A method and system for pattern correction of an unmanned aerial vehicle antenna test

Abstract

The present invention provides a method and system for pattern correction of an unmanned aerial vehicle (UAV) antenna. The original test data of the antenna to be tested is obtained through a variety of flight trajectories and preprocessed to obtain the normalized amplitude value, the azimuth angle and the elevation angle in the spherical coordinate system corresponding to the measurement points. The positions of the target grid points to be interpolated are calculated according to different types of test data. Based on the inverse distance weighted interpolation algorithm, the amplitude value of the target point corresponding to the target grid point is calculated according to the obtained normalized amplitude value, the azimuth angle and the elevation angle in the spherical coordinate system corresponding to the measurement points, and the positions of the target grid points, so as to obtain the pattern of the antenna to be tested. The high-precision three-dimensional pattern is obtained by using discrete sampling points, which reduces the time required for testing parameters such as the high-precision three-dimensional pattern of the antenna to be tested, and improves the test efficiency and test effectiveness.

Description

Technical Field

[0001] The present invention belongs to the field of antenna pattern testing, and particularly relates to a method and system for pattern correction for unmanned aerial vehicle (UAV) antenna testing. Background Art

[0002] The statements in this part merely provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] During UAV antenna testing, a ground signal source provides an excitation signal for the antenna under test. This signal is radiated into space by the antenna under test. The signal receiving device and the on-board computer carried on the UAV collect radio frequency signals, and the measurement data is transmitted to the ground station through the data link transmission system. The antenna pointing has been corrected by adjusting the UAV attitude and the pan-tilt head pointing. After the test starts, the UAV flies along the planned route and continuously collects data. The ground station unit obtains the spatial position information and the collected data with time stamps in real time. Finally, after software processing and error correction, the pattern parameters of the antenna under test in the transmitting state are obtained. After the test is completed, a series of UAV position data with time information and measurement amplitude data with time information are obtained. The closest method in the existing methods is as follows: after corresponding the UAV position and the measurement data by time stamps, the one-dimensional antenna pattern is obtained by one-dimensional interpolation, and the elevation angle data is measured by equally spaced elevation angles, and the data is extended to three dimensions. However, in the existing pattern fitting processing method obtained from measurement data processing, due to the flight time limitation, the elevation angles usually have a large interval, which affects the final pattern display processing effect. Summary of the Invention

[0004] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a method for pattern correction for UAV antenna testing, which uses discrete sampling points to obtain a high-precision three-dimensional pattern, reduces the time required for testing parameters such as the high-precision three-dimensional pattern of the antenna under test, and improves the test efficiency and test effectiveness.

[0005] To achieve the above object, one or more embodiments of the present invention provide the following technical solutions: A method for pattern correction for UAV antenna testing, comprising the following steps:

[0006] Obtain the original test data of the antenna under test through various flight trajectories and perform preprocessing to obtain the normalized amplitude value, the azimuth angle, and the elevation angle in the spherical coordinate system corresponding to the measurement points;

[0007] Calculate the positions of the target grid points to be interpolated according to different types of test data;

[0008] Based on the inverse distance weighted interpolation algorithm, the amplitude value of the target point corresponding to the target grid point is calculated according to the obtained original test data and the azimuth angle, elevation angle, and target grid point position in the spherical coordinate system corresponding to the measurement point, and the radiation pattern of the antenna under test is obtained.

[0009] Further, the flight trajectory includes but is not limited to spherical spiral flight and multi-azimuth vertical semi-circular flight.

[0010] Further, the original test data includes the maximum value of the spectrum and the corresponding timestamp recorded during the measurement, the UAV position data and the corresponding timestamp obtained before the measurement, and the UAV position data and the corresponding timestamp obtained after the measurement;

[0011] According to the timestamp corresponding to the spectrum, the timestamp corresponding to the UAV position data obtained before the measurement, the timestamp corresponding to the UAV position data obtained after the measurement, the UAV position data obtained before the measurement, and the UAV position data obtained after the measurement, the amplitude coordinates are calculated by one-dimensional interpolation.

[0012] Further, before the inverse distance weighted interpolation operation, it also includes obtaining the normalized amplitude value and the corresponding spherical coordinate system position according to the radar equation, where the received energy is inversely proportional to the square of the distance under far-field conditions.

[0013] Further, the inverse distance weighted interpolation algorithm calculates the amplitude value of the target point corresponding to the target grid point according to the amplitude of the obtained original test data and the target grid point position, and the radiation pattern data specifically includes:

[0014] Converting the spherical amplitude data into three-dimensional amplitude data;

[0015] Converting the target grid point position into the target point position;

[0016] Selecting the n three-dimensional amplitude data points closest to the target position point;

[0017] Based on the inverse distance weighted interpolation algorithm and the n three-dimensional amplitude data points at the selected target position point, the amplitude value corresponding to each target point position is calculated.

[0018] Further, it also includes calculating the equivalent isotropic radiated power based on the input port power of the airborne receiver on the UAV side, the receiving cable loss, the distance between the transmitting and receiving antennas, and the test frequency for the obtained radiation pattern data.

[0019] Further, the gain is calculated according to the calculated equivalent isotropic radiated power, the transmit power, and the transmit cable attenuation.

[0020] The second aspect of the present invention provides a radiation pattern correction system for UAV antenna testing, including:

[0021] Data acquisition module: It is configured to obtain the original test data of the antenna to be tested through multiple flight trajectories and perform preprocessing to obtain the azimuth angle and elevation angle in the spherical coordinate system corresponding to the measurement points.

[0022] Data processing module, which is configured to calculate the positions of target grid points that need to be interpolated according to different types of test data.

[0023] Antenna pattern calculation module, which is configured to calculate the amplitude values of the target points corresponding to the target grid points based on the inverse distance weighted interpolation algorithm according to the obtained normalized amplitude values, the azimuth angle and elevation angle in the spherical coordinate system corresponding to the measurement points, and the positions of the target grid points, so as to obtain the pattern of the antenna to be tested.

[0024] The third aspect of the present invention provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps described in the above method are completed.

[0025] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and computer instructions stored on the memory and running on the processor. When the computer instructions are run by the processor, the steps described in the above method are completed.

[0026] The above one or more technical solutions have the following beneficial effects:

[0027] The pattern fitting and correction technology for UAV antenna testing used in the present invention utilizes discrete sampling points to obtain a high-precision three-dimensional pattern, and at the same time provides a specific method for directly calculating the gain through calibration data, reducing the time required for testing parameters such as the high-precision three-dimensional pattern of the antenna to be tested, and improving the test efficiency and test effectiveness.

[0028] The advantages of the additional aspects of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention.

[0030] Figure 1 It is a flowchart of a pattern correction method for UAV antenna testing according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] It should be noted that the following detailed description is exemplary and is intended to provide further illustration of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention pertains.

[0032] It should be noted that the terms used herein are merely for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention.

[0033] In the case of no conflict, the embodiments in the present invention and the features in the embodiments may be combined with each other.

[0034] Embodiment 1

[0035] As Figure 1 shown, this embodiment discloses a method for pattern correction of an antenna for unmanned aerial vehicle (UAV) testing, including the following steps:

[0036] Step 1: Obtain the original test data of the antenna to be tested through various flight trajectories and perform preprocessing to obtain the azimuth angle and elevation angle in the spherical coordinate system corresponding to the measurement points.

[0037] Step 2: Calculate the positions of the target grid points that need to be interpolated according to different types of test data.

[0038] Step 3: Based on the inverse distance weighted interpolation algorithm, calculate the amplitude value of the target point position corresponding to the target grid point according to the obtained original test data, the azimuth angle and elevation angle in the spherical coordinate system corresponding to the measurement points, and the positions of the target grid points, so as to obtain the pattern of the antenna to be tested.

[0039] Calculate the amplitude value of the target point position corresponding to the target grid point according to the position to obtain the pattern data.

[0040] In step 1 of this embodiment, the original test data is obtained through two three-dimensional flight modes, namely the multi-azimuth vertical semi-circular flight trajectory and the spherical spiral flight trajectory. During the flight test, the maximum value of the spectrum and the corresponding timestamp, the position of the UAV and the timestamp are recorded for a certain flight mode; when saving the test data, the maximum amplitude amp measured by the spectrum analyzer loaded on the UAV and the corresponding timestamp time_amp, the position data (x1, y1, z1) of the UAV obtained most recently before the measurement and the corresponding timestamp time_stamp1, and the position data (x2, y2, z2) of the UAV obtained most recently after the measurement and the corresponding timestamp time_stamp2 are recorded in the test data.

[0041] In this embodiment, the nearest before measurement: time_stamp1 is less than time_amp, and the difference between time_stamp1 and time_amp is the smallest; the nearest after measurement: time_stamp2 is greater than time_amp, and the difference between time_stamp2 and time_amp is the smallest.

[0042] In this embodiment, the spectrum analyzer measures the power amplitude at each frequency within a certain frequency range. When reading, it is in logarithmic format and in dB units. The maximum value of the power amplitude on the frequency-power amplitude (dB) curve is found and this value is recorded.

[0043] In this embodiment, after reading the measurement data, the exact position coordinates (x, y, z) during measurement are calculated by one-dimensional interpolation based on the time stamp time_amp, the time stamps time_stamp1 and time_stamp2, and the position data (x1, y1, z1), (x2, y2, z2).

[0044] The calculation method is as follows:

[0045] x = x1 + (x2 - x1) * (time_amp - time_stamp1) / (time_stamp2 - time_stamp1) (1)

[0047] y = y1 + (y2 - y1) * (time_amp - time_stamp1) / (time_stamp2 - time_stamp1) (2)

[0049] z = z1 + (z2 - z1) * (time_amp - time_stamp1) / (time_stamp2 - time_stamp1) (3)

[0051] In this embodiment, since the flight trajectory is generally spherical or cylindrical and the flight error of the drone is within 0.3 m, when the flight trajectory is spherical (radius R0), the data more than 0.3 meters away from the flight center point (x0, y0, z0) on the flight trajectory will be deleted as invalid data to remove the abnormal measurement data that may be collected during the takeoff and ending phases, that is The data points will be deleted as invalid data.

[0052] Since the jitter during the flight of the drone will cause measurement errors, in this embodiment, filtering is used to eliminate them. The median filtering and mean filtering are combined. A certain range of N + 2 points (N is the size of the filtering window) before and after the current position is selected, and the maximum amplitude point and the minimum point within the N + 2 points are removed. For example, when N = 9, when processing the 15th point, the 10th point to the 20th point are selected for processing. After removing the maximum amplitude point and the minimum amplitude point, the remaining amplitude points amp(n) are averaged to obtain amp_mean:

[0053]

[0054] Among them, the number of points n can be set and determined. Generally, 5 - 10 points are taken. N is the size of the filtering window, that is, when processing, the average is calculated using N points near the data.

[0055] In addition, due to the error in the position of the drone, the error caused by the change in the test distance needs to be compensated before interpolation. According to the radar equation, the received energy in the far - field condition is inversely proportional to the square of the distance, and the normalized amplitude value amp0 and the corresponding spherical coordinate positions theta, phi are obtained:

[0056]

[0057]

[0058] Among them, R is the distance from the measurement point to the antenna under test, atan2 is the arccosine function in matlab, which is used to calculate the radian. x, y, z are the accurate position coordinates obtained through one - dimensional interpolation.

[0059] In step 2 of this embodiment, the target range is calculated according to the measurement type. The measurement types are divided into two - dimensional data, one - dimensional horizontal circle, and one - dimensional vertical circle. For the one - dimensional horizontal circle, only one horizontal or vertical curve is selected. When two - dimensional data is selected, the maximum and minimum values of theta and phi are automatically calculated as the range to be interpolated, and the position of the grid points map(theta, phi) to be interpolated is calculated according to the interpolation interval input in the interface.

[0060] It can be understood that the interpolation interval is set manually. The two - dimensional matrix corresponding to the azimuth angle theta and the elevation angle phi can be obtained through meshgrid in matlab.

[0061] The array obtained by corresponding theta and phi at the same row and column positions of the two - dimensional matrix is map(theta, phi).

[0062] For example, if the theta list is 0, 1, 2; and the phi list is 3, 4; then the theta matrix is: 0 1 2 0 1 2

[0065] The phi matrix is as follows: 3 3 3 4 4 4

[0068] The map array is

[0069] (0, 3), (1, 3), (2, 3), (0, 4), (1, 4), (2, 4).

[0070] In step 3 of this embodiment, according to the normalized amplitude value of the original data obtained above, the azimuth angle in the spherical coordinate system corresponding to the measurement point, and the elevation angle array data(amp0, theta, phi) in the spherical coordinate system corresponding to the measurement point, calculate the amplitude value at the target grid point position map(theta, phi) that needs to be interpolated, which specifically includes:

[0071] Step 2-1: Convert the spherical coordinate system to a three-dimensional coordinate system

[0072] The IDW algorithm (inverse distance weighted interpolation algorithm) calculates the weight according to the distance between the interpolation point and the sample point. To avoid abnormal interpolation at the pole position, the calculation needs to be performed in the rectangular coordinate system. The spherical amplitude data data(amp0, theta, phi) will be converted to three-dimensional amplitude data data(tmpx, tmpy, tmpz, tmpamp):

[0073]

[0074] Convert the target grid point position map(theta, phi) to the target point position tar(tarx, tary, tarz):

[0075]

[0076] Step 2-2: Select valid points:

[0077] Valid points refer to the n three-dimensional amplitude data points closest to the target position tar(tarx, tary, tarz). n is determined according to the interface input value, and it is generally appropriate to be 50-200. The more points are selected, the smoother the finally generated radiation pattern will be.

[0078] Step 2-3: Perform interpolation using the IDW algorithm:

[0079] In the IDW algorithm, the distance attenuation factor is selected as 2. According to the IDW algorithm, the amplitude value taramp corresponding to the target point position is:

[0080]

[0081] By calculating the amplitude value taramp corresponding to each target position tar (tarx, tary, tarz) in sequence, the radiation pattern can be obtained.

[0082] In this embodiment, since it is difficult to move the antenna under test, it is difficult to use the method of measuring a standard gain antenna for comparative calculation of gain. To calculate the EIRP (Equivalent Isotropic Radiated Power) and gain, the airborne equipment at the UAV end needs to be the receiver. According to the test frequency, test distance, transmit power, transmit-end cable loss, receive-end cable loss, and airborne antenna gain, the EIRP and gain are calculated through formulas such as the radar equation.

[0083] The effective radiated power of the transmitting antenna EIRP = transmit power Ps - transmit cable attenuation L + transmit antenna gain Ga + power amplifier gain Gt;

[0084] Free space loss Ld = 32.45 + 20lgR + 20lgf, where R is the distance between the transmitting and receiving antennas, in meters; f is the test frequency, in Hz;

[0085] The power at the input port of the receiver Paut = EIRP - free space loss Ld + receive antenna gain Gaut;

[0086] The calculation of the power at the input port of the receiver Pr = Paut - receive cable loss La + low-noise amplifier gain GLNA.

[0087] According to the above calculation formulas for the effective radiated power of the transmitting antenna, free space loss, power at the input port of the receiver, and power at the input port of the receiver, without considering the power amplifier and low-noise amplifier, the EIRP can be calculated based on the power Pr at the input port of the receiver, receive cable loss La, distance R between the transmitting and receiving antennas, and test frequency f. Then, the gain can be calculated through the transmit power Ps, transmit cable attenuation L, and the calculated EIRP.

[0088] In this embodiment, measure the displayed value Prj of the receiver at the input power Pij of the metered signal source at this frequency, and the calibrated cable loss Lrj measured by the vector network analyzer to obtain the offset value Arz = (Pij - Lrj) - Prj at this frequency; calculate the power Pr at the input port of the calibrated receiver = Pi + Arz, where Pi is the amplitude value displayed by the receiver. Here, because the receiver data has been processed, take the taramp obtained in formula (9).

[0089] Then calculate the EIRP based on the power Pr at the input port of the receiver, receive cable loss La, distance R between the transmitting and receiving antennas, and test frequency f:

[0090] EIRP = Pr + La + 32.45 + 20lgR + 20lgf - Gaut(10)

[0091] Among them, Pr is the power at the input port of the calibrated receiver, La is the receiving cable loss, R is the distance between the transmitting and receiving antennas, f is the measurement frequency, and Gaut is the receiving antenna gain.

[0092] In this embodiment, the displayed value Psj of the transmitting power P of the transmitting source is measured by a metering power meter, and the cable loss Lsj during calibration measured by a vector network analyzer is used to obtain the offset value Asz = Psj - (P - Lrj) at this frequency; the calibrated transmitting power Ps = Ps1 + Asz is calculated.

[0093] According to the formula: transmitting antenna gain Ga = effective isotropic radiated power EIRP of the transmitting antenna - transmitting power Ps + transmitting cable attenuation L - power amplifier gain Gt, the transmitting antenna gain is calculated.

[0094] Embodiment 2

[0095] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above method are implemented.

[0096] Embodiment 3

[0097] The purpose of this embodiment is to provide a computer-readable storage medium.

[0098] A computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the above method are executed.

[0099] Embodiment 4

[0100] The purpose of this embodiment is to provide a pattern correction system for UAV antenna testing, including:

[0101] Data acquisition module: It is configured to obtain the original test data of the antenna under test through various flight modes and perform preprocessing to obtain the amplitude of the original test data;

[0102] Original test data processing module, which is configured to calculate the position of the target grid points that need to be interpolated according to the type of the tested data;

[0103] Pattern data calculation module, which is configured to calculate the amplitude value of the target point position corresponding to the target grid points based on the inverse distance weighted interpolation algorithm according to the amplitude of the obtained original test data and the position of the target grid points, and obtain the pattern data.

[0104] In the devices of the above Second, Third, and Fourth Embodiments, the steps involved correspond to those of the First Method Embodiment. For specific implementation manners, reference may be made to the relevant description part of the First Embodiment. The term "computer-readable storage medium" should be understood to include a single medium or multiple media containing one or more instruction sets; it should also be understood to include any medium that can store, encode, or carry an instruction set for execution by a processor and cause the processor to execute any method in the present invention.

[0105] Those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computer device. Optionally, they can be implemented by program codes executable by a computing device, so that they can be stored in a storage device for execution by the computing device, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0106] Although the specific implementation manners of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that, based on the technical solutions of the present invention, various modifications or deformations that can be made without creative efforts by those skilled in the art are still within the protection scope of the present invention.

Claims

1. A method for pattern correction of an unmanned aerial vehicle antenna, characterized in that, It includes the following steps: Obtain the original test data of the antenna to be measured through various flight trajectories and perform preprocessing to obtain the normalized amplitude value, azimuth angle, and elevation angle in the spherical coordinate system corresponding to the measurement points; Calculate the positions of the target grid points to be interpolated according to different types of test data; Based on the inverse distance weighted interpolation algorithm, calculate the amplitude values of the target points corresponding to the target grid points according to the obtained normalized amplitude value, azimuth angle, elevation angle, and target grid point positions in the spherical coordinate system corresponding to the measurement points, and obtain the radiation pattern of the antenna to be measured. Specifically, it includes: Convert the spherical amplitude data into three-dimensional amplitude data; Convert the target grid point positions into target point positions; Select the n three-dimensional amplitude data points closest to the target position point; Calculate the amplitude value corresponding to each target point position based on the inverse distance weighted interpolation algorithm and the n three-dimensional amplitude data points at the selected target position point.

2. The pattern correction method for UAV antenna testing according to claim 1, wherein The flight trajectories include, but are not limited to, spherical spiral flight and multi-azimuth vertical semi-circular flight.

3. A pattern correction method for UAV antenna testing according to claim 1, characterized in that, The original test data includes the maximum value of the spectrum recorded during measurement and the corresponding timestamp, the UAV position data obtained before measurement and the corresponding timestamp, and the UAV position data obtained after measurement and the corresponding timestamp; Calculate the amplitude coordinates by using one-dimensional interpolation according to the timestamp corresponding to the spectrum, the timestamp corresponding to the UAV position data obtained before measurement, the timestamp corresponding to the UAV position data obtained after measurement, the UAV position data obtained before measurement, and the UAV position data obtained after measurement.

4. A pattern correction method for UAV antenna testing according to claim 1, characterized in that, Before the inverse distance weighted interpolation operation, it also includes obtaining the normalized amplitude value and the corresponding spherical coordinate system position according to the radar equation, where the received energy under far-field conditions is inversely proportional to the square of the distance.

5. A pattern correction method for drone antenna testing according to claim 1, characterized in that It also includes calculating the equivalent isotropic radiated power based on the obtained radiation pattern data, the input port power of the on-board receiver at the UAV end, the receiving cable loss, the distance between the transmitting and receiving antennas, and the test frequency.

6. The method for pattern correction based on UAV antenna testing according to claim 5, characterized in that, Calculate the gain according to the calculated equivalent isotropic radiated power, transmit power, and transmit cable attenuation.

7. A pattern correction system for UAV antenna testing, characterized in that, It includes: Data acquisition module: It is configured to obtain the original test data of the antenna to be measured through various flight trajectories and perform preprocessing to obtain the normalized amplitude value, azimuth angle, and elevation angle in the spherical coordinate system corresponding to the measurement points; Data processing module, which is configured to calculate the positions of the target grid points to be interpolated according to different types of test data; Antenna radiation pattern calculation module, which is configured to calculate the amplitude values of the target points corresponding to the target grid points based on the inverse distance weighted interpolation algorithm according to the obtained normalized amplitude value, azimuth angle, elevation angle, and target grid point positions, and obtain the radiation pattern of the antenna to be measured. Specifically, it includes: Convert the spherical amplitude data into three-dimensional amplitude data; Convert the target grid point positions into target point positions; Select the n three-dimensional amplitude data points closest to the target position point; Calculate the amplitude value corresponding to each target point position based on the inverse distance weighted interpolation algorithm and the n three-dimensional amplitude data points at the selected target position point.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in a radiation pattern correction method for UAV antenna testing as described in any one of claims 1-6.

9. A processing device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in a pattern correction method for UAV antenna testing according to any one of claims 1-6.

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