command to check its connectivity.

[0170] Step 3-2: Use Keysight Command Expert to check if the connection is successful. After confirming a successful connection, begin Visa programming. The programming includes: clearing the port and then setting the measurement mode to NA, setting the measurement result to S21, and setting the start frequency, cutoff frequency, and number of sampling points to the input values ​​of the operating computer 14. At this point, the vector network analyzer 7 is set up, and measurement begins based on this setup.

[0171] (2) Measurement system signal link connection

[0172] This invention relates to a UAV-based ground object scattering measurement system, comprising a transmitting signal link and a receiving signal link. The transmitting signal link is as follows: a vector network analyzer 7 is interconnected with an operating computer 14 via IP. Radio frequency (RF) signal commands are set on the operating computer 14 and sent to the vector network analyzer 7. The vector network analyzer 7 generates an RF signal, which is converted into an optical signal by an RF-to-fiber optic signal converter II 8. This optical signal is then transmitted through an optical fiber to the airborne measurement system. The signal is then converted back into an RF signal by an optical fiber-to-RF signal converter II 9, amplified by a power amplifier 10, and transmitted by the transmitting antenna 11. The receiving signal link is as follows: the receiving antenna 3 receives the echo signal, converts it into an optical signal by an RF-to-fiber optic signal converter I 4, transmits it through an optical fiber to the ground-based RF system, converts it back into an RF signal by an optical fiber-to-RF signal converter I 5, amplified by a low-noise amplifier 6, and transmitted to the vector network analyzer 7. The operating computer 14 reads and processes the echo signal received by the vector network analyzer 7.

[0173] Step 4: Write the UAV control program according to the measurement task, including the UAV flight control program and the gimbal control program. After completion, conduct flight tests and adjust the parameters until the requirements are met.

[0174] (1) The specific steps for writing the UAV trajectory flight control program are as follows:

[0175] Step 4-1a: Place corner reflector 12. According to the experimental requirements, plan the flight path of UAV 1 as a straight line with corner reflector 12 as the midpoint of the path, with a total length of 10m. Based on this, determine the starting point, midpoint, and ending point of the flight mission and define them as UAV waypoints in the program. Except for the starting point, the flight actions of the remaining waypoints are set to fly to the next waypoint and automatically land, with a flight speed of 2m / min. At this time, the lateral scanning distance of the antenna is 2m.

[0176] Step 4-2a: Connect the operating computer 14 and the drone 1 to achieve real-time communication.

[0177] Step 4-3a: Set the waypoint mission information for UAV 1, including mission ID, number of waypoints (3), do not repeat missions, and land on the spot after the waypoints are completed.

[0178] Step 4-4a: Set the waypoint information of UAV 1, that is, the information of the starting point, midpoint and ending point, including the waypoint coordinates recorded during pre-flight, the waypoint type is set to straight flight, the heading type is set to the next waypoint, the waypoint task is set to present, and the flight speed is confirmed during debugging.

[0179] Steps 4-5a: Since no new action is required, no new action will be defined here. That is, the midpoint flight action of UAV 1 is set to no action, and the endpoint flight action is set to automatic landing.

[0180] Step 4-6a: Upload the waypoint mission information, waypoint information and waypoint action information corresponding to steps 4-3a, 4-4a and 4-5a to UAV 1. After successful upload, you can obtain real-time flight information of UAV through the specified interface and control waypoint missions such as starting, stopping or pausing missions, or readjust the above parameters according to the actual situation.

[0181] (2) Based on the measurement task design of this embodiment, the angles of the receiving antenna 3 and the transmitting antenna 11 do not need to be adjusted for this flight mission. Measurement can be performed under the condition of gimbal centered, and there is no need to write gimbal control task program.

[0182] Step 5: Write the SAR imaging program, which includes the following steps:

[0183] Step 5-1: Import raw echo data.

[0184] Step 5-2: Perform range compression on the original echo data based on the principle of matched filtering.

[0185] Step 5-3: Based on the stationary phase method, perform range migration correction using Fourier time-frequency transform of the orientation position and sinc interpolation.

[0186] Step 5-4: After the range migration correction is completed, further directional compression is performed based on the matched filtering principle, and then the directional Fourier time-frequency transform is performed to obtain the SAR imaging result.

[0187] Step 5-5: Output SAR imaging results and draw SAR imaging map.

[0188] Step 6: Perform scattering measurements to obtain the initial measurement results.

[0189] Find an open, flat area to place the corner reflector 12, taking care to avoid interference from fiber optic cables and base stations. Set the start and stop frequencies to 18GHz and 26.5GHz, and the number of sampling points to 201 in the program, and start the operation. Following step 4-1a, set the flight path of the UAV 1 to a 10m straight line, placing the corner reflector 12 at the midpoint; at this point, the antenna scanning path is 2m. During the measurement process, the operating computer 14 will display the target radar one-dimensional image and SAR imaging results in real time. Monitor the radar image generation and UAV flight status in real time. After continuous adjustments, the final UAV flight speed is set to 0.15m / s, and the waypoint position is corrected, yielding the initial measurement results.

[0190] Step 7: Repeat step 6 to obtain the final measurement result.

[0191] To reduce the interference of accidental factors on the measurement results, after the measurement in step 6 is completed, the data is saved and step 6 is executed again while keeping all parameters unchanged to obtain the second measurement result. The second measurement result is compared with the first measurement result in step 6. The results are basically consistent, indicating that the experimental results are highly feasible. The second measurement result is saved and exported as the final measurement result of the midpoint group.

[0192] Step 8: Analyze the final measurement results.

[0193] In this embodiment, the one-dimensional range image results and SAR imaging results of the point group are as follows: Figure 11 , 12 As shown, the one-dimensional range image results reveal a peak value, indicating the presence of a target. SAR imaging clearly shows a strong scattering center along the path, and its azimuth position matches the direct measurement results, accurately identifying the presence and location of corner reflector 12. The measurement task is now complete.

[0194] To further verify the effectiveness of the measurement method of the present invention, this embodiment, while keeping the above measurement task parameters unchanged, only changes a certain parameter of the corner reflector 12, such as changing its placement position from the middle of the path to the end of the path, and repeats steps 4, 6, and 7 to obtain the final measurement results of the endpoint group. The one-dimensional range image results and SAR imaging results are as follows: Figure 13 ,14 As shown, comparing the one-dimensional range image measurement results of the midpoint group and the endpoint group reveals a peak value in the echo data, indicating the presence of a target. Comparing the two SAR imaging results, a strong scattering center is clearly visible along the path, and the azimuth positions of the midpoint and endpoint groups correspond to the positions of these strong scattering centers, respectively, located in the middle and end sections of the path. This indicates ideal imaging results and the ability to accurately identify the presence and location of the corner reflector target. In summary, these results demonstrate that the UAV-based ground object scattering measurement system and method of this invention can accurately identify the presence and location of the target 12.

Claims

1. An unmanned aerial vehicle based geophysical scatterometer system, characterized in that, The system comprises an aerial measurement system, a communication conversion module and a ground radio frequency system, the aerial measurement system is used for transmitting radio frequency signals and receiving echo signals, the communication conversion module is used for converting signal types, and the ground radio frequency system is used for generating radio frequency signals and processing echo signals. The aerial measurement system comprises a UAV (1), a gimbal (2) mounted on the UAV (1), a power amplifier (10), a transmitting antenna (11) and a receiving antenna (3) loaded on the gimbal (2). The communication conversion module comprises two groups of radio frequency-fiber signal converters and fiber-radio signal converters connected by optical fibers, the radio frequency-fiber signal converters comprise a radio frequency-fiber signal converter I (4) and a radio frequency-fiber signal converter II (8), the radio frequency-fiber signal converter I (4) is connected with the receiving antenna (3), the fiber-radio signal converters comprise a fiber-radio signal converter I (5) and a fiber-radio signal converter II (9), the fiber-radio signal converter II (9) is sequentially connected with the power amplifier (10) and the transmitting antenna (11), the radio frequency-fiber signal converter I (4) and the fiber-radio signal converter II (9) are arranged on the gimbal (2), and the radio frequency-fiber signal converter II (8) and the fiber-radio signal converter I (5) are arranged on the ground. The ground radio frequency system comprises a vector network analyzer (7) and a low-noise amplifier (6), an output end of the vector network analyzer (7) is connected with the radio frequency-fiber signal converter II (8), an input end of the vector network analyzer (7) is sequentially connected with the low-noise amplifier (6) and the fiber-radio signal converter I (5), the vector network analyzer (7) is further connected with a mobile power supply (13) and an operation computer (14), and the ground radio frequency system further comprises a UAV flight monitor (15).

2. The unmanned aerial vehicle based geophysical scatterometry method as claimed in claim 1, wherein, The system is implemented on the UAV-based ground object scatterometry system in claim 1 and specifically implemented according to the following steps. Step 1, determining a measurement target (12); Step 2, device preparation, comprising selecting a device according to the measurement target (12) and calibrating the vector network analyzer (7); Step 2-1b, selecting a calibration kit according to a measurement cable specification; Step 2-2b, setting a calibration type as full 2-port calibration; Step 2-3b, connecting one end of a measurement cable to test port 1 and the other end to an open circuit standard, measuring open circuit calibration data at the test port 1, and displaying a check mark on the left side of a "Port 1 Open" menu; Step 2-4b, using the same method as step 2-3b to measure short circuit calibration data and load calibration data at the test port 1; Step 2-5b, using the same method as step 2-3b to measure open circuit calibration data, short circuit calibration data and load calibration data at the test port 2; Step 2-6b, connecting the test port 1 and the test port 2 and performing a calibration action, thereby completing calibration of the vector network analyzer (7). Step 3, device interconnection, including operating computer (14) interconnection vector network analyzer (7) and measurement system signal link connection; Step 3-1, install Keysight IO library suite, Keysight Command Expert, and install corresponding matlab library, connect network cable, set the IP of operating computer (14) to make it in the same subnet as the vector network analyzer (7), use the ping command to detect and ensure its connectivity; Step 3-2, use Keysight Command Expert to detect whether the connection is successful, and start visa programming after confirming the successful connection; Programming content includes: emptying the port and setting the measurement mode to NA, setting the measurement result to S21, setting the start frequency, cutoff frequency, and sampling point number as the input value of operating computer (14); At this time, the vector network analyzer (7) is set, and the measurement is started on this basis; Step 4, write unmanned aerial vehicle control program according to measurement task, including unmanned aerial vehicle flight path control program and gimbal control program; The specific writing process of the unmanned aerial vehicle flight path control program is as follows: Step 4-1a, according to the preset flight path of the unmanned aerial vehicle (1), the flight task is split to determine the unmanned aerial vehicle waypoint in the path, the flight action corresponding to each waypoint and the flight speed between waypoints; Step 4-2a, connect operating computer (14) and unmanned aerial vehicle (1) to realize real-time communication; Step 4-3a, set the waypoint task information of unmanned aerial vehicle (1), including task ID, number of waypoints, task repetition times, and action after waypoint; Step 4-4a, set the waypoint information of unmanned aerial vehicle (1), including basic parameters and optional parameters, the basic parameters including waypoint coordinates, waypoint type, heading type and flight speed, the optional parameters including buffer distance, heading angle, steering mode, interest point, single point maximum flight speed, single point cruise speed; Step 4-5a, set new action according to whether there is a custom action requirement, and then set the waypoint action information of unmanned aerial vehicle (1), including action ID, trigger and actuator; Step 4-6a, upload the waypoint task information, waypoint information and waypoint action information corresponding to steps 4-3a, 4-4a and 4-5a to unmanned aerial vehicle (1), and after successful uploading, the real-time information of unmanned aerial vehicle flight can be obtained and real-time control can be adjusted through the specified interface waypoint task; The specific writing process of the gimbal control program is as follows: Step 4-1b, initialize the gimbal control function module, including calling the gimbal control function class and creating a control object, after creating and specifying the control object, the state information of the gimbal (2) can be obtained; Step 4-2b, control the attitude of the gimbal (2) through the interface specified in the Gimbal Manager Sync Sample, including three-axis absolute angle, rotation mode and rotation speed, the three-axis absolute angle including roll axis absolute angle, pitch axis absolute angle and yaw axis absolute angle; Step 4-3b, after completing the task, select whether to center the gimbal (2) according to the need. Step 5, write SAR imaging program; Step 5-1, import original echo data; Step 5-2, compress the original echo data in the distance direction based on the matched filter principle; Step 5-3, correct the distance migration based on the direction bit Fourier time-frequency transform and sinc interpolation on the basis of the stationary phase method; Step 5-4, after the distance migration correction is completed, first, further direction bit compression is carried out based on the matched filter principle, and then the direction bit Fourier time-frequency transform is carried out to obtain the SAR imaging result; Step 5-5, output the SAR imaging result and draw the SAR imaging graph; Step 6, carry out scattering measurement to obtain initial measurement result; Step 7, repeat step 6 to obtain final measurement result; Step 8, analyze the final measurement result.

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