WO2021031975A1 - 无人机航向确定方法、装置及无人机 - Google Patents

无人机航向确定方法、装置及无人机 Download PDF

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Publication number
WO2021031975A1
WO2021031975A1 PCT/CN2020/108929 CN2020108929W WO2021031975A1 WO 2021031975 A1 WO2021031975 A1 WO 2021031975A1 CN 2020108929 W CN2020108929 W CN 2020108929W WO 2021031975 A1 WO2021031975 A1 WO 2021031975A1
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Prior art keywords
drone
magnetic field
heading
heading angle
uav
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PCT/CN2020/108929
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English (en)
French (fr)
Inventor
李颖杰
张添保
陈刚
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深圳市道通智能航空技术有限公司
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Publication of WO2021031975A1 publication Critical patent/WO2021031975A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft

Definitions

  • This application relates to the field of drone technology, and in particular to a method and device for determining the heading of the drone, and the drone.
  • Multi-rotor UAV heading control is directly related to the flight stability and flight safety of UAV.
  • the yaw angle that is, the heading angle
  • the magnetometer measures the earth's magnetic field data, and the three-axis magnetic readings given by it are extremely susceptible to environmental influences, so the given initial value often deviates from the true course.
  • the drone flies other sensors participate in the heading angle fusion process, and accurate heading angle information will be obtained.
  • the aircraft When the heading angle has a large deviation from the initial heading angle given by the magnetometer, the aircraft will make a large heading The correction is reflected in the flight process, that is, the heading angle will have a large change, from flying to a slash, and at worst, a runaway bomber caused by a large correction of the heading angle.
  • the accuracy of the initial value of the heading angle directly affects the flight safety and flight quality of the multi-rotor UAV from take-off to obtaining the multi-sensor fusion heading angle. Therefore, how to give the initial value of the heading angle to minimize and avoid The initial value error has become an important task.
  • the embodiments of the present invention provide a method, a device and a drone for determining the accuracy of the initial value of the drone's heading angle.
  • a method for determining the heading of an unmanned aerial vehicle includes:
  • the detecting the flying height of the drone and the magnetic field parameters in the flying environment of the drone includes:
  • the magnetic field parameters in the flying environment of the drone are detected every preset time.
  • the updating the initial value of the heading angle according to the flying height and the magnetic field parameter includes:
  • the calculating the error of the magnetic field parameter detected each time includes:
  • the magnetic field parameter and the reference magnetic field parameter are compared to calculate the error of the magnetic field parameter.
  • the magnetic field parameters include magnetic field strength and magnetic field inclination.
  • the flying height threshold is 1.5-2m.
  • the preset time is 10-30 ms.
  • the determining the heading of the drone according to the corrected heading angle includes:
  • the updating the attitude of the drone according to the current attitude of the drone and the initial value of the heading angle includes:
  • r is the quaternion with the Z axis of the drone as the axis of rotation
  • q 0 is the quaternion of the current attitude of the drone
  • q is the quaternion of the updated attitude of the drone number.
  • the quaternion with the Z axis of the drone as the rotation axis is calculated by the following formula
  • ⁇ 0 is the yaw angle
  • r is a quaternion with the UAV Z axis as the rotation axis.
  • the method before the real-time detection of the flying height of the drone and the magnetic field parameters in the flying environment of the drone, the method further includes:
  • the embodiments of the present invention also provide the following technical solutions: a device for determining the heading of an unmanned aerial vehicle.
  • the device for determining the UAV heading includes: a detection module for detecting the flying height of the UAV and the magnetic field parameters in the flying environment of the UAV;
  • the heading angle update module updates the initial value of the heading angle according to the flight altitude and the magnetic field parameters
  • the data fusion module is used for data fusion between the data collected by the sensor and the initial value of the heading angle to obtain the corrected heading angle;
  • the heading determination module is used to determine the heading of the UAV according to the corrected heading angle.
  • the detection module includes a flying height detection unit and a magnetic field parameter detection unit;
  • the height detection unit is used to detect in real time whether the flying height of the drone is less than a preset flying height threshold
  • the magnetic field parameter detection unit is configured to detect the magnetic field parameter in the flying environment of the drone every preset time when the flying height of the drone is less than the flying height threshold.
  • the heading angle update module includes an error calculation unit and a heading angle initial value determination unit;
  • the error calculation unit is used to calculate the error of the magnetic field parameter detected each time
  • the initial heading angle determination unit is used to obtain the heading angle of the UAV when the detected error of the magnetic field parameter is the smallest, and use it as the initial heading angle.
  • the error calculation unit includes a positioning subunit, a reference magnetic field parameter acquisition subunit, and an error calculation subunit;
  • the positioning subunit is used to obtain the latitude and longitude of the location of the drone;
  • the reference magnetic field parameter acquisition subunit is used to obtain reference magnetic field parameters according to the latitude and longitude of the location of the drone;
  • the error calculation subunit is used to compare the magnetic field parameter with the reference magnetic field parameter to calculate the error of the magnetic field parameter.
  • the magnetic field parameters include magnetic field strength and magnetic field inclination.
  • a storage module is further included, and the storage module is used to store the flying height threshold and the preset time.
  • the flying height threshold is 1.5-2m;
  • the preset time is 10-30ms.
  • the heading determination module includes an attitude update unit and a heading update unit;
  • the attitude update unit is used to update the attitude of the drone according to the current attitude of the drone and the corrected heading angle;
  • the heading update unit is used to determine the heading of the drone according to the updated attitude of the drone.
  • an unmanned aerial vehicle includes:
  • An arm connected to the fuselage
  • the power device is arranged on the arm and is used to provide power for the drone to fly;
  • a magnetometer set on the fuselage, used to obtain the initial value of the heading angle of the drone
  • a variety of sensors are provided on the fuselage for collecting corresponding flight data
  • the flight controller is located on the fuselage
  • the flight controller includes:
  • a memory communicatively connected with the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can be used to execute the above The method for determining the heading of the UAV described.
  • the method for selecting the initial value of the heading angle of the drone can be within the preset flying height range of the drone by detecting the magnetic field parameters in the flying environment of the drone.
  • the heading angle still has a certain degree of accuracy, which reduces the probability of UAV taking off in a ground environment with magnetic interference, and improves flight safety.
  • Figure 1 is a schematic diagram of an application environment of an embodiment of the present invention.
  • FIG. 2 is a schematic flowchart of a method for determining a heading of a drone provided by an embodiment of the present invention
  • FIG. 3 is a schematic diagram of the flow of S21 in Figure 2;
  • FIG. 4 is a graph of UAV flight height versus flight time provided by an embodiment of the present invention.
  • FIG. 5 is a graph of three-axis readings of a UAV magnetometer versus flight time according to an embodiment of the present invention
  • FIG. 6 is a schematic diagram of the flow of S22 in FIG. 2;
  • FIG. 7 is a schematic diagram of the flow of S221 in FIG. 6;
  • FIG. 8 is a structural block diagram of an apparatus for determining a UAV heading provided by an embodiment of the present invention.
  • Fig. 9 is a structural block diagram of a drone provided by an embodiment of the present invention.
  • the embodiment of the present invention provides a method and device for determining the heading of a drone.
  • the method and device can detect the magnetic field parameters in the flying environment of the drone within the preset flying height range of the drone. Obtain the most accurate initial value of the heading angle to eliminate the influence of the external environment on the magnetometer, and provide a more accurate initial value of the heading angle for the UAV 10 to perform data fusion.
  • the heading angle still has a certain degree of accuracy, which reduces the probability of bombing the UAV 10 taking off in a ground environment with magnetic interference, and improves flight safety.
  • the following examples illustrate the application environment of the UAV heading determination method and device.
  • FIG. 1 is a schematic diagram of the application environment of the system for selecting the initial value of the drone heading angle provided by an embodiment of the present invention; as shown in FIG. 1, the application scenario includes the drone 10, the wireless network 20, the intelligent terminal 30 and the user 40 . The user 40 can operate the smart terminal 30 to control the drone 10 through the wireless network 20.
  • the UAV 10 may be an unmanned aerial vehicle driven by any type of power, including but not limited to a rotary wing UAV, a fixed wing UAV, an umbrella wing UAV, a flapping wing UAV, and a helicopter model.
  • a multi-rotor drone is taken as an example for presentation.
  • the unmanned aerial vehicle 10 may have a corresponding volume or power according to actual needs, so as to provide load capacity, flight speed, and flight range that can meet the needs of use.
  • One or more sensors may be added to the drone 10 to enable the drone 10 to realize corresponding functions.
  • the drone 10 is provided with at least one sensor of an accelerometer, a gyroscope, a magnetometer, a GPS navigator, and a vision sensor.
  • the UAV 10 also includes a flight controller, which serves as a control core for UAV flight and data transmission, and integrates one or more modules to execute corresponding logic control programs.
  • a flight controller which serves as a control core for UAV flight and data transmission, and integrates one or more modules to execute corresponding logic control programs.
  • the smart terminal 30 may be any type of smart device used to establish a communication connection with the drone 10, such as a mobile phone, a tablet computer, or a smart remote control.
  • the smart terminal 30 may be equipped with one or more different user 40 interaction devices to collect instructions from the user 40 or display and feedback information to the user 40.
  • buttons, display screens, touch screens, speakers, and remote control joysticks include but are not limited to: buttons, display screens, touch screens, speakers, and remote control joysticks.
  • the smart terminal 30 may be equipped with a touch screen, through which the user 40 receives the remote control instruction of the drone 10 and displays the image information obtained by aerial photography to the user 40 through the touch screen. The user 40 can also Switch the image information currently displayed on the display through the remote control touch screen.
  • the UAV 10 and the smart terminal 30 can also integrate existing image visual processing technologies to further provide more intelligent services.
  • the drone 10 can collect images through a dual-lens camera, and the smart terminal 30 can analyze the images, so as to realize the gesture control of the drone 10 by the user 40.
  • the wireless network 20 may be a wireless communication network used to establish a data transmission channel between two nodes based on any type of data transmission principle, such as a Bluetooth network located in different signal frequency bands, a WiFi network, a wireless cellular network, or a combination thereof.
  • Fig. 2 is an embodiment of a method for determining a heading of a drone provided by an embodiment of the present invention. As shown in Figure 2, the method for determining the heading of the UAV can be executed by the flight controller of the UAV, and includes the following steps:
  • an air pressure detection device may be used to detect the flight height of the drone 10, which includes a barometer, a sensor protection cover, and a duct.
  • the barometer is sealed in the sensor protection cover, and is installed in the drone together with the sensor protection cover.
  • On the human-machine 10, one end of the conduit is connected with the sensor protection cover, and the other end extends upward after passing through the sensor protection cover.
  • the sensor protection cover and the duct are provided, and the nozzle position at the top of the duct is set to extend upward, so as to effectively isolate the external environment of the barometer from the turbulence generated by the rotation of the blades, thereby preventing the barometer from being inadequate Stabilizing the interference of the atmospheric pressure environment helps to ensure accurate detection of the atmospheric pressure height.
  • At least two sensors such as air pressure detection device, accelerometer, GPS and ultrasonic can be used at the same time, and then complementary filtering or Kalman filtering can be used to fuse the data of these sensors to correct each other, and finally obtain the flight of UAV 10 height.
  • a magnetometer is used to detect the magnetic field parameters of the drone 10, and the magnetic field parameters include magnetic field strength and magnetic field inclination.
  • the initial value of the heading angle can be obtained through a variety of sensors, such as an electronic compass, a magnetometer, and an acceleration sensor.
  • sensors such as an electronic compass, a magnetometer, and an acceleration sensor.
  • the aforementioned various sensors are easily affected by the external environment and cannot accurately obtain the heading angle, which affects the attitude estimation. Because this kind of error is random, it cannot be eliminated in advance.
  • the magnetometer is susceptible to interference from the magnetic field generated by the surrounding environment (such as high-voltage lines, iron ore factories, etc.), thereby affecting the output of the heading angle.
  • other reasons such as ground fluctuations and the shaking of the UAV 10 body cause the turbulence of the carrier attached to the electronic compass, and the heading angle obtained by the electronic compass shows large fluctuations.
  • the initial value of the heading angle with the highest accuracy is obtained to eliminate the influence of the external environment on the magnetometer, which provides data fusion for the drone 10 More accurate initial value of heading angle.
  • the heading angle obtained by the electronic compass can also be processed and corrected by the median method and Kalman filter to obtain a more accurate heading angle.
  • the aforementioned sensor includes at least one of an accelerometer, a magnetometer, a gyroscope, a positioner, and a vision sensor.
  • the technology of data fusion is to analyze, sort, and fuse the data collected by the sensors.
  • Multi-sensor fusion data can correct the initial value of the heading angle, thereby giving more accurate heading angle data.
  • the data collected by the sensor and the initial value of the heading angle can be processed by a variety of different data fusion algorithms, such as: weighted average method, normalized weighted average method, Kalman filter, and extended Kalman filter.
  • data fusion is performed on data collected by multiple sensors based on the weighted average method.
  • the first step is to initialize the various software and hardware to be used, such as sensor initialization and Kalman filter initialization, etc.
  • the second step is to obtain IMU data, and then use this part of the data to make a judgment to see if Need to do attitude angle compensation, if it needs compensation, what is the specific value
  • the third step is to obtain the data collected by sensors such as accelerometer, magnetometer, gyroscope, locator and vision sensor, and do relevant weighting for this part of the data value Averaging operation, Kalman filter the obtained data value, thereby generating the corrected heading angle.
  • the attitude of the drone 10 is updated according to the current attitude of the drone 10 and the corrected heading angle, and further, the attitude of the drone 10 is determined according to the updated attitude of the drone 10
  • the heading of the drone 10 is described.
  • the current quaternion q 0 of the attitude of the drone 10 is obtained; according to the initial value of the heading angle and the corrected heading angle, the heading deflection angle ⁇ 0 is obtained , and the heading deflection angle ⁇ 0 Is the difference between the initial value of the heading angle and the corrected heading angle.
  • the body coordinate system is fixedly connected with the drone, the body coordinate system conforms to the right-hand rule, the origin is at the center of gravity of the drone, the X axis points to the direction of the drone, and the Y axis is from the origin Point to the right side of the drone, and the Z-axis direction is determined by the right-hand rule based on the X and Y axes.
  • the embodiments of the present invention provide a method and device for determining the heading of the drone.
  • the method and device can detect the magnetic field parameters in the flying environment of the drone within the preset flying height range of the drone. Obtain the most accurate initial value of the heading angle to eliminate the influence of the external environment on the magnetometer, and provide a more accurate initial value of the heading angle for the UAV 10 to perform data fusion. Taking off in a ground environment, the heading angle still has a certain degree of accuracy, which reduces the probability of the UAV 10 taking off in a ground environment with magnetic interference, and improves flight safety.
  • before detecting the flying height of the drone it includes: after the drone is turned on, initializing the initial value of the heading angle, and the initial value of the heading angle is given by a magnetometer.
  • S21 includes the following step:
  • the flying height threshold of the drone 10 is 1.5-2 m, and the flying height threshold is derived from the existing flight data of the drone 10.
  • Figure 4 shows the altitude information of the drone during a flight
  • Figure 5 shows the corresponding three-axis readings of the magnetometer during the flight.
  • the UAV 10 only changes the altitude, and does not perform actions in the roll and pitch channels.
  • hAGL represents the fusion altitude
  • hBaro represents the barometer altitude.
  • x represents the magnetic induction reading of the x-axis of the magnetometer
  • y represents the magnetic induction reading of the y-axis of the magnetometer
  • the z axis represents the magnetic induction reading of the z-axis of the magnetometer.
  • an air pressure detecting device is used to detect the flying height of the drone 10, which includes a barometer, a sensor protection cover, and a duct.
  • the barometer is sealed in the sensor protection cover and installed in the unmanned aircraft together with the sensor protection cover.
  • one end of the conduit is connected with the sensor protection cover, and the other end extends upward after passing through the sensor protection cover.
  • the sensor protection cover and the pipe are arranged, and the position of the nozzle at the top of the pipe is set to extend upward, so as to effectively isolate the external environment where the barometer is located from the turbulence generated by the rotation of the blades, thereby avoiding the pressure of the barometer.
  • the interference of unstable air pressure environment helps to ensure the accurate detection of air pressure height.
  • the flying height of the drone detected by the above-mentioned air pressure detection device, accelerometer, GPS and ultrasonic sensors is acquired in real time. Then compare the flying height of the drone with the flying height threshold of the drone. When the flying height of the drone is less than the flying height threshold, the magnetometer detects that the drone is flying at this time every 10-15ms Magnetic field parameters at altitude.
  • the magnetic field parameter includes at least one of a magnetic field strength, a magnetic field inclination angle, and a magnetic field deflection angle.
  • the preset time can be set according to the take-off ground environment. For example, when the take-off ground environment contains a lot of metal or other magnetic objects (such as high-voltage lines, iron ore factories, etc.), the take-off ground environment has an impact on the magnetic force. The magnetic field interference generated by the meter is strong, and the preset time can be reduced, for example, to 5-9 ms. For another example, when the take-off ground environment contains less metal or other magnetic objects, and the magnetic field generated by the take-off ground environment is weaker than the magnetic field generated by the magnetometer, the preset time can be increased, for example, to 16-20 ms.
  • the take-off ground environment contains a lot of metal or other magnetic objects (such as high-voltage lines, iron ore factories, etc.)
  • the preset time can be reduced, for example, to 5-9 ms.
  • the preset time can be increased, for example, to 16-20 ms.
  • S22 includes the following steps:
  • the World Geomagnetic Field Model provides a reference magnetic field quantity for the error judgment of the magnetic field parameters obtained by the magnetometer.
  • WMM is a mathematical model of the earth’s main magnetic field. The model can be used to calculate the geomagnetic field characteristic quantities at any point in the world. . According to the longitude, latitude, altitude, time and other information provided by the UAV GPS receiver, as well as the world geomagnetic field model WMM published by the National Geophysical Data Center of the United States, the interference determination of the magnetic field during the flight of the UAV is made.
  • the analysis is mainly performed from two aspects. One is to compare the local magnetic field intensity measured by the magnetometer with the reference magnetic field provided by WMM, and the other is to compare the local magnetic field inclination measured by the magnetometer with the reference magnetic field provided by WMM. . When there is a large error between these two values, it is determined that there is magnetic field interference.
  • the magnetic field parameters before take-off of the unmanned aerial vehicle are calculated through the magnetometer readings, and the above-mentioned magnetic field parameters are used as the first magnetic field parameters.
  • the magnetic field parameters at the flying height of the drone at this time are acquired every preset time, and the magnetic field parameters are used as the second The magnetic field parameter, the first magnetic field parameter is compared with the second magnetic field parameter, if the error between the second magnetic field and the parameter reference magnetic field is smaller than the error between the first magnetic field parameter and the reference magnetic field, then the second magnetic field parameter is replaced
  • the first magnetic field parameter that is, the second magnetic field parameter becomes the first magnetic field parameter, and cyclically, when the flying height of the drone reaches the flying height threshold, the first magnetic field parameter is
  • the optimal magnetic field parameter that is, the error between the first magnetic field parameter and the reference magnetic field is the smallest, and the heading angle at the flying height of the UAV corresponding to the optimal magnetic field parameter can be obtained to obtain the corresponding magnetic field parameter error.
  • the flying height threshold of the drone 10 is 1.5-2m.
  • the flying height of the drone reaches the flying height threshold, the impact of the take-off ground environment on the magnetometer is already very weak.
  • the heading angle obtained by the magnetometer is more accurate, and this heading angle is used as the initial value of the heading angle to complete the update of the initial value of the heading angle.
  • the flying height of the UAV is much higher than the altitude of 1.5-2m, so updating the initial value of the heading angle at the altitude of 1.5-2m will not affect the normal flight.
  • the flying height threshold can be set according to the take-off ground environment. For example, when the take-off ground environment contains a lot of metal or other magnetic objects (such as high-voltage lines, iron ore factories, etc.), the take-off ground environment has a negative impact on the magnetic force. The magnetic field interference generated by the meter is strong, and the flying height threshold can be increased, for example, to 3-5m. For another example, when the take-off ground environment contains less metal or other magnetic objects, and the magnetic field generated by the magnetometer is weakly interfered by the take-off ground environment, the flying height threshold can be reduced, for example, to 1-1.4m .
  • S221 includes the following steps:
  • the longitude, latitude, altitude, time and other information of the location of the drone can be obtained through the GPS receiver onboard the drone.
  • S2213 Compare the magnetic field parameter with the reference magnetic field parameter, and calculate the error of the magnetic field parameter in the flying environment of the drone.
  • the comparison is mainly made from two aspects. One is to compare the local magnetic field intensity measured by the magnetometer with the reference magnetic field provided by WMM, and the other is to compare the local magnetic field inclination measured by the magnetometer with the reference magnetic field provided by WMM. When there is a large error between these two values, it is determined that there is magnetic field interference.
  • the embodiments of the present application provide an apparatus 50 for determining the heading of a drone.
  • the UAV heading determination device 50 includes a detection module 51, a heading angle update module 52, a data fusion module 53, and a heading determination module 54.
  • the flying height detection module 51 is used to detect the flying height of the drone and the magnetic field parameters in the flying environment of the drone.
  • the heading angle update module 52 is used to update the initial value of the heading angle according to the flying height and the magnetic field parameters.
  • the data fusion module 53 is configured to perform data fusion between the data collected by the sensor and the initial value of the heading angle to obtain the corrected heading angle.
  • the heading determination module 54 is used to determine the heading of the UAV according to the corrected heading angle.
  • the heading angle update module 52 when the heading angle update module 52 receives the drone flight height detected by the flight height detection module 51 and the magnetic field parameters in the drone flight environment, the heading angle update module 52 Obtain the accurate initial value of the heading angle under the magnetic field parameters at different flight altitudes; then the data fusion module 53 respectively fuse the received initial value of the heading angle with the data collected by the sensor to obtain the corrected heading angle; the final heading The determining module 54 is configured to determine the heading of the UAV 10 according to the corrected heading angle.
  • the most accurate initial heading angle value is obtained by detecting the magnetic field parameters in the flying environment of the drone, so as to eliminate the influence of the external environment on the magnetometer and perform data for the drone 10 Fusion provides a more accurate initial value of the heading angle, enabling the UAV 10 to take off in a ground environment with magnetic interference.
  • the heading angle still has a certain degree of accuracy, which reduces the UAV 10 in a ground environment with magnetic interference.
  • the probability of taking off the bomber improves flight safety.
  • the following examples illustrate the application environment of the UAV heading determination method and device.
  • the UAV heading determination device 50 further includes a storage module 55 configured to store the flying height threshold and the preset time.
  • the flying height threshold of the drone is 1.5-2m; the preset time is 10-30ms.
  • the heading angle update module 52 includes an error calculation unit and a heading angle initial value determination unit.
  • the error calculation unit is used to calculate the error of the magnetic field parameter detected each time; the initial value determination unit of the heading angle is used to obtain the heading angle of the drone when the detected error of the magnetic field parameter is the smallest, and use it as The initial value of the heading angle.
  • the error calculation unit includes a positioning subunit, a reference magnetic field parameter acquisition subunit, and an error calculation subunit; the positioning subunit is used to obtain the latitude and longitude of the location of the drone; The reference magnetic field parameter acquisition subunit is used to obtain reference magnetic field parameters according to the latitude and longitude of the location of the drone; the error calculation subunit is used to compare the magnetic field parameters with the reference magnetic field parameters to calculate the magnetic field The error of the parameter.
  • the heading determination module 54 includes an attitude update unit and a heading update unit.
  • the attitude update unit is used to update the attitude of the drone according to the current attitude of the drone and the corrected heading angle; the heading update unit is used to update the attitude of the drone according to the updated attitude To determine the heading of the drone.
  • the attitude update unit is specifically used to obtain the quaternion q 0 of the current attitude of the UAV 10; obtain the heading deflection angle ⁇ 0 according to the initial value of the heading angle and the corrected heading angle; According to the heading deflection angle ⁇ 0 , the quaternion with the Z axis of the UAV 10 as the rotation axis is obtained:
  • FIG. 9 is a structural block diagram of a drone 10 provided by an embodiment of the present invention.
  • the UAV 10 may include: a body, an arm, a power unit, a magnetometer, various sensors, a flight controller, and a communication module 130.
  • the flight controller includes a processor 110 and a memory 120.
  • the arm is connected with the fuselage; the power device is arranged on the arm and is used to provide power for the drone to fly.
  • the magnetometer is used to obtain the initial value of the heading angle of the drone.
  • the multiple types of sensors are used to collect corresponding flight data, and the multiple types of sensors may be accelerometers, gyroscopes, magnetometers, GPS navigators, and vision sensors.
  • the processor 110, the memory 120, and the communication module 130 establish a communication connection between any two through a bus.
  • the processor 110 may be of any type and has one or more processing cores. It can perform single-threaded or multi-threaded operations, and is used to parse instructions to perform operations such as obtaining data, performing logical operation functions, and issuing operation processing results.
  • the memory 120 can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as the program corresponding to the method for determining the heading of a drone in the embodiment of the present invention Instructions/modules (for example, the flying height detection module 51, the heading angle update module 52, the data fusion module 53, the heading determination module 54, the storage module 55 shown in FIG. 8).
  • the processor 110 executes various functional applications and data processing of the UAV heading determination device 50 by running the non-transient software programs, instructions, and modules stored in the memory 120, that is, to realize the unmanned operation in any of the foregoing method embodiments. How to determine the aircraft heading.
  • the memory 120 may include a program storage area and a data storage area.
  • the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the drone heading determination device 50 Wait.
  • the memory 120 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices.
  • the memory 120 may optionally include memories remotely provided with respect to the processor 110, and these remote memories may be connected to the drone 10 via a network. Examples of the aforementioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
  • the memory 120 stores instructions that can be executed by the at least one processor 110; the at least one processor 110 is used to execute the instructions to implement the drone heading determination method in any of the foregoing method embodiments, for example, The above-described method steps 21, 22, 23, 24, etc. are executed to realize the functions of the modules 51-55 in FIG. 8.
  • the communication module 130 is a functional module used to establish a communication connection and provide a physical channel.
  • the communication module 130 may be any type of wireless or wired communication module 130, including but not limited to a WiFi module or a Bluetooth module.
  • the embodiment of the present invention also provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors 110 is executed, for example, executed by one of the processors 110 in FIG. 9, so that the one or more processors 110 can execute the method for determining the drone heading in any of the foregoing method embodiments, for example, execute the steps 21, 22, 23, 24, etc., realize the functions of modules 51-55 in Figure 8.
  • the device embodiments described above are merely illustrative.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each implementation manner can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware.
  • a person of ordinary skill in the art can understand that all or part of the processes in the methods of the foregoing embodiments can be implemented by instructing relevant hardware by a computer program in a computer program product.
  • the computer program can be stored in a non-transitory computer.
  • the computer program includes program instructions, and when the program instructions are executed by a related device, the related device can execute the procedures of the embodiments of the foregoing methods.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM), etc.
  • the above products can execute the method for determining the heading of the drone provided by the embodiments of the present invention, and have the corresponding functional modules and beneficial effects for executing the method for determining the heading of the drone.
  • the method for determining the heading of the drone provided in the embodiment of the present invention.

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Abstract

一种无人机航向角初始值选取方法、装置及无人机。该方法包括：检测无人机的飞行高度和无人机飞行环境中的磁场参数（S21）；根据飞行高度和磁场参数，更新航向角初值（S22）；将传感器采集的数据与航向角初值进行数据融合，得到修正后的航向角（S23）；根据修正后的航向角，确定无人机的航向（S24）。该方法可以在无人机（10）的预设飞行高度范围内，通过检测无人机（10）飞行环境中的磁场参数情况，得到准确度最高的航向角初值，实现了无人机（10）在具有磁干扰的地面环境中起飞，航向角仍具有一定的准确程度，减少了无人机（10）在具有磁干扰地面环境中起飞的炸机概率，提高了飞行安全性。

Description

无人机航向确定方法、装置及无人机
本申请要求于2019年8月19日提交中国专利局、申请号为201910765629.8、申请名称为“无人机航向确定方法、装置及无人机”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及无人机技术领域，尤其涉及一种无人机航向确定方法、装置及无人机。
背景技术
多旋翼无人机航向控制，直接关系到无人机的飞行稳定性和飞行安全性。无人机滚转、俯仰、偏航三个姿态通道中，偏航角度，即航向角，由磁力计给出初值，其他传感器对其进行后期修正最终得到融合后的航向角。磁力计测量地磁场数据，其给出的三轴磁读数极易受环境影响，所以其给定的初值往往会偏离真正的航向。随着无人机飞行，其他传感器参与航向角融合过程，准确的航向角信息会被获得，当该航向角与磁力计给定的初始航向角具有较大偏差时，飞机会对航向进行大幅度修正，体现在飞行过程中，就是航向角会出现较大的变化，轻则飞斜线，重则出现诸如航向角大幅修正导致的失控炸机。
航向角初始值的准确程度直接影响了多旋翼无人机从起飞到获得多传感器融合航向角这一过程中的飞行安全和飞行品质，因此，如何给定航向角初值，尽量减小和避免初值误差，成为一项重要工作。
发明内容
为了解决上述技术问题，本发明实施例提供一种提高无人机的航向角初始值精确度的无人机航向确定方法、装置及无人机。
为解决上述技术问题，本发明实施例提供以下技术方案：一种无人机航向确定方法。所述无人机航向确定方法包括：
检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数；
根据所述飞行高度和所述磁场参数，更新航向角初值；
将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角；
根据所述修正后的航向角，确定所述无人机的航向。
可选地，所述检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数，包括：
实时检测所述无人机的飞行高度是否小于预设的飞行高度阈值；
当所述无人机的飞行高度小于所述飞行高度阈值时，每隔预设时间检测一次所述无人机飞行环境中的磁场参数。
可选地，所述根据所述飞行高度和所述磁场参数，更新所述航向角初值，包括：
计算每次检测的所述磁场参数的误差；
获取检测到的所述磁场参数误差最小时所述无人机的航向角，并将所述航向角作为航向角初值。
可选地，所述计算每次检测的所述磁场参数的误差，包括：
获取所述无人机所在位置的经纬度；
根据所述无人机所在位置的经纬度，得到基准磁场参数；
对比所述磁场参数和所述基准磁场参数，以计算所述磁场参数的误差。
可选地，所述磁场参数包括磁场强度和磁场倾角。
可选地，所述飞行高度阈值为1.5-2m。
可选地，所述预设时间为10-30ms。
可选地，所述根据所述修正后的航向角，确定所述无人机的航向，包括：
根据当前无人机的姿态和所述修正后的航向角，更新所述无人机的姿态；
根据更新后的所述无人机的姿态，确定所述无人机的航向。
可选地，所述根据当前所述无人机的姿态和所述航向角初值，更新所述无人机的姿态，包括：
获取当前所述无人机的姿态的四元数；
根据所述航向角初值和所述修正后的航向角，得到航向偏角；
根据所述航向偏角，得到以无人机Z轴为转轴的四元数：
通过如下算式，确定更新后的所述无人机的姿态的四元数：
q＝r*q 0
其中，r为以所述无人机Z轴为转轴的四元数，q 0为当前所述无人机的姿态的四元数，q为更新后的所述无人机的姿态的四元数。
可选地，通过如下算式，计算得到以所述无人机Z轴为转轴的四元数
Figure PCTCN2020108929-appb-000001
其中，ψ 0为所述航向偏角，r为以所述无人机Z轴为转轴的四元数。
可选地，所述实时检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数之前，还包括：
所述无人机开机后，初始化所述航向角初值。
为解决上述技术问题，本发明实施例还提供以下技术方案：一种无人机航向确定装置。
所述无人机航向确定装置包括：检测模块，用于检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数；
航向角更新模块，根据所述飞行高度和所述磁场参数，更新航向角初值；
数据融合模块，用于将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角；
航向确定模块，用于根据所述修正后的航向角，确定所述无人机的航向。
可选地，所述检测模块包括飞行高度检测单元和磁场参数检测单元；
所述高度检测单元用于实时检测所述无人机的飞行高度是否小于预设的飞行高度阈值；
所述磁场参数检测单元用于当所述无人机的飞行高度小于所述飞行高度阈值时，每隔预设时间检测一次所述无人机飞行环境中的磁场参数。
可选地，所述航向角更新模块包括误差计算单元和航向角初值确定单元；
所述误差计算单元用于计算每次检测的所述磁场参数的误差；
所述航向角初值确定单元用于获取检测到的所述磁场参数误差最小时所述无人机的航向角并作为航向角初值。
可选地，所述误差计算单元包括定位子单元、基准磁场参数获取子单元和误差计算子单元；
所述定位子单元用于获取所述无人机所在位置的经纬度；
所述基准磁场参数获取子单元用于根据所述无人机所在位置的经纬度，得到基准磁场参数；
所述误差计算子单元用于将所述磁场参数与所述基准磁场参数作对比，计算所述磁场参数的误差。
可选地，所述磁场参数包括磁场强度和磁场倾角。
可选地，还包括存储模块，所述存储模块用于存储飞行高度阈值和预设时间。
可选地，所述飞行高度阈值为1.5-2m；
所述预设时间为10-30ms。
可选地，航向确定模块包括姿态更新单元和航向更新单元；
所述姿态更新单元用于根据当前无人机的姿态和所述修正后的航向角，更新所述无人机的姿态；
所述航向更新单元用于根据更新后的所述无人机的姿态，确定所述无人机的航向。
为解决上述技术问题，本发明实施例还提供以下技术方案：一种无人机。所述无人机包括：
机身；
机臂，与所述机身相连；
动力装置，设于所述机臂，用于给所述无人机提供飞行的动力；
磁力计，设于所述机身，用于获取所述无人机的航向角初值；
多种传感器，设于所述机身，用于分别采集相应的飞行数据；以及
飞行控制器，设于所述机身；
所述飞行控制器包括：
处理器；以及
与所述处理器通信连接的存储器；其中，所述存储器存储有可被所述处理 器执行的指令，所述指令被所述处理器执行，以使所述处理器能够用于执行如上述所述的无人机航向确定方法。
与现有技术相比较，本发明实施例的提供无人机航向角初始值选取方法可以在无人机的预设飞行高度范围内，通过检测所述无人机飞行环境中的磁场参数情况，得到准确度最高的航向角初值，来消除外界环境对磁力计的影响，为无人机进行数据融合提供了更为准确的航向角初值，实现了无人机在具有磁干扰的地面环境中起飞，航向角仍具有一定的准确程度，减少了无人机在具有磁干扰地面环境中起飞的炸机概率，提高了飞行安全性。
附图说明
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。
图1为本发明实施例的应用环境示意图；
图2为本发明实施例提供的无人机航向确定方法的流程示意图；
图3是图2中S21的流程示意图；
图4为本发明实施例提供的无人机飞行高度-飞行时间的曲线图；
图5为本发明实施例提供的无人机的磁力计三轴读数-飞行时间的曲线图；
图6是图2中S22的流程示意图；
图7是图6中S221的流程示意图；
图8为本发明实施例提供的无人机航向确定装置的结构框图；
图9为本发明实施例提供的无人机的结构框图。
具体实施方式
为了便于理解本发明，下面结合附图和具体实施例，对本发明进行更详细的说明。需要说明的是，当元件被表述“固定于”另一个元件，它可以直接在另一个元件上、或者其间可以存在一个或多个居中的元件。当一个元件被表述“连接”另一个元件，它可以是直接连接到另一个元件、或者其间可以存在一个或多个居中的元件。本说明书所使用的术语“上”、“下”、“内”、“外”、“底部”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。此外，术语“第一”、“第二”“第三”等仅用于描述目的，而不能理解为指示或暗示相对重要性。
除非另有定义，本说明书所使用的所有的技术和科学术语与属于本发明的技术领域的技术人员通常理解的含义相同。本说明书中在本发明的说明书中所 使用的术语只是为了描述具体的实施例的目的，不是用于限制本发明。本说明书所使用的术语“和/或”包括一个或多个相关的所列项目的任意的和所有的组合。
此外，下面所描述的本发明不同实施例中所涉及的技术特征只要彼此之间未构成冲突就可以相互结合。
本发明实施例提供了一种无人机航向确定方法和装置，所述方法和装置可以在无人机的预设飞行高度范围内，通过检测所述无人机飞行环境中的磁场参数情况，得到准确度最高的航向角初值，来消除外界环境对磁力计的影响，为无人机10进行数据融合提供了更为准确的航向角初值，实现了无人机10在具有磁干扰的地面环境中起飞，航向角仍具有一定的准确程度，减少了无人机10在具有磁干扰地面环境中起飞的炸机概率，提高了飞行安全性。以下举例说明所述无人机航向确定方法和装置的应用环境。
图1是本发明实施例提供的无人机航向角初值选取***的应用环境的示意图；如图1所示，所述应用场景包括无人机10、无线网络20、智能终端30以及用户40。用户40可操作智能终端30通过无线网络20操控所述无人机10。
无人机10可以是以任何类型的动力驱动的无人飞行载具，包括但不限于旋翼无人机、固定翼无人机、伞翼无人机、扑翼无人机以及直升机模型等。在本实施例中以多旋翼无人机为例进行陈述。
该无人机10可以根据实际情况的需要，具备相应的体积或者动力，从而提供能够满足使用需要的载重能力、飞行速度以及飞行续航里程等。无人机10上还可以添加有一种或者多种传感器，令无人机10能够实现相应的功能。
例如，在本实施例中，该无人机10设置有加速度计、陀螺仪、磁力计、GPS导航仪和视觉传感器中的至少一种传感器。
无人机10还包括飞行控制器，作为无人机飞行和数据传输等的控制核心，整合一个或者多个模块，以执行相应的逻辑控制程序。
智能终端30可以是任何类型，用以与无人机10建立通信连接的智能装置，例如手机、平板电脑或者智能遥控器等。该智能终端30可以装配有一种或者多种不同的用户40交互装置，用以采集用户40指令或者向用户40展示和反馈信息。
这些交互装置包括但不限于：按键、显示屏、触摸屏、扬声器以及遥控操作杆。例如，智能终端30可以装配有触控显示屏，通过该触控显示屏接收用户40对无人机10的遥控指令并通过触控显示屏向用户40展示航拍获得的图像信息，用户40还可以通过遥控触摸屏切换显示屏当前显示的图像信息。
在一些实施例中，无人机10与智能终端30之间还可以融合现有的图像视觉处理技术，进一步的提供更智能化的服务。例如无人机10可以通过双光相机采集图像的方式，由智能终端30对图像进行解析，从而实现用户40对于无人机10的手势控制。
无线网络20可以是基于任何类型的数据传输原理，用于建立两个节点之 间的数据传输信道的无线通信网络，例如位于不同信号频段的蓝牙网络、WiFi网络、无线蜂窝网络或者其结合。
图2为本发明实施例提供的无人机航向确定方法的实施例。如图2所示，该无人机航向确定方法可以由无人机的飞行控制器执行，包括如下步骤：
S21、检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数。
具体地，可以采用气压检测装置来检测无人机10的飞行高度，该气压检测装置包括气压计、传感器保护罩及导管，气压计密封设于传感器保护罩内，并连同传感器保护罩安装于无人机10上，导管的一端与传感器保护罩连通，另一端从传感器保护罩穿出后向上延伸。
通过设有传感器保护罩及导管，并将导管的顶端的管口位置设置成向上延伸，以能将气压计的所在外部环境与桨叶旋转产生的扰流进行有效隔离，进而避免气压计受不稳定气压环境的干扰，利于确保气压高度的精确检测。
在一些实施例中，可同时采用气压检测装置、加速度计、GPS和超声波等至少二种传感器，然后使用互补滤波或者卡尔曼滤波融合这些传感器的数据，互相修正，最后得到无人机10的飞行高度。
具体地，采用磁力计检测无人机10的磁场参数，所述磁场参数包括磁场强度和磁场倾角。
S22、根据所述飞行高度和所述磁场参数，更新航向角初值。
具体地，可通过多种传感器获得上述航向角初值，如电子罗盘、磁力计和加速度传感器等，但是上述多种传感器均易受到外界环境的影响，不能准确的获取航向角，影响了姿态估算的稳定性和可靠性，由于此类误差是随机的，无法预先消除。例如，磁力计易受周围环境(如高压线、铁矿厂等)所产生的磁场干扰，从而影响航向角的输出。又例如，地面的波动及无人机10本体的抖动等其他原因造成电子罗盘所附载体的颠簸，由电子罗盘得到的航向角显示出较大波动。
在本实施例中，通过检测所述无人机飞行环境中的磁场参数情况，得到准确度最高的航向角初值来消除外界环境对磁力计的影响，为无人机10进行数据融合提供了更为准确的航向角初值。
在一些实施例中，也可对电子罗盘获取的航向角采用中值法和卡尔曼滤波器进行处理修正，以得到更为精确的航向角。
S23、将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角。
具体的，上述传感器包括加速度计、磁力计、陀螺仪、定位仪和视觉传感器中的至少一种。
数据融合的技术是对传感器采集的数据进行分析，整理，融合等一系列的操作处理，多传感器融合数据能够实现对航向角初值的修正，从而给出更为准确的航向角数据。
传感器采集的数据与所述航向角初值可采用多种不同的数据融合算法进 行处理，例如：加权平均法、归一化加权平均法、卡尔曼滤波和扩展卡尔曼滤波。
在本实施例中，基于加权平均法对多传感器采集的数据进行数据融合。具体地，第一步就要将所要使用到的各种软硬件进行初始化操作，如传感器初始化以及卡尔曼滤波初始化等；第二步要获取IMU数据，再通过这部分数据信息做判断，看是否需要做姿态角补偿，若是需要补偿，具体数值为多少；第三步要获取加速度计、磁力计、陀螺仪、定位仪和视觉传感器等传感器采集的数据，针对这部分数据值，做相关的加权平均操作，把得到的数据值进行卡尔曼滤波，从而产生修正后的航向角。
S24、根据所述修正后的航向角，确定所述无人机10的航向。
具体地，根据当前所述无人机10的姿态和所述修正后的航向角，更新所述无人机10的姿态，进一步地，根据更新后的所述无人机10的姿态，确定所述无人机10的航向。
具体地，获取当前所述无人机10的姿态的四元数q 0；根据所述航向角初值和所述修正后的航向角，得到航向偏角ψ 0，所述航向偏角ψ 0为所述航向角初值与所述修正后的航向角之差。
建立机体坐标系，所述机体坐标系与所述无人机固联，所述机体坐标系符合右手法则，原点在无人机的重心处，X轴指向无人机前进方向，Y轴由原点指向无人机右侧，Z轴方向根据X、Y轴由右手法则确定。
根据所述航向偏角ψ 0，得到以所述无人机10的Z轴为转轴的四元数：
Figure PCTCN2020108929-appb-000002
根据以所述无人机10的Z轴为转轴的四元数r与当前所述无人机10的姿态的四元数q 0，得到新的所述无人机10的姿态的四元数q＝r*q 0。
本发明实施例提供了一种无人机航向确定方法和装置，所述方法和装置可以在无人机的预设飞行高度范围内，通过检测所述无人机飞行环境中的磁场参数情况，得到准确度最高的航向角初值，来消除外界环境对磁力计的影响，为无人机10进行数据融合提供了更为准确的航向角初值，实现了无人机10在具有磁干扰的地面环境中起飞，航向角仍具有一定的准确程度，减少了无人机10在具有磁干扰地面环境中起飞的炸机概率，提高了飞行安全性。
在一些实施例中，所述检测无人机飞行高度之前，包括：所述无人机开机后，初始化所述航向角初值，所述航向角初值由磁力计给出。
为了使更新的航向角初值更为精确，需要准确检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数，在一些实施例中，请参阅图3，S21包括如下步骤：
S211:实时检测所述无人机的飞行高度是否小于预设的飞行高度阈值。优选地，所述无人机10的所述飞行高度阈值为1.5-2m，所述飞行高度阈值是由无人机10现有飞行数据基础上得出。
具体地，请一并参阅图4和图5，图4给出了一次飞行中无人机高度信息，图5给出了该飞行中相应的磁力计三轴读数。在本次飞行中，无人机10仅做高度变化，在滚转和俯仰通道不做动作。图4中hAGL代表融合高度，hBaro代表气压计高度。图5中x代表磁力计x轴的磁感应强度读数，y代表磁力计y轴的磁感应强度读数，z轴代表磁力计z轴的磁感应强度读数。对比图4和图5可以看出，随着无人机高度的升高，其磁力计读数也随之变化。分析原因，是由于无人机起飞地面对磁场产生影响，导致磁力计读数变化。通常情况下，起飞地面对磁场的影响普遍存在，在含有金属或其他磁性物体的环境中，这种影响更加剧烈。而以往对无人机10航向角的初值给定，往往是在地面完成的，这就导致了初值的不准确。
结合图4和图5分析可以得出，由于地面环境的不确定会导致磁力计给出的磁场信息不准确，从而导致航向角初值不准确。这种影响与距离的二次方成反比，通过检测无人机实时高度发现，当无人机高度达到1.5-2m时，磁力计读数不再发生明显变化，此时起飞地面环境对磁力计的影响已经十分微弱，此时磁力计能够给出更加准确的磁场信息，从而使更新的航向角初始值也更加准确，因此本发明将所述无人机10的所述飞行高度阈值设为1.5-2m。而且通常情况下，无人机飞行高度远高于1.5-2m高度，因此在1.5-2m高度更新航向角初值不会对正常飞行造成影响。
具体地，采用气压检测装置来检测无人机10的飞行高度，该气压检测装置包括气压计、传感器保护罩及导管，气压计密封设于传感器保护罩内，并连同传感器保护罩安装于无人机10上，导管的一端与传感器保护罩连通，另一端从传感器保护罩穿出后向上延伸。本发明通过设置传感器保护罩及导管，并将导管的顶端的管口位置设置成向上延伸，以能将气压计的所在外部环境与桨叶旋转产生的扰流进行有效隔离，进而避免气压计受不稳定气压环境的干扰，利于确保气压高度的精确检测。
S212:当所述无人机的飞行高度小于所述飞行高度阈值时，每隔预设时间检测一次所述无人机飞行环境中的磁场参数。所述预设时间为10-15ms。
具体地，首先实时获取由上述气压检测装置、加速度计、GPS和超声波等传感器检测的无人机飞行高度。然后对比无人机飞行高度与所述无人机的飞行高度阈值，当所述无人机的飞行高度小于所述飞行高度阈值时，每隔10-15ms通过磁力计检测无人机此时飞行高度下的磁场参数。所述磁场参数包括磁场强度、磁场倾角和磁场偏角中的至少一种。
在一些实施例中，所述预设时间可根据起飞地面环境进行设置，例如当起飞地面环境中含有较多金属或其他磁性物体(如高压线、铁矿厂等)，此时起飞地面环境对磁力计所产生的磁场干扰较强，可将所述预设时间减小，比如减小至5-9ms。又例如当起飞地面环境中含有较少金属或其他磁性物体，此时起飞地面环境对磁力计所产生的磁场干扰较弱，可将所述预设时间增大，比如增加至16-20ms。
为了使更新的航向角初值更为精确，在一些实施例中，请参阅图6，S22包括如下步骤：
S221:计算每次检测的所述磁场参数的误差。
具体地，世界地磁场模型(WMM)为磁力计获取的磁场参数的误差判定提供了一个基准磁场量，WMM是地球主磁场的数学模型，利用该模型可以计算全球任意位置点的地磁场特征量。根据无人机GPS接收机提供的经度、纬度、高度、时间等信息，以及美国国家地球物理数据中心公布的世界地磁场模型WMM，对无人机飞行过程中的磁场进行干扰判定。
在本实施例中，主要从两方面进行分析，一是磁力计测量的当地磁场强度与WMM提供的基准磁场量作对比，一是磁力计测量的当地磁场倾角与WMM提供的基准磁场量作对比。当这两个值出现较大误差时，判定具有磁场干扰。
S222:获取检测到的所述磁场参数误差最小时所述无人机的航向角并作为航向角初值。
具体地，所述无人机开机后，通过磁力计读数计算无人机起飞前的磁场参数，并将上述磁场参数作为第一磁场参数。
所述无人机起飞后且所述无人机飞行高度小于所述飞行高度阈值时，每隔预设时间，获取此时无人机飞行高度下的磁场参数，将所述磁场参数作为第二磁场参数，将所述第一磁场参数与所述第二磁场参数做对比，若第二磁场与参数基准磁场量误差小于第一磁场参数与基准磁场量误差，则将所述第二磁场参数替代所述第一磁场参数，即所述第二磁场参数变为第一磁场参数，循环往复，则当所述无人机飞行高度达到所述飞行高度阈值时，此时所述第一磁场参数为最优磁场参数，即所述第一磁场参数与基准磁场量误差最小，获取最优磁场参数对应的所述无人机飞行高度处的航向角，即可获取磁场参数误差最小时对应的所述无人机飞行高度处的航向角。
具体地，所述无人机10的所述飞行高度阈值为1.5-2m，当所述无人机飞行高度达到所述飞行高度阈值时，此时起飞地面环境对磁力计的影响已经十分微弱，此时通过磁力计获取到的航向角更加准确，并将此航向角作为航向角初值，以完成航向角初值的更新。而且通常情况下，无人机飞行高度远高于1.5-2m高度，因此在1.5-2m高度更新航向角初值不会对正常飞行造成影响。
在一些实施例中，所述飞行高度阈值可根据起飞地面环境进行设置，例如当起飞地面环境中含有较多金属或其他磁性物体(如高压线、铁矿厂等)，此时起飞地面环境对磁力计所产生的磁场干扰较强，可将所述飞行高度阈值增大，比如增大至3-5m。又例如当起飞地面环境中含有较少金属或其他磁性物体，此时起飞地面环境对磁力计所产生的磁场干扰较弱，可将所述飞行高度阈值减小，比如减小至1-1.4m。
为了准确计算出每隔所述预设时间检测的所述无人机飞行环境中的磁场参数的误差。在一些实施例中，请参阅图7，S221包括以下步骤：
S2211:获取所述无人机所在位置的经纬度。
具体地，可通过无人机机载的GPS接收机获取所述无人机所在位置的经度、纬度、高度、时间等信息。
S2212:根据所述无人机所在位置的经纬度，得到基准磁场参数。
具体地，根据GPS得到的经纬度查WMM表得到当地的磁场强度，磁场倾角，磁场偏角等信息。
S2213:将所述磁场参数与所述基准磁场参数作对比，计算所述无人机飞行环境中的磁场参数的误差。
具体地，主要从两方面进行对比，一是磁力计测量的当地磁场强度与WMM提供的基准磁场量作对比，一是磁力计测量的当地磁场倾角与WMM提供的基准磁场量作对比。当这两个值出现较大误差时，判定具有磁场干扰。
需要说明的是，在上述各个实施例中，上述各步骤之间并不必然存在一定的先后顺序，本领域普通技术人员，根据本申请实施例的描述可以理解，不同实施例中，上述各步骤可以有不同的执行顺序，亦即，可以并行执行，亦可以交换执行等等。
作为本申请实施例的另一方面，本申请实施例提供一种无人机航向确定装置50。请参阅图8，该无人机航向确定装置50包括：检测模块51、航向角更新模块52、数据融合模块53以及航向确定模块54。
飞行高度检测模块51用于检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数。
航向角更新模块52用于根据飞行高度和所的磁场参数，更新航向角初值。
数据融合模块53用于将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角。
航向确定模块54用于根据所述修正后的航向角，确定所述无人机的航向。
具体地，在本实施例中，当航向角更新模块52接收到飞行高度检测模块51检测到的无人机飞行高度及无人机飞行环境中的磁场参数，航向角更新模块52根据无人机不同飞行高度下的的磁场参数情况，获取准确的航向角初值；然后数据融合模块53分别将接收到的航向角初值与传感器采集的数据进行数据融合，得到修正后的航向角；最后航向确定模块54用于根据所述修正后的航向角，确定所述无人机10的航向。
因此，在本实施例中，通过检测所述无人机飞行环境中的磁场参数情况，得到准确度最高的航向角初值，来消除外界环境对磁力计的影响，为无人机10进行数据融合提供了更为准确的航向角初值，实现了无人机10在具有磁干扰的地面环境中起飞，航向角仍具有一定的准确程度，减少了无人机10在具有磁干扰地面环境中起飞的炸机概率，提高了飞行安全性。以下举例说明所述无人机航向确定方法和装置的应用环境。
在一些实施例中，无人机航向确定装置50还包括存储模块55，所述存储模块55用于存储飞行高度阈值和预设时间。
优选地，所述无人机的所述飞行高度阈值为1.5-2m；所述预设时间为 10-30ms。
其中，在一些实施例中，所述航向角更新模块52包括误差计算单元和航向角初值确定单元。所述误差计算单元用于计算每次检测的所述磁场参数的误差；所述航向角初值确定单元用于获取检测到的所述磁场参数误差最小时所述无人机的航向角并作为航向角初值。
其中，在一些实施例中，所述误差计算单元包括定位子单元、基准磁场参数获取子单元和误差计算子单元；所述定位子单元用于获取所述无人机所在位置的经纬度；所述基准磁场参数获取子单元用于根据所述无人机所在位置的经纬度，得到基准磁场参数；所述误差计算子单元用于将所述磁场参数与所述基准磁场参数作对比，计算所述磁场参数的误差。
其中，在一些实施例中，航向确定模块54包括姿态更新单元和航向更新单元。所述姿态更新单元用于根据当前无人机的姿态和所述修正后的航向角，更新所述无人机的姿态；所述航向更新单元用于根据更新后的所述无人机的姿态，确定所述无人机的航向。
其中，姿态更新单元具体用于获取当前所述无人机10的姿态的四元数q 0；根据所述航向角初值和所述修正后的航向角，得到航向偏角ψ 0；根据所述航向偏角ψ 0，得到以所述无人机10的Z轴为转轴的四元数：
Figure PCTCN2020108929-appb-000003
根据以所述无人机10的Z轴为转轴的四元数r与当前所述无人机10的姿态的四元数q 0，得到新的所述无人机10的姿态q＝r*q 0。
图9为本发明实施例提供的无人机10的结构框图。如图9所示，该无人机10可以包括：机身、机臂、动力装置、磁力计、多种传感器、飞行控制器以及通信模块130。其中，飞行控制器包括处理器110和存储器120。
所述机臂与所述机身相连；所述动力装置设于所述机臂，用于给所述无人机提供飞行的动力。
所述磁力计用于获取所述无人机的航向角初值。多种所述传感器用于分别采集相应的飞行数据，多种所述传感器可为加速度计、陀螺仪、磁力计、GPS导航仪和视觉传感器中的多种。
所述处理器110、存储器120以及通信模块130之间通过总线的方式，建立任意两者之间的通信连接。
处理器110可以为任何类型，具备一个或者多个处理核心的处理器110。其可以执行单线程或者多线程的操作，用于解析指令以执行获取数据、执行逻辑运算功能以及下发运算处理结果等操作。
存储器120作为一种非暂态计算机可读存储介质，可用于存储非暂态软件程序、非暂态性计算机可执行程序以及模块，如本发明实施例中的无人机航向确定方法对应的程序指令/模块(例如，附图8所示的飞行高度检测模块51、航向角更新模块52、数据融合模块53、航向确定模块54、存储模块55)。处 理器110通过运行存储在存储器120中的非暂态软件程序、指令以及模块，从而执行无人机航向确定装置50的各种功能应用以及数据处理，即实现上述任一方法实施例中无人机航向确定方法。
存储器120可以包括存储程序区和存储数据区，其中，存储程序区可存储操作***、至少一个功能所需要的应用程序；存储数据区可存储根据无人机航向确定装置50的使用所创建的数据等。此外，存储器120可以包括高速随机存取存储器，还可以包括非暂态存储器，例如至少一个磁盘存储器件、闪存器件、或其他非暂态固态存储器件。在一些实施例中，存储器120可选包括相对于处理器110远程设置的存储器，这些远程存储器可以通过网络连接至无人机10。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
所述存储器120存储有可被所述至少一个处理器110执行的指令；所述至少一个处理器110用于执行所述指令，以实现上述任意方法实施例中无人机航向确定方法，例如，执行以上描述的方法步骤21、22、23、24等等，实现图8中的模块51-55的功能。
通信模块130是用于建立通信连接，提供物理信道的功能模块。通信模块130以是任何类型的无线或者有线通信模块130，包括但不限于WiFi模块或者蓝牙模块等。
进一步地，本发明实施例还提供了一种非暂态计算机可读存储介质，所述非暂态计算机可读存储介质存储有计算机可执行指令，该计算机可执行指令被一个或多个处理器110执行，例如，被图9中的一个处理器110执行，可使得上述一个或多个处理器110执行上述任意方法实施例中无人机航向确定方法，例如，执行以上描述的方法步骤21、22、23、24等等，实现图8中的模块51-55的功能。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。
通过以上的实施方式的描述，本领域普通技术人员可以清楚地了解到各实施方式可借助软件加通用硬件平台的方式来实现，当然也可以通过硬件。本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程是可以通过计算机程序产品中的计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非暂态计算机可读取存储介质中，该计算机程序包括程序指令，当所述程序指令被相关设备执行时，可使相关设备执行上述各方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory,ROM)或随机存储记忆体(Random Access Memory,RAM)等。
上述产品可执行本发明实施例所提供的无人机航向确定方法，具备执行无 人机航向确定方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本发明实施例所提供的无人机航向确定方法。
最后应说明的是：以上实施例仅用以说明本发明的技术方案，而非对其限制；在本发明的思路下，以上实施例或者不同实施例中的技术特征之间也可以进行组合，步骤可以以任意顺序实现，并存在如上所述的本发明的不同方面的许多其它变化，为了简明，它们没有在细节中提供；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (20)

  1. 一种无人机航向确定方法，应用于无人机，其特征在于，包括：
    检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数；
    根据所述飞行高度和所述磁场参数，更新航向角初值；
    将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角；
    根据所述修正后的航向角，确定所述无人机的航向。
  2. 根据权利要求1所述的方法，其特征在于，
    所述检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数，包括：
    实时检测所述无人机的飞行高度是否小于预设的飞行高度阈值；
    当所述无人机的飞行高度小于所述飞行高度阈值时，每隔预设时间检测一次所述无人机飞行环境中的磁场参数。
  3. 根据权利要求2所述的方法，其特征在于，
    所述根据所述飞行高度和所述磁场参数，更新所述航向角初值，包括：
    计算每次检测的所述磁场参数的误差；
    获取检测到的所述磁场参数的误差最小时所述无人机的航向角，并将所述航向角作为航向角初值。
  4. 根据权利要求3所述的方法，其特征在于，
    所述计算每次检测的所述磁场参数的误差，包括：
    获取所述无人机所在位置的经纬度；
    根据所述无人机所在位置的经纬度，得到基准磁场参数；
    对比所述磁场参数和所述基准磁场参数，以计算所述磁场参数的误差。
  5. 根据权利要求2所述的方法，其特征在于，
    所述磁场参数包括磁场强度和磁场倾角。
  6. 根据权利要求2所述的方法，其特征在于，
    所述飞行高度阈值为1.5-2m。
  7. 根据权利要求2所述的方法，其特征在于，
    所述预设时间为10-30ms。
  8. 根据权利要求4所述的方法，其特征在于，
    所述根据所述修正后的航向角，确定所述无人机的航向，包括：
    根据当前无人机的姿态和所述修正后的航向角，更新所述无人机的姿态；
    根据更新后的所述无人机的姿态，确定所述无人机的航向。
  9. 根据权利要求8所述的方法，其特征在于，
    所述根据当前所述无人机的姿态和所述航向角初值，更新所述无人机的姿态，包括：
    获取当前所述无人机的姿态的四元数；
    根据所述航向角初值和所述修正后的航向角，得到航向偏角；
    根据所述航向偏角，得到以无人机Z轴为转轴的四元数：
    通过如下算式，确定更新后的所述无人机的姿态四元数：
    q＝r*q 0；
    其中，r为以所述无人机Z轴为转轴的四元数，q 0为当前所述无人机的姿态的四元数，q为更新后的所述无人机的姿态四元数。
  10. 根据权利要求9所述的方法，其特征在于，该方法还包括：通过如下算式，计算得到以所述无人机Z轴为转轴的四元数：
    Figure PCTCN2020108929-appb-100001
    其中，ψ 0为所述航向偏角，r为以所述无人机Z轴为转轴的四元数。
  11. 根据权利要求1所述的方法，其特征在于，
    所述检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数之前，还包括：
    所述无人机开机后，初始化所述航向角初值。
  12. 一种无人机航向确定装置，其特征在于，包括：
    检测模块，用于检测所述无人机的飞行高度和所述无人机飞行环境中的磁场参数；
    航向角更新模块，根据所述飞行高度和所述磁场参数，更新航向角初值；
    数据融合模块，用于将传感器采集的数据与所述航向角初值进行数据融合，得到修正后的航向角；
    航向确定模块，用于根据所述修正后的航向角，确定所述无人机的航向。
  13. 根据权利要求12所述的无人机航向确定装置，其特征在于，
    所述检测模块包括飞行高度检测单元和磁场参数检测单元；
    所述高度检测单元用于实时检测所述无人机的飞行高度是否小于预设的飞行高度阈值；
    所述磁场参数检测单元用于当所述无人机的飞行高度小于所述飞行高度阈值时，每隔预设时间检测一次所述无人机飞行环境中的磁场参数。
  14. 根据权利要求13所述的无人机航向确定装置，其特征在于，
    所述航向角更新模块包括误差计算单元和航向角初值确定单元；
    所述误差计算单元用于计算每次检测的所述磁场参数的误差；
    所述航向角初值确定单元用于获取检测到的所述磁场参数的误差最小时所述无人机的航向角并作为航向角初值。
  15. 根据权利要求14所述的无人机航向确定装置，其特征在于，
    所述误差计算单元包括定位子单元、基准磁场参数获取子单元和误差计算子单元；
    所述定位子单元用于获取所述无人机所在位置的经纬度；
    所述基准磁场参数获取子单元用于根据所述无人机所在位置的经纬度，得到基准磁场参数；
    所述误差计算子单元用于将所述磁场参数与所述基准磁场参数作对比，计算所述磁场参数的误差。
  16. 根据权利要求12所述的无人机航向确定装置，其特征在于，
    所述磁场参数包括磁场强度和磁场倾角。
  17. 根据权利要求13所述的无人机航向确定装置，其特征在
    于，还包括存储模块，所述存储模块用于存储所述飞行高度阈值和所述预设
    时间。
  18. 根据权利要求13所述的无人机航向确定装置，其特征在
    于，
    所述飞行高度阈值为1.5-2m；
    所述预设时间为10-30ms。
  19. 根据权利要求12所述的无人机航向确定装置，其特征在于，
    航向确定模块包括姿态更新单元和航向更新单元；
    所述姿态更新单元用于根据当前无人机的姿态和所述修正后的航向角，更新所述无人机的姿态；
    所述航向更新单元用于根据更新后的所述无人机的姿态，确定所述无人机的航向。
  20. 一种无人机，其特征在于，包括：
    机身；
    机臂，与所述机身相连；
    动力装置，设于所述机臂，用于给所述无人机提供飞行的动力；
    磁力计，设于所述机身，用于获取所述无人机的航向角初值；
    多种传感器，设于所述机身，用于分别采集相应的飞行数据；以及
    飞行控制器，设于所述机身；
    所述飞行控制器包括：
    处理器；以及
    与所述处理器通信连接的存储器；其中，所述存储器存储有可被所述处理器执行的指令，所述指令被所述处理器执行，以使所述处理器能够用于执行如权利要求1-11中任一项所述的无人机航向确定方法。
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