Base station antenna pattern measuring device and method based on unmanned aerial vehicle attitude perception

Abstract

The invention discloses a base station antenna pattern measuring device and method based on unmanned aerial vehicle attitude perception, and belongs to the technical field of wireless communication and antenna test.The device comprises an unmanned aerial vehicle platform, a central processing module, a signal receiving and storing module, a carrying three-dimensional holder and sensing equipment, the sensing device comprises an RTK-GPS, an IMU and an electronic compass. At each measuring point, the deviation between the current angle and the expected angle of the holder is calculated in real time and serves as the input of a controller, a holder driving instruction is generated, and closed-loop control is achieved; and recording pose information of each measurement point, receiving a base station signal at each measurement point, and recording and storing an original signal so as to generate a base station antenna pattern. According to the invention, high-precision and automatic measurement of the base station antenna pattern is realized, and the on-network actual performance of the antenna can be accurately recovered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication and antenna testing, in particular to a base station antenna pattern measurement device and method based on unmanned aerial vehicle attitude sensing. BACKGROUND

[0002] Traditional manual or ground measurement methods cannot accurately determine the relative position and attitude of the measurement antenna and the base station antenna to be measured, resulting in large alignment errors and measurement results that cannot truly reflect the in-network pattern of the antenna.

[0003] Complex operation and low efficiency: the traditional method requires a large amount of manual intervention and repeated calibration at multiple measurement points, which is tedious and time-consuming, especially for base stations in complex terrain (such as rooftops and mountainous areas).

[0004] Dynamic disturbance has a large impact: when using an unmanned aerial vehicle as a platform, wind disturbance and body vibration during flight can cause the attitude of the unmanned aerial vehicle to change constantly, and if not compensated in real time, the pointing of the measurement antenna will continuously deviate from the target, resulting in distorted measurement data.

[0005] High risk of high-altitude operation: in the traditional method, manual tower climbing or high-altitude operation is required in some scenarios, which poses a high safety risk. SUMMARY

[0006] The present application aims to overcome the shortcomings of the prior art and provide a base station antenna pattern measurement device and method based on unmanned aerial vehicle attitude sensing.

[0007] The purpose of the present application is achieved by the following technical solution: a base station antenna pattern measurement device based on unmanned aerial vehicle attitude sensing, comprising: An unmanned aerial vehicle platform carrying a three-dimensional gimbal and a sensing device, and performing a flight path task; the three-dimensional gimbal carries a measurement antenna for receiving measurement signals during flight path operation, and the three-dimensional gimbal adjusts the azimuth and elevation angles according to gimbal driving instructions from a central processing module; the sensing device is used to accurately obtain the position and attitude of the unmanned aerial vehicle in three-dimensional space; A central processing module using an embedded computer for real-time data fusion, target vector calculation, gimbal driving instruction generation, and sending gimbal driving instructions to the three-dimensional gimbal to adjust the azimuth and elevation angles; A signal receiving and storing module for recording and storing the signals received by the measurement antenna to generate a base station antenna pattern.

[0008] A base station antenna pattern measurement method based on unmanned aerial vehicle attitude sensing, comprising the following steps: Step S1. Establish a local ENU coordinate system with the base station as the origin, and convert the RTK coordinates of the UAV to the position in the ENU coordinate system in real time ; Step S2. Take the actual phase center of the measurement antenna as the transmitting point, and calculate the unit vector pointing to the base station in the ENU coordinate system, i.e. the target direction in ENU ; Step S3. Convert the target direction in ENU to the body coordinate system FRD; Step S4. Convert to the two degrees of freedom of the gimbal, i.e. the azimuth and the pitch, and take the obtained azimuth and pitch as the expected angles of the gimbal; Step S5. At each measurement point, calculate the deviation between the current angle of the gimbal and the expected angle in real time, generate the driving instructions of the gimbal, and realize closed-loop control; Step S6. Record the pose information (i.e. the information output by the RTK-GPS, IMU and electronic compass) at each measurement point, receive the base station signal at each measurement point and store the original signal record, so as to generate the base station antenna pattern.

[0009] The beneficial effects of the present application are: extremely high alignment accuracy: by combining high-precision GPS / IMU data and active gimbal compensation algorithm, the influence of UAV attitude jitter on measurement accuracy is eliminated, and "pixel-level" alignment of the measurement antenna to the base station antenna is realized, and the measurement result is highly reliable.

[0010] Full automation and high efficiency: (1) Measurement process automation, only need to preset the flight route and base station information, can automatically complete the scanning measurement in all directions or specific angles, greatly improves the measurement efficiency, and the single station measurement time can be shortened from several hours to several tens of minutes.

[0011] (2) Realize the "restoration" of the antenna performance: due to the high measurement accuracy, the obtained data can accurately draw the pattern of the antenna in the actual installation environment, so as to "restore" its real coverage performance, and provide irrefutable data support for network optimization and fault diagnosis (such as antenna skew, reverse feed line, etc.).

[0012] (3) Strong safety and accessibility: no need for manual tower climbing, avoiding the risk of high-altitude operation, and some base stations that are difficult to reach by traditional methods can be easily measured, with wide application range. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 The flowchart of the method of the present application. DETAILED DESCRIPTION

[0014] The technical solutions of the present application will be described in further detail below with reference to the drawings, but the protection scope of the present application is not limited to the following description.

[0015] The base station antenna pattern measurement device based on unmanned aerial vehicle attitude perception comprises: An unmanned aerial vehicle platform carries a three-dimensional gimbal and a sensing device, and performs a flight path task; the three-dimensional gimbal carries a measurement antenna for receiving measurement signals during flight path flight, and the three-dimensional gimbal is used to adjust the azimuth angle and the pitch angle according to gimbal driving instructions from a central processing module; the sensing device is used to obtain the position and attitude of the unmanned aerial vehicle in three-dimensional space with high precision; The central processing module adopts an embedded computer, and is used for real-time data fusion, target vector calculation, gimbal driving instruction generation, and sending of gimbal driving instructions to the three-dimensional gimbal for adjustment of the azimuth angle and the pitch angle; The signal receiving and storing module is used for recording and storing the signals received by the measurement antenna, so as to generate a base station antenna pattern.

[0016] The sensing device comprises an RTK-GPS, an IMU and an electronic compass; The sensing device comprises an RTK-GPS, an IMU and an electronic compass; The RTK-GPS is used to obtain the positioning information of the unmanned aerial vehicle in three-dimensional space, including longitude, latitude and height; The IMU is used to provide the quaternion of the attitude information of the unmanned aerial vehicle and the angular velocity of the body; The electronic compass is used to provide the heading angle of the unmanned aerial vehicle.

[0017] As Figure 1 shown, the base station antenna pattern measurement method based on unmanned aerial vehicle attitude perception comprises the following steps: Step S1. Establishing a local ENU coordinate system with the base station as the origin, and converting the RTK coordinates of the unmanned aerial vehicle to the position in the ENU coordinate system in real time ; S101. Given the base station geodetic coordinates: , and the unmanned aerial vehicle RTK geodetic coordinates: ; wherein, respectively represent the longitude, latitude and elliptic height of the base station, respectively represent the longitude, latitude and elliptic height of the unmanned aerial vehicle; Under the given latitude , the calculation formula of the colure curvature radius is determined as follows: wherein, is the length of the long semi-axis of the earth, in meters. denotes the square of the first eccentricity, , denotes the flattening of the Earth as an ellipsoid, ; S102. The conversion formula of the base station geodetic coordinate system and the UAV RTK geodetic coordinate system to the ECEF coordinate system is given: refers to the coordinate obtained by conversion to the ECEF coordinate system; the ECEF coordinate system refers to the Earth-Centered Earth-Fixed rectangular coordinate system; When is taken , the obtained is the conversion result of the base station geodetic coordinate system to the ECEF coordinate system, denoted as ; When is taken , the obtained is the conversion result of the UAV RTK geodetic coordinate system to the ECEF coordinate system, denoted as ; S103. Convert the ECEF coordinate system to the local ENU coordinate system: Calculate the relative displacement of the UAV and the base station in the ECEF coordinate system : The rotation matrix of the base station ECEF coordinate system to the ENU coordinate system with the base station as the origin is: Calculate the position of the UAV in the ENU coordinate system with the base station as the origin : .

[0018] Step S2. Take the actual phase center of the measurement antenna as the transmission point, and calculate the unit vector pointing to the base station in the ENU coordinate system, that is, the target direction in ENU ; S201. Given the operator that converts the ENU coordinate system to the NED coordinate system : S202. Construct the rotation matrix of the NED coordinate system to the body coordinate system FRD from the UAV attitude quaternion : Calculate the rotation matrix of the ENU coordinate system to the body coordinate system FRD:​ S203. Compute the rotation matrix from the body frame FRD to ENU: S204. Compute the measured antenna position: Let the fixed offset of the RTK antenna relative to the measurement antenna in the body frame FRD be Convert it to the offset in the ENU frame : Compute the phase center position of the measurement antenna : S205. Compute the unit vector of the phase center of the measurement antenna pointing to the base station, with the base station as the origin , i.e. the target direction: where is the negation of : .

[0019] Step S3. Convert the target direction in ENU to the body frame FRD; Send the target direction into the body frame to get the target direction in the body-centered coordinate system : .

[0020] This step naturally offsets the pitch / roll / yaw of the body, so that the gimbal control only needs to face the target direction in the "machine body view".

[0021] Step S4. Convert to the two degrees of freedom of the gimbal, i.e. azimuth and pitch, and take the obtained azimuth and pitch as the expected angles of the gimbal; Compute the azimuth : The azimuth is the right turn angle relative to "machine head straight ahead" on the horizontal plane; atan2 automatically handles the quadrant; Compute the pitch : .

[0022] where the Down of the FRD coordinate system is positive, and the pitch angle "up is positive", so take .

[0023] In the embodiments of the present application, when the azimuth angle value is unstable, is locked as the last valid value, and only the pitch is controlled; if the gimbal coordinate definition is different from the FRD, the pitch angle is taken as negative or is processed in the installation calibration matrix.

[0024] Step S5. At each measurement point, the deviation of the current angle of the gimbal from the expected angle is calculated in real time, the gimbal driving instruction is generated, and closed-loop control is realized. S501. Error calculation and controller input: the deviation of the current angle of the gimbal from the expected angle is calculated in real time as the input of the controller, supporting stable tracking: Obtaining the expected gimbal angle, including: the expected azimuth angle , the expected pitch angle , unit: degree or radian; Obtaining the gimbal feedback, including the current actual azimuth angle , and the current actual pitch angle , which are obtained by real-time acquisition of the gimbal feedback; Obtaining attitude data: body angular velocity , which is obtained from the IMU, , unit: rad / s; Error solving: azimuth error ; pitch error ; In the embodiments of the present application, limiting processing is needed: the error is limited in [-180°, 180°] to avoid wrap-around, if |error|>threshold, an alarm log is triggered; S502. The central processor generates the gimbal driving instruction to realize closed-loop stability and dynamic compensation: In the embodiments of the present application, input preparation: the error and the angular velocity are packaged and sent to the controller, the cycle is 10-20 ms, matching the main loop frequency; wherein the controller refers to the algorithm module of the gimbal tracking control loop integrated in the central processor, including (PID or PI controller with angle error as input) and feedforward module (prediction compensation based on body angular velocity / angular acceleration) For the azimuth angle: the azimuth error is sent to the first PID controller, and the control signal output by the first PID controller; Calculate the feedforward compensation control signal of the azimuth angle: ; is the pre-calibration matrix; the feedforward azimuth compensation is based on ; Calculate the total control output of the azimuth angle: Utilizing generate a gimbal driving instruction to drive and control the gimbal; For the pitch angle: send the pitch error into a second PID controller, and output a control signal from the second PID controller ; calculate a feedforward compensation control signal of the pitch angle: ; the feedforward pitch compensation is based on ; calculate a total control output of the pitch angle: Utilizing generate a gimbal driving instruction to drive and control the gimbal.

[0025] In the embodiments of the present application, the PID calculation method is: , which is independently calculated for the azimuth and the pitch, respectively; Kp / Ki / Kd needs to be tuned, and the initial value is based on the gimbal specification; wherein is the deviation of the expected angle and the actual angle (when e takes the azimuth error , then is obtained, if e takes the pitch error , then is obtained, The initial value is set according to the gimbal specification (inertia, rated motor torque), and is iteratively tuned in actual test.

[0026] In the embodiments of the present application, frequency stratification is performed: the outer ring runs at 50-200 Hz in this step; the inner ring is built-in ≥500 Hz in the gimbal driver, to ensure high-frequency response; In the embodiments of the present application, the system first compares the expected gimbal angle with the actual feedback angle to obtain the errors in the azimuth and the pitch. Subsequently, the control module performs operation based on the errors to generate a driving instruction for the motor, and the control method is divided into two parts: PID control: through the proportional, integral and differential links, the instantaneous error is suppressed, the accumulated deviation is eliminated, and the dynamic oscillation is reduced, so as to realize basic tracking of the expected angle.

[0027] Feedforward compensation: the body angular velocity information is introduced at the same time, the offset caused by the disturbance of the unmanned aerial vehicle attitude is predicted in advance, and a compensation amount is added in the control instruction, so as to accelerate the response speed and improve the stability.

[0028] Finally, the PID output and the feedforward compensation are superimposed to form a total gimbal driving instruction, and are limited in amplitude when necessary to avoid motor overload. The whole process is run by the upper computer at a medium frequency, and the fine adjustment is completed by the high-speed current / speed ring inside the gimbal. This layered closed-loop control ensures dynamic response and stability.

[0029] In the embodiments of the present application, performance optimization can also be performed: monitoring error convergence time; if jitter is large, increasing Kalman filter smoothing , or adaptively adjusting PID parameters; Integration suggestion: use embedded computers to implement algorithms, support ROS node publishing / subscription; record control data; Safety mechanism: if RTK / IMU signal is lost, switch to open-loop mode, fix gimbal angle; when frequency < 50 Hz, degrade alarm; Test indicators: static tracking error < 0.5°, dynamic tracking error < 1° (dynamic); response delay < 20ms.

[0030] During system operation, control effect needs to be continuously optimized and monitored. The specific process includes: Performance observation: real-time monitoring of angle error and response process, if oscillation or slow convergence occurs, control parameters can be adjusted or filtering can be added to improve.

[0031] Data integration: all control quantities and error data are recorded and stored for subsequent analysis and parameter optimization.

[0032] Safety mechanism: once sensor data interruption or main control frequency anomaly is detected, the system will immediately switch to safety mode, keeping the gimbal at a stable angle to avoid the risk of losing control.

[0033] Through the above optimization and monitoring, the scheme can maintain stable work under actual flight disturbance and complex environment, and enter safety mode in time when an exception occurs, thereby ensuring the reliability of measurement data and the safety of system operation.

[0034] Step S6. Record the pose information of each measurement point (i.e. the information output by RTK-GPS, IMU and electronic compass), and receive base station signals at each measurement point and record and store the original signals to generate a base station antenna directional diagram.

[0035] The above description shows and describes one preferred embodiment of the present application, but as previously mentioned, it should be understood that the present application is not limited to the form disclosed herein, should not be considered as excluding other embodiments, and can be used in various other combinations, modifications and environments, and can be modified by the above teachings or related art or knowledge within the scope of the inventive concept described herein. Any modification and change made by those skilled in the art without departing from the spirit and scope of the present application shall be within the protection scope of the appended claims of the present application.

Claims

1. A base station antenna directional diagram measurement device based on unmanned aerial vehicle attitude perception, characterized in that: It comprises: An unmanned aerial vehicle platform, which is equipped with a three-dimensional gimbal and a sensing device, and performs a flight task along a route; the three-dimensional gimbal carries a measuring antenna, which is used for receiving a measuring signal during the flight along the route, and the three-dimensional gimbal is used for adjusting an azimuth angle and a pitch angle according to a gimbal driving instruction received from a central processing module; the sensing device is used for obtaining a position and an attitude of the unmanned aerial vehicle in a three-dimensional space with high precision; The central processing module is an embedded computer, which is used for real-time data fusion, target vector calculation, gimbal driving instruction generation, and sending of the gimbal driving instruction to the three-dimensional gimbal for adjusting the azimuth angle and the pitch angle; A signal receiving and storing module is used for recording and storing the signal received by the measuring antenna, so as to generate a base station antenna directional diagram.

2. The unmanned aerial vehicle attitude sensing based base station antenna directional diagram measurement apparatus according to claim 1, wherein: The sensing device comprises an RTK-GPS, an IMU, and an electronic compass; The RTK-GPS is used for obtaining positioning information of the unmanned aerial vehicle in the three-dimensional space, including a longitude, a latitude, and an altitude; The IMU is used for providing a quaternion of the attitude information of the unmanned aerial vehicle and an angular velocity of the body; The electronic compass is used for providing a heading angle of the unmanned aerial vehicle.

3. The method of measuring the base station antenna directional diagram based on the unmanned aerial vehicle attitude sensing, based on the device of any one of claims 1-2, characterized in that: The method comprises the following steps: Step S1. Establish a local ENU coordinate system with the base station as the origin, and convert the UAV RTK coordinates to the position in the ENU coordinate system in real time ; Step S2. Take the measured antenna actual phase center as the transmitting point, and calculate the unit vector pointing to the base station in the ENU coordinate system, i.e. the target direction in ENU ; Step S3. The target direction under the ENU is converted into the body coordinate system FRD. Turning to the body coordinate system FRD; Step S4. Convert the yaw angle and the pitch angle to two degrees of freedom of the gimbal, i.e. azimuth angle and elevation angle, and take the obtained azimuth angle and elevation angle as the expected angles of the gimbal. Convert the yaw angle and the pitch angle to two degrees of freedom of the gimbal, i.e. azimuth angle and elevation angle, and take the obtained azimuth angle and elevation angle as the expected angles of the gimbal. Step S5. At each measuring point, a deviation between a current angle of the gimbal and an expected angle is calculated in real time, a gimbal driving instruction is generated, and closed-loop control is realized; Step S6. Pose information of each measuring point, i.e. information output by the RTK-GPS, the IMU, and the electronic compass, is recorded, and a base station signal is received at each measuring point and recorded and stored as a raw signal, so as to generate a base station antenna directional diagram.

4. The method of claim 3, wherein the method further comprises: The step S1 comprises: S101. Given the base station geodetic coordinates: , and the UAV RTK geodetic coordinates: ; wherein, respectively represent the longitude, latitude and ellipsoidal height of the base station, respectively represent the longitude, latitude and ellipsoidal height of the UAV; At a given latitude The calculation formula of the meridian curvature radius is determined as follows The calculation formula of the meridian curvature radius is determined as follows wherein is the length of the major axis of the Earth, in meters; denotes the first eccentricity squared, , denotes the flattening of the Earth as an ellipsoid, ; S102. Conversion formulas from a base station geodetic coordinate system and an unmanned aerial vehicle RTK geodetic coordinate system to an ECEF coordinate system are given: refers to coordinates obtained by converting to the ECEF coordinate system; the ECEF coordinate system refers to the Earth-Centered, Earth-Fixed rectangular coordinate system; When Take , the resulting is the conversion result of the base station geodetic coordinate system to the ECEF coordinate system, denoted as ; When Take , the resulting is the conversion result of the UAV RTK geodetic coordinate system to the ECEF coordinate system, denoted as ; S103. The ECEF coordinate system is converted to a local ENU coordinate system: Computing relative displacement of a drone and a base station in an ECEF coordinate system : A rotation matrix for converting the base station ECEF coordinate system to an ENU coordinate system with the base station as the origin is: calculating the position of the drone in an ENU coordinate system with the base station as the origin : 。 5. The method of claim 3, wherein the method further comprises: The step S2 comprises: S201. Given an operator that converts ENU coordinate system to NED coordinate system : S202. By the drone attitude quaternion , construct a rotation matrix of the NED coordinate system to the body coordinate system FRD : A rotation matrix from the ENU coordinate system to a body coordinate system FRD is calculated: S203. A rotation matrix from the body coordinate system FRD to the ENU is calculated: S204. A position of the measuring antenna is calculated: Under the system FRD, the fixed offset of RTK antenna relative to the survey antenna , which is converted into the offset in the ENU coordinate system : Computing a phase center position of a measuring antenna : S205. Calculate the unit vector of the phase center of the measuring antenna pointing to the base station, with the base station as the origin i.e. the target direction: wherein is the negated result of 。 6. The method of claim 5, wherein the method further comprises: The step S3 comprises: Send the target direction into the body coordinate system, get the target direction that needs to point to in the body-centered coordinate system : 。 7. The method of claim 6, wherein the method further comprises: The step S4 comprises: Computing an azimuth angle : The azimuth angle is a right turning angle on a horizontal plane relative to "straight ahead"; atan2 automatically processes quadrants; Computing the pitch angle : 。 8. The method of claim 3, wherein the method further comprises: The step S5 comprises: S501. Error calculation and controller input: a deviation between a current angle of the gimbal and an expected angle is calculated in real time as an input of a controller, which supports stable tracking: An expected gimbal angle is obtained, comprising: desired azimuth angle , desired elevation angle , in degrees or radians; Obtaining gimbal feedback, including a current actual azimuth angle , and a current actual pitch angle , are obtained by real-time acquisition of gimbal feedback; Acquisition of attitude data: body angular velocity This data is acquired from the IMU, in rad / s; Error solution: Azimuth error ; Elevation error ; S502. The central processor generates a gimbal driving instruction, realizes closed-loop stability, and compensates dynamically: For the azimuth angle: The azimuth error is sent to a first PID controller, and a control signal is outputted by the first PID controller ; feedforward compensation control signal for the azimuth angle: ; is a pre-calibration matrix; the feedforward azimuth compensation is based on ; Total control output for calculating azimuth angle: Utilizing Generate a gimbal driving instruction to drive and control the gimbal. For the pitch angle: The pitch error is sent to a second PID controller, and a control signal is outputted by the second PID controller ; A feedforward compensation control signal for the pitch angle is calculated: ; the feedforward pitch compensation is based on ; Total control output for calculating the pitch angle: Utilizing Generate a gimbal driving instruction to drive and control the gimbal.

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