Servo control system and control method based on unmanned platform target tracking

Abstract

The invention relates to a servo control system and method based on unmanned platform target tracking. The system comprises a small optical sensor assembly, an image processing unit, a gyroscope IMU unit, a position coding unit, a three-axis servo motor and a servo control unit. And the position coding unit is used for acquiring the absolute position of the starting time of the three-axis servo motor and starting the inner ring stable loop control and detection equipment position information so as to adjust the small optical sensor assembly to move to a specified position. The three-axis servo motor is used for receiving the servo control signal and locking the posture and position of the unmanned platform in the rolling direction, the azimuth direction and the pitching direction according to the posture and position of the target calibration object. And the servo control unit performs path optimization calculation on the received equipment position information, attitude information and navigation path by adopting multi-closed-loop nested loop control, generates a servo control signal and feeds the servo control signal back to the system. By adopting the method, the small target tracking precision and the servo control efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned platform target tracking, and in particular to a servo control system and a control method based on unmanned platform target tracking. Background Art

[0002] In the prior art, the following solutions are usually adopted for the problem of small target tracking and control, but there are many shortcomings. First, many prior arts use a single type of sensor, such as an optical sensor or an IMU (inertial measurement unit) for target detection and tracking. These systems are relatively simple, but their detection accuracy and anti-interference ability are limited, and they are easily affected by environmental changes and noise, resulting in poor tracking effects. Secondly, traditional servo control systems usually adopt single-loop control, that is, only one feedback loop is used to adjust system parameters. This method has low control accuracy and slow response speed, and it is difficult to meet the requirements of high-precision and high-dynamic target tracking. In addition, many existing systems use a pre-set fixed path for navigation and do not have the ability to optimize the path in real time. This method is prone to tracking failure or increased error when the target moves or the environment changes. Finally, in terms of attitude calibration, the prior art may only use a simple calibration method, which cannot fully eliminate the influence of environmental factors (such as temperature changes) on sensor accuracy, resulting in poor accuracy of attitude information.

[0003] Single sensor systems perform poorly in complex environments and are prone to tracking loss or reduced accuracy. In addition, single-loop control systems have limited adjustment capabilities and slow response speeds, making it difficult to meet the needs of highly dynamic target tracking.

[0004] In summary, existing technologies usually adopt methods such as single sensor, single-loop control, fixed path navigation and simple calibration, which have problems such as low detection accuracy, slow response speed, poor adaptability and inaccurate posture calibration. Summary of the invention

[0005] Based on this, it is necessary to provide a servo control system and control method based on unmanned platform target tracking that can improve the small target tracking accuracy and speed in response to the above technical problems.

[0006] A servo control system based on unmanned platform target tracking, the servo control system includes: a small optical sensor component, an image processing unit and a three-axis servo control unit. The image processing unit includes: an image tracking unit and an image navigation unit. The three-axis servo control unit includes: a gyro IMU unit, a position encoding unit, a three-axis servo motor and a servo control unit.

[0007] A small optical sensor assembly is used for the UAV platform to obtain optical images of target calibration objects and transmit the optical images to the image tracking unit to extract the characteristic information of multiple target calibration objects.

[0008] The image tracking unit is used to convert the received feature information into photoelectric signals, calculate the target surface tracking distance between the target calibration object and the UAV platform, and output the tracking signal corresponding to the minimum value of the target surface tracking distance to the image navigation unit and the servo control unit respectively.

[0009] The image navigation unit is used to analyze the tracking signal according to the path optimization strategy, generate a first navigation path, and transmit the first navigation path back to the servo control unit step by step.

[0010] The gyro IMU unit is used to collect the original attitude information of the target calibration object through a three-axis sensor, calibrate the original attitude information using temperature segmentation, obtain the corrected attitude information, and periodically send the attitude information to the servo control unit.

[0011] The position encoding unit is used to obtain the absolute position of the start-up time of the three-axis servo motor, start the inner loop stabilization loop control according to the absolute position control, and detect the device position information of the small optical sensor component, and transmit the device position information to the servo control unit to adjust the movement of the small optical sensor component to the specified position.

[0012] The three-axis servo motor is used to receive the servo control signal output by the servo control unit to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction according to the posture and position of the target calibration object.

[0013] The servo control unit is used to perform path optimization calculation on the received device position information, posture information and the first navigation path by adopting multi-closed-loop nested loop control to generate a servo control signal, and the servo control signal is fed along the multi-closed-loop nested loop.

[0014] A servo control method based on unmanned platform target tracking, the method comprising:

[0015] An optical image of a target calibration object is acquired according to a small optical sensor component of the UAV platform, and the optical image is transmitted to an image tracking unit to extract feature information of multiple target calibration objects.

[0016] After the image tracking unit converts the received feature information into photoelectric signals, the target surface tracking distance between the target calibration object and the UAV platform is calculated, and the tracking signal corresponding to the minimum value of the target surface tracking distance is output to the image navigation unit and the servo control unit respectively.

[0017] The tracking signal is parsed according to the path optimization strategy of the image navigation unit to generate a first navigation path, and the first navigation path is transmitted back to the servo control unit step by step.

[0018] The original attitude information of the target calibration object is collected according to the three-axis sensor of the gyro IMU unit, and the original attitude information is calibrated by temperature segmentation to obtain the corrected attitude information, and the attitude information is periodically sent to the servo control unit.

[0019] The absolute position of the start-up time of the three-axis servo motor is obtained according to the position encoding unit, the inner loop stabilization loop control is started according to the absolute position control, and the device position information of the small optical sensor component is detected, and the device position information is transmitted to the servo control unit to adjust the movement of the small optical sensor component to the specified position.

[0020] The three-axis servo motor receives the servo control signal output by the servo control unit to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction according to the posture and position of the target calibration object.

[0021] The servo control unit adopts multi-closed-loop nested loop control to perform path optimization calculation on the received device position information, posture information and the first navigation path to generate a servo control signal, and the servo control signal is fed along the multi-closed-loop nested loop.

[0022] The above-mentioned servo control system and control method based on unmanned platform target tracking, the system includes a small optical sensor assembly, an image processing unit and a three-axis servo control unit. First, the small optical sensor assembly obtains an optical image of the target calibration object and transmits the image to the image tracking unit to extract the characteristic information of the target. The image tracking unit converts the characteristic information into a photoelectric signal, calculates the target surface tracking distance between the target calibration object and the unmanned aerial vehicle platform, and then outputs the tracking signal to the image navigation unit and the servo control unit according to the minimum value of the target surface tracking distance. The image navigation unit analyzes the tracking signal according to the path optimization strategy, generates a first navigation path, and transmits it back to the servo control unit step by step. The three-axis servo control unit includes a gyro IMU unit, a position encoding unit, a three-axis servo motor and a servo control unit. The gyro IMU unit collects the original posture information of the target calibration object through a three-axis sensor, uses temperature segmented calibration to obtain the corrected posture information, and periodically sends it to the servo control unit. The position encoding unit obtains the absolute position of the start-up time of the three-axis servo motor, and starts the inner loop stabilization loop according to the absolute position control, and at the same time detects the device position information of the small optical sensor assembly, and transmits this information to the servo control unit to adjust the sensor assembly to the specified position. The three-axis servo motor receives the servo control signal output by the servo control unit, and locks the attitude and position of the unmanned platform in the roll direction, azimuth direction and pitch direction according to the attitude and position of the target calibration object. The servo control unit adopts multi-closed-loop nested loop control to perform path optimization calculation on the received device position information, attitude information and the first navigation path, generate servo control signals, and feed them along the multi-closed-loop nested loop. The multi-sensor fusion design improves the accuracy of data acquisition and the stability of the system. The collaborative work of the image processing unit and the servo control unit enables the system to adjust the position and attitude of the unmanned platform in real time, ensuring stable tracking of the target. Through multi-closed-loop nested loop control and real-time feedback adjustment, the system can quickly and accurately handle target tracking tasks in various complex environments. Its comprehensive use of sensors and advanced control algorithms makes the system have high precision and high responsiveness, significantly improves the accuracy and control efficiency of small target tracking, and realizes the high-efficiency application of unmanned platforms in small target tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural block diagram of a servo control system based on unmanned platform target tracking in one embodiment;

[0024] Figure 2 A schematic diagram of a servo control electrical system framework based on unmanned platform target tracking in one embodiment;

[0025] Figure 3 A schematic diagram of a stable platform control algorithm loop in one embodiment;

[0026] Figure 4 A schematic diagram of a tracking loop in one embodiment;

[0027] Figure 5 The figure is a flow chart of a servo control method based on target tracking of an unmanned platform in one embodiment. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0029] In one embodiment, Figure 1 As shown, the servo control system based on unmanned platform target tracking includes: a small optical sensor component 102, an image processing unit and a three-axis servo control unit. The image processing unit includes: an image tracking unit 104 and an image navigation unit 106. The three-axis servo control unit includes: a gyro IMU unit 108, a position encoding unit 110, a three-axis servo motor 112 and a servo control unit 114.

[0030] The small optical sensor assembly 102 is used for the UAV platform to obtain an optical image of a target calibration object, and transmit the optical image to an image tracking unit to extract feature information of multiple target calibration objects.

[0031] The image tracking unit 104 is used to convert the received feature information into photoelectric signals, calculate the target surface tracking distance between the target calibration object and the UAV platform, and output the tracking signal corresponding to the minimum value of the target surface tracking distance to the image navigation unit and the servo control unit respectively.

[0032] It is worth mentioning that the hardware design of the image tracking unit adopts FPGA+ARM architecture. The FPGA reads and controls the camera image and tracks the target, while the ARM recognizes the target. First, the FPGA reads the camera image and sends the image to the ARM for target recognition. After the ARM recognizes the target, it combines with the FPGA to track the target in real time.

[0033] The image navigation unit 106 is used to analyze the tracking signal according to the path optimization strategy, generate a first navigation path, and transmit the first navigation path back to the servo control unit step by step.

[0034] The gyro IMU unit 108 is used to collect the original posture information of the target calibration object through a three-axis sensor, calibrate the original posture information by temperature segmentation, obtain the corrected posture information, and periodically send the posture information to the servo control unit.

[0035] It is worth mentioning that the gyro IMU unit collects angular velocity information in the inertial system through the inertial IMU unit, and periodically sends the angular velocity information to the servo control unit. The servo control unit uses the angular velocity information as the input of the stabilization loop, and outputs the motor torque signal through the servo closed-loop control to control the motor to compensate for the angular velocity signal caused by the disturbance of the unmanned platform, ensuring that the optical axis of the fixedly installed gyro IMU unit can effectively isolate the disturbance, thereby improving the imaging stability and the target locking and tracking accuracy.

[0036] The position encoding unit 110 is used to obtain the absolute position of the start-up time of the three-axis servo motor, start the inner loop stabilization loop control according to the absolute position control, and detect the device position information of the small optical sensor component, and transmit the device position information to the servo control unit to adjust the movement of the small optical sensor component to the specified position.

[0037] It is worth mentioning that the main types of position sensors are rotary transformers, photoelectric encoders, and magnetic encoders. Through the structural layout design, the rotary transformer is divided into a stator, rotor, and coaxial structure integrated design. The magnetic encoder is used as the position acquisition unit of the unmanned platform. The sensor is relatively mature in the industrial field, and the highest accuracy can reach within 0.2°. The magnetic encoder adopts a magnetoelectric design, and the magnetic field change of the magnetic induction device is used to generate or provide the position and speed of the servo motor. The physical working principle of the magnetic encoder is the magnetoresistance effect. The magnetoresistance effect is generated by the internal carriers of the energized conductor or semiconductor, and the external Lorentz magnetic force causes the internal carrier motion trajectory to deflect or produce spiral motion, thereby changing the potential difference inside the conductor or semiconductor. This process belongs to the microscopic performance, and the macroscopic performance is only the change of the external magnetic field, and the magnetic resistance value will also change accordingly, which is the magnetoresistance effect of the magnetic encoder. The advantage of using the magnetic field principle to generate signals is that the magnetic field signal will not be affected by dust, moisture, high temperature and vibration.

[0038] The three-axis servo motor 112 is used to receive the servo control signal output by the servo control unit to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction according to the posture and position of the target calibration object.

[0039] The servo control unit 114 is used to perform path optimization calculation on the received device position information, posture information and the first navigation path by adopting multi-closed-loop nested loop control to generate a servo control signal, and the servo control signal is fed along the multi-closed-loop nested loop.

[0040] It is worth mentioning that the servo control unit uses ARM as the servo control processor, which mainly completes the closed-loop control of the three-axis servo motor, speed and position sensor acquisition, communication protocol analysis and processing, and comprehensive control. At the same time, it performs multi-level processing on the power supply, and uses DC-DC and LDO design solutions to perform secondary power supply processing on the input power supply to ensure the power supply requirements of the internal IC while ensuring the power supply requirements of the motor and gyro IMU unit. The servo control unit integrates the motor drive module and position sensor analysis unit design, the hardware circuit is designed in a centralized area, the module area is separated, and the digital signal and analog signal are isolated and processed.

[0041] In one embodiment, if Figure 2 As shown in the figure, the framework of the servo control electrical system based on target tracking of unmanned platforms is shown. After the optical signals obtained by the front downward visible light detector and the front downward infrared detector are converted into electrical signals, they are directly sent to the image tracking board. After the optical signals obtained by the downward visible light detector and the downward infrared detector are converted into electrical signals, they are sent to the imaging board for signal synthesis processing, and then transmitted to the image tracking board in two ways. The image tracking board performs small target detection calculation on the image electrical signal, and the calculation results are output to the image navigation board through the Ethernet and SDI interfaces. The image navigation board takes the detected small target image as the path end point, performs positioning path planning, and outputs the path planning scheme to the airborne flight control, data link, and feeds it back to the image tracking board at the same time, so that the image tracking board synchronizes the path to the servo control board. The servo control board synthesizes the small target detection image processing results and the path planning scheme, and generates attitude control signals for each servo unit and gyro board respectively.

[0042] In one embodiment, the small optical sensor assembly includes: a front downward-looking infrared detector, a front downward-looking visible light detector, a downward-looking infrared detector, and a downward-looking visible light detector. The front downward-looking infrared detector and the downward-looking infrared detector are used to collect infrared images formed by infrared energy reflected by target calibration objects through infrared lenses and detectors, and the infrared image is processed by an infrared processing module to extract infrared characteristic information of multiple target calibration objects, and the infrared characteristic information is transmitted to an image tracking unit. The front downward-looking visible light detector and the downward-looking visible light detector are used to collect visible light images reflected by target calibration objects through the joint action of visible light lenses and detectors, and the visible light image is processed by a visible light processing module to extract visible light characteristic information of multiple target calibration objects, and the visible light characteristic information is transmitted to the image tracking unit.

[0043] It is worth mentioning that the infrared camera is mainly composed of an infrared lens, a detector and a processing circuit. The infrared lens mainly completes the infrared energy reflection of the object and projects the object onto the detector. The processing circuit controls the detector to collect and output infrared images, and the detector circuit mainly completes the image data acquisition.

[0044] In one embodiment, the target surface tracking distance includes: infrared tracking distance and visible light tracking distance. The image tracking unit is also used to calculate the infrared tracking distance between the target calibration object and the UAV platform according to the received infrared feature information and the preset infrared distance constraint condition:

[0045]

[0046] Among them, R IR To meet the infrared tracking distance of the minimum resolvable temperature difference, R TV is the visible light tracking distance that meets the requirements of the number of compressed lines, V is the visible distance, MRTD is the minimum resolvable temperature difference of the infrared camera, ΔT is the background temperature difference of the target calibration object, m is the diffusion coefficient, f′ is the focal length of the infrared camera lens, H is the size of the target calibration object, N is the vertical resolution of the infrared camera, h is the target height of the infrared camera, n is the number of compressed lines, ω b is the half field of view of the infrared camera. And according to the received visible light feature information and the preset visible light distance constraint, the visible light tracking distance between the target calibration object and the UAV platform is calculated:

[0047]

[0048]

[0049] Among them, R TV is the visible light tracking distance that meets the target contrast requirement, V is the visible distance, MTF is the modulation transfer function of the objective lens of the visible light camera, and E is t is the illumination near the target calibration object, γ is the reflectivity of the surface of the target calibration object to visible light, T 0 is the optical transmittance of the objective lens of the visible light camera, E d is the minimum illumination requirement of the target surface of the visible light camera, F = f' / D is the aperture number of the objective lens of the visible light camera, f' is the focal length of the objective lens of the visible light camera, D is the incident aperture diameter of the objective lens of the visible light camera, m is the dispersion coefficient, H is the size of the target calibration object, N is the vertical resolution of the visible light camera, ω b is the half field of view of the visible light camera, h is the target height of the visible light camera, and n is the required number of lines.

[0050] It is worth noting that the infrared recognition distance refers to the maximum oblique distance at which the useful signal of the target can be extracted. The recognition distance should meet the following two conditions at the same time: ① The target temperature difference meets the minimum resolvable temperature difference (MRTD) requirement of the infrared detector; ② The target pixels occupy a certain number of rows in the image. These two conditions must be met at the same time, and neither can be missing. The final result of the infrared recognition distance is the closest distance among the infrared recognition distances that meet the two conditions. According to the Johnson criterion and image recognition experience, the equivalent size of the infrared target must occupy more than 6 pixels, and the small target detection system can capture the target.

[0051] In addition, the visible light camera is mainly composed of two parts: the optical lens and the detector circuit. The optical lens mainly completes the optical reflection of the object and projects the object on the detector. The detector circuit mainly completes the data acquisition of the image. After the detector circuit obtains the image data, it is sent to the FPGA of the back-end processing board through the LVDS data line. After the FPGA performs ISP processing on the image, the image is generated. The image sensor unit is one of the core units of the camera. The unit includes the image sensor, the image sensor peripheral circuit and the secondary power supply design. The image sensor converts the optical image into a charge image signal and reads it out in a specified sequence; the peripheral circuit cooperates with the sensor to work normally; the secondary power supply part converts the camera power supply into various secondary power supplies required by the sensor. The visible light recognition distance refers to the maximum oblique distance at which the useful signal of the target can be extracted. The recognition distance should meet the following three conditions at the same time: ① The target contrast meets the requirements of the CMOS imaging sensor system for signal extraction capability; ② The illumination requirement of the target image on the CMOS target surface is at least greater than the CMOS sensitivity; ③ The target pixel occupies a certain number of visible light rows. The three conditions must be met at the same time, and none of them can be missing. The final result of the visible light seeker recognition distance is to take the shortest distance among the visible light recognition distances that meet the three conditions. According to Johnson's criterion and image recognition experience, the critical directional size of the visible light target must be more than 8 pixels so that the visible light seeker can reliably capture the target.

[0052] In one embodiment, the gyro IMU unit includes: an IMU inertial component unit, an independent accelerometer and a controller processing unit. The IMU inertial component unit is used to collect the three-axis angular rate information, three-axis acceleration information and other sensor data uploaded by the three-axis sensor, and output it to the controller processing unit. The independent accelerometer is used to output independent acceleration data to the controller processing unit. The controller processing unit is used to read the data of the IMU inertial component unit and the independent accelerometer, so as to perform temperature calibration on the three-axis sensor by temperature segmentation, and obtain corrected three-axis angular rate information, three-axis acceleration information and independent acceleration data. The corrected three-axis angular rate information, three-axis acceleration information and independent acceleration data are solved at the initial viewing angle, and the data is fused and compensated to obtain the three-axis attitude angle information, and the corrected three-axis angular rate information and three-axis attitude angle information are periodically output to the servo control unit.

[0053] It is worth noting that the hardware design of the gyro board IMU unit consists of a three-axis angular rate sensor, a three-axis accelerometer, a controller processing unit, and a secondary power supply processing unit. The IMU inertial component outputs raw sensor data such as angular velocity data and accelerometer data. A separate three-axis accelerometer outputs acceleration data. The controller processing unit reads the IMU inertial component sensor data and independent accelerometer data, and after temperature compensation and calibration of the sensor, it performs initial angle calculation, data fusion and compensation, and coordinate transformation, and finally obtains attitude angle information. The corrected three-axis gyro angular rate information and the fused three-axis attitude angle information are periodically sent to the back-end servo control board unit. The gyro IMU unit uses temperature segmentation for compensation and performs gyro output linear correction to ensure that the gyro zero bias stability is not affected by temperature changes.

[0054] In one embodiment, the three-axis servo motor includes: a roll servo motor, an azimuth servo motor and a pitch servo motor. The roll servo motor is used to adjust the posture and position of the unmanned platform in the roll direction according to the roll control signal generated by the parsed servo control signal. The azimuth servo motor is used to adjust the posture and position of the unmanned platform in the azimuth direction according to the azimuth control signal generated by the parsed servo control signal. The pitch servo motor is used to adjust the posture and position of the unmanned platform in the pitch direction according to the pitch control signal generated by the parsed servo control signal. The roll servo motor, the azimuth servo motor and the pitch servo motor adopt a direct drive method for three-axis servo linkage.

[0055] It is worth mentioning that the servo linkage adopts a direct drive mode. After load torque estimation, the load torque, friction torque and eccentric torque of each servo motor are preliminarily estimated. Although the roll and azimuth motors are not affected by eccentric gravity, there is still the influence of unbalanced inertia torque caused by longitudinal acceleration during operation. Therefore, the maximum output torque of the roll load needs to be T1=57.6mN·m; the maximum output torque of the azimuth load is T2=48mN·m; the maximum continuous torque of the pitch load is: T3=34mN·m.

[0056] In one embodiment, the position encoding unit includes: a roll encoder, an azimuth encoder, and a pitch encoder. The roll encoder is used to control the roll servo motor to move to a specified position in the roll direction according to the roll rate by using the magnetoresistance effect. The azimuth encoder is used to control the azimuth servo motor to move to a specified position in the azimuth direction according to the azimuth rate by using the magnetoresistance effect. The pitch encoder is used to control the pitch servo motor to move to a specified position in the pitch direction according to the azimuth rate by using the magnetoresistance effect.

[0057] In one embodiment, the servo control unit uses ARM as a servo control processor, and is connected to the gyro IMU unit, the three-axis servo motor and the position encoding unit through a line-to-line aviation connector. The multi-closed-loop nested loop control includes: an inner-loop stabilization loop control and an outer-loop tracking loop control. The servo control unit is also used to solve the tracking performance error index of the target calibration object in the outer-loop tracking loop control according to the received device position, attitude information, the first navigation path and the preset correction network transfer function, and transmit the tracking performance error index back to the inner-loop stabilization loop control for signal calibration, generate a locking tracking control signal, and feed the locking tracking control signal to the position encoding unit, the gyro IMU unit and the three-axis servo motor respectively.

[0058] In one of the embodiments, the principle of the inner loop stabilization loop control is as follows: in the stage of searching for the target calibration object by the UAV platform, a multi-loop closed-loop system of current loop, speed loop and position loop is used, and the angular velocity of the motion of the stabilization platform mechanism relative to the inertial space is measured by the rate gyro, and the angular velocity of the motion is compensated by the stabilization loop PID controller, so that the UAV platform is in a self-stabilizing state. When the UAV platform is in a self-stabilizing state, the position loop receives the given instructions in real time, and controls the search, locking and tracking of the target calibration object by the human-machine platform according to the given instructions. When the UAV platform locks the target calibration object, the small optical sensor assembly enters the automatic tracking mode, the position loop reference is added to the target deviation for position tracking, and a given speed loop reference is output, the speed loop performs vector transformation on the given speed loop reference, and outputs three mutually 120° sinusoidal current signals to drive the three-axis servo motor to calibrate the deviation in real time, and complete the tracking control of the target calibration object. The principle of the outer tracking loop control is: the imaging system of the small optical sensor assembly calculates the angular error signal of the target calibration object and transmits it to the inner stabilization loop control. The inner stabilization loop control adjusts the optical axis to move in the direction of reducing the error angle to form a closed-loop negative feedback, thereby completing the unmanned platform's tracking of the target calibration object at the line of sight angle.

[0059] It is worth noting that the servo control system corresponds to two loops. In the stabilization process (stabilization loop), the rate gyro measures the angular velocity of the stabilization platform mechanism relative to the inertial space during the target search phase, and the stabilization loop PID controller performs speed compensation to maintain the stability of the stabilization platform relative to the inertial space and isolate the aircraft disturbance caused by the body vibration. The system has high requirements for dynamic response and static stability, and adopts a multi-loop closed-loop system of current loop + speed loop + position loop. In the tracking process (tracking loop), in the terminal guidance phase, the video detector captures the target, processes and detects its video signal, and then compares the captured target center with the sensor visual axis center to obtain the target deviation. The deviation is transmitted to the servo control unit, and the PID closed-loop control is performed to track the target. The position of the stabilization platform relative to the aircraft measured by the angular displacement sensor is transmitted to the onboard computer, thereby adjusting the aircraft attitude and truly realizing the aircraft's locking and tracking of the target. The stabilization loop and the tracking loop are integrated, with the stabilization loop as the inner loop and the tracking loop as the outer loop, and the system function is realized through dual closed-loop control.

[0060] In one embodiment, if Figure 3As shown, before the device locks the target, the unmanned platform is in a self-stabilizing state, and completes the search, locking and tracking of the target according to the instructions. At this time, the position loop receives the given instructions in real time. After locking the target, the camera enters the automatic tracking mode, the position loop reference is added to the target deviation for position tracking, the position loop outputs the given speed loop reference, the speed loop outputs the given current loop reference, and the current loop outputs the three mutually 120° sinusoidal current signals through vector transformation to drive the motor to calibrate the deviation in real time, so as to achieve the purpose of tracking the target, which can not only isolate the external disturbance function in real time, but also track the target dynamically in real time. During the execution of the above functions, the magnetic encoder measures the angular position information of the platform relative to the aircraft frame, and transmits this information to the onboard computer to guide the unmanned platform to move along the tracking trajectory. At the same time, in the target tracking mode, the locked target angular velocity information is transmitted to the onboard computer for processing.

[0061] In one embodiment, if Figure 4 As shown in the figure, for tracking targets with low mobility, the tracking error is determined by the static accuracy of the tracking sensor and the stability accuracy of the line of sight. For highly maneuverable targets, the tracking loop is required to have sufficient bandwidth, and the increase in bandwidth is limited by the update frequency of the sensor and the delays and lags in the tracker. The tracking loop bandwidth, maximum tracking angular velocity, and line of sight angular velocity output error are all dynamic performance indicators of the tracking loop in the control system. The principle of the tracking loop is: the imaging system calculates the target angle error signal and transmits it to the stabilization loop. The stabilization loop makes the optical axis move in the direction of reducing the error angle to form a closed-loop negative feedback, thereby realizing automatic tracking of the line of sight angle.

[0062] Each module in the above-mentioned servo control system based on unmanned platform target tracking can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0063] In one embodiment, Figure 5 As shown in FIG. 1 , a servo control method based on target tracking of an unmanned platform is provided. The method is applied to Figure 1 The servo control system in is taken as an example to illustrate, including the following steps:

[0064] Step 502 , obtaining an optical image of a target calibration object according to a small optical sensor component of the UAV platform, and transmitting the optical image to an image tracking unit to extract feature information of a plurality of target calibration objects.

[0065] Step 504, after the image tracking unit converts the received feature information into photoelectric signals, the target surface tracking distance between the target calibration object and the UAV platform is calculated, and the tracking signal corresponding to the minimum value of the target surface tracking distance is output to the image navigation unit and the servo control unit respectively.

[0066] Step 506 , analyzing the tracking signal according to the path optimization strategy of the image navigation unit, generating a first navigation path, and transmitting the first navigation path back to the servo control unit step by step.

[0067] Step 508, collecting original posture information of the target calibration object according to the three-axis sensor of the gyro IMU unit, calibrating the original posture information by temperature segmentation, obtaining corrected posture information, and periodically sending the posture information to the servo control unit.

[0068] Step 510, obtaining the absolute position of the start-up time of the three-axis servo motor according to the position encoding unit, starting the inner loop stabilization loop control according to the absolute position control, and detecting the device position information of the small optical sensor assembly, and transmitting the device position information to the servo control unit to adjust the small optical sensor assembly to move to the specified position.

[0069] Step 512, receiving the servo control signal output by the servo control unit according to the three-axis servo motor, so as to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction respectively according to the posture and position of the target calibration object.

[0070] Step 514, the servo control unit uses multiple closed-loop nested loop control to perform path optimization calculation on the received device position information, posture information and the first navigation path to generate a servo control signal, and the servo control signal is fed along the multiple closed-loop nested loops.

[0071] In the above-mentioned servo control method based on unmanned platform target tracking, the system includes a small optical sensor assembly, an image processing unit and a three-axis servo control unit. First, the small optical sensor assembly obtains an optical image of the target calibration object and transmits the image to the image tracking unit to extract the characteristic information of the target. The image tracking unit converts the characteristic information into a photoelectric signal, calculates the target surface tracking distance between the target calibration object and the unmanned aerial vehicle platform, and then outputs a tracking signal to the image navigation unit and the servo control unit according to the minimum value of the target surface tracking distance. The image navigation unit analyzes the tracking signal according to the path optimization strategy, generates a first navigation path, and transmits it back to the servo control unit step by step. The three-axis servo control unit includes a gyro IMU unit, a position encoding unit, a three-axis servo motor and a servo control unit. The gyro IMU unit collects the original posture information of the target calibration object through a three-axis sensor, obtains the corrected posture information by temperature segment calibration, and periodically sends it to the servo control unit. The position encoding unit obtains the absolute position of the start-up time of the three-axis servo motor, and starts the inner loop stabilization loop according to the absolute position control, and at the same time detects the device position information of the small optical sensor assembly, and transmits this information to the servo control unit to adjust the sensor assembly to the specified position. The three-axis servo motor receives the servo control signal output by the servo control unit, and locks the attitude and position of the unmanned platform in the roll direction, azimuth direction and pitch direction according to the attitude and position of the target calibration object. The servo control unit adopts multi-closed-loop nested loop control to perform path optimization calculation on the received device position information, attitude information and the first navigation path, generate servo control signals, and feed them along the multi-closed-loop nested loop. The multi-sensor fusion design improves the accuracy of data acquisition and the stability of the system. The collaborative work of the image processing unit and the servo control unit enables the system to adjust the position and attitude of the unmanned platform in real time, ensuring stable tracking of the target. Through multi-closed-loop nested loop control and real-time feedback adjustment, the system can quickly and accurately handle target tracking tasks in various complex environments. Its comprehensive use of sensors and advanced control algorithms makes the system have high precision and high responsiveness, significantly improves the accuracy and control efficiency of small target tracking, and realizes the high-efficiency application of unmanned platforms in small target tracking.

[0072] It should be understood that although Figure 5The steps in the flowchart of are shown in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in 5 may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0073] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0074] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0075] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0076] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A servo control system based on unmanned platform target tracking, characterized in that: The servo control system includes: a small optical sensor component, an image processing unit and a three-axis servo control unit; wherein the image processing unit includes: an image tracking unit and an image navigation unit; the three-axis servo control unit includes: a gyro IMU unit, a position encoding unit, a three-axis servo motor and a servo control unit; The small optical sensor assembly is used for the UAV platform to obtain an optical image of a target calibration object, and transmit the optical image to an image tracking unit to extract feature information of multiple target calibration objects; The image tracking unit is used to convert the received feature information into photoelectric signals, calculate the target surface tracking distance between the target calibration object and the UAV platform, and output the tracking signal corresponding to the minimum value of the target surface tracking distance to the image navigation unit and the servo control unit respectively; The image navigation unit is used to analyze the tracking signal according to the path optimization strategy, generate a first navigation path, and transmit the first navigation path back to the servo control unit step by step; The gyro IMU unit is used to collect the original posture information of the target calibration object through a three-axis sensor, calibrate the original posture information by temperature segmentation, obtain the corrected posture information, and periodically send the posture information to the servo control unit; The position encoding unit is used to obtain the absolute position of the start-up time of the three-axis servo motor, start the inner loop stabilization loop control according to the absolute position control, and detect the device position information of the small optical sensor assembly, and transmit the device position information to the servo control unit to adjust the small optical sensor assembly to move to a specified position; The three-axis servo motor is used to receive the servo control signal output by the servo control unit to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction according to the posture and position of the target calibration object; The servo control unit is used to perform path optimization calculation on the received device position information, the posture information and the first navigation path using multi-closed-loop nested loop control to generate a servo control signal, and the servo control signal is fed along the multi-closed-loop nested loop.

2. The servo control system according to claim 1, characterized in that: The small optical sensor assembly includes: a front downward-looking infrared detector, a front downward-looking visible light detector, a downward-looking infrared detector, and a downward-looking visible light detector; The front downward infrared detector and the downward infrared detector are used to collect infrared images formed by infrared energy reflected by the target calibration object through infrared lenses and detectors, and the infrared image is used to extract infrared feature information of multiple target calibration objects through an infrared processing module, and the infrared feature information is transmitted to the image tracking unit; The front downward-looking visible light detector and the downward-looking visible light detector are used to collect the visible light image reflected by the target calibration object through the joint action of the visible light lens and the detector. The visible light image is processed by a visible light processing module to extract visible light feature information of multiple target calibration objects, and the visible light feature information is transmitted to the image tracking unit.

3. The servo control system according to claim 1, characterized in that: The target surface tracking distance includes: infrared tracking distance and visible light tracking distance; The image tracking unit is further used to calculate the infrared tracking distance between the target calibration object and the UAV platform according to the received infrared feature information and the preset infrared distance constraint condition: Among them, R IR To meet the infrared tracking distance of the minimum resolvable temperature difference, R TV is the visible light tracking distance that meets the requirements of the number of compressed lines, V is the visible distance, MRTD is the minimum resolvable temperature difference of the infrared camera, ΔT is the background temperature difference of the target calibration object, m is the diffusion coefficient, f′ is the focal length of the infrared camera lens, H is the size of the target calibration object, N is the vertical resolution of the infrared camera, h is the target height of the infrared camera, n is the number of compressed lines, ω b is the half field of view of the infrared camera; And according to the received visible light feature information and the preset visible light distance constraint condition, the visible light tracking distance between the target calibration object and the UAV platform is calculated: Among them, R TV is the visible light tracking distance that meets the target contrast requirement, V is the visible distance, MTF is the modulation transfer function of the objective lens of the visible light camera, and E is t is the illumination near the target calibration object, γ is the reflectivity of the surface of the target calibration object to visible light, T0 is the optical transmittance of the objective lens of the visible light camera, E d is the minimum illumination requirement of the target surface of the visible light camera, F = f' / D is the aperture number of the objective lens of the visible light camera, f' is the focal length of the objective lens of the visible light camera, D is the incident aperture diameter of the objective lens of the visible light camera, m is the dispersion coefficient, H is the size of the target calibration object, N is the vertical resolution of the visible light camera, ω b is the half field of view of the visible light camera, h is the target height of the visible light camera, and n is the required number of lines.

4. The servo control system according to claim 3, characterized in that: The gyro IMU unit includes: an IMU inertial component unit, an independent accelerometer and a controller processing unit; The IMU inertial component unit is used to collect three-axis angular rate information, three-axis acceleration information and other sensor data uploaded by the three-axis sensor, and output it to the controller processing unit; The independent accelerometer is used to output independent acceleration data to the controller processing unit; The controller processing unit is used to read the data of the IMU inertial component unit and the independent accelerometer, so as to perform temperature calibration on the three-axis sensor by temperature segmentation to obtain corrected three-axis angular rate information, three-axis acceleration information and independent acceleration data; perform initial viewing angle calculation, data fusion and compensation on the corrected three-axis angular rate information, three-axis acceleration information and independent acceleration data to obtain three-axis attitude angle information, and periodically output the corrected three-axis angular rate information and the three-axis attitude angle information to the servo control unit.

5. The servo control system according to claim 1, characterized in that: The three-axis servo motor includes: a roll servo motor, an azimuth servo motor and a pitch servo motor; The roll servo motor is used to adjust the posture and position of the unmanned platform in the roll direction according to the roll control signal generated by analyzing the servo control signal; The azimuth servo motor is used to adjust the posture and position of the unmanned platform in the azimuth direction according to the azimuth control signal generated by analyzing the servo control signal; The pitch servo motor is used to adjust the posture and position of the unmanned platform in the pitch direction according to the pitch control signal generated by analyzing the servo control signal; The roll servo motor, the azimuth servo motor and the pitch servo motor are directly driven to perform three-axis servo linkage.

6. The servo control system according to claim 5, characterized in that: The position encoding unit includes: a roll encoder, an azimuth encoder and a pitch encoder; The roll encoder is used to control the roll servo motor to move to a specified position in the roll direction according to the roll rate by using the magnetoresistance effect; The azimuth encoder is used to control the azimuth servo motor to move to a specified position in the azimuth direction according to the azimuth rate by using the magnetoresistance effect; The pitch encoder is used to control the pitch servo motor to move to a specified position in the pitch direction according to the azimuth rate by using the magnetoresistance effect.

7. The servo control system according to claim 5, characterized in that: The servo control unit adopts ARM as a servo control processor, and is connected with the gyro IMU unit, the three-axis servo motor and the position encoding unit through a line-to-line aviation connector; The multi-closed-loop nested loop control includes: the inner loop stabilization loop control and the outer loop tracking loop control; The servo control unit is also used to solve the tracking performance error index of the target calibration object in the outer-loop tracking loop control according to the received device position, the posture information, the first navigation path and the preset correction network transfer function, and feed the tracking performance error index back to the inner-loop stabilization loop control for signal calibration, generate a locking tracking control signal, and feed the locking tracking control signal to the position encoding unit, the gyro IMU unit and the three-axis servo motor respectively.

8. The servo control system according to claim 7, characterized in that: The principle of the inner-loop stabilization loop control is as follows: in the stage of the UAV platform searching for the target calibration object, a multi-loop closed-loop system of a current loop, a speed loop and a position loop is used, the angular velocity of the motion of the stabilization platform mechanism relative to the inertial space is measured according to the rate gyro, and the stabilization loop PID controller is used to perform speed compensation on the angular velocity of the motion, so that the UAV platform is in a self-stabilizing state; when the UAV platform is in a self-stabilizing state, the position loop receives a given instruction in real time, and controls the search, locking and tracking of the target calibration object by the human-machine platform according to the given instruction; when the UAV platform locks the target calibration object, the small optical sensor assembly enters an automatic tracking mode, the position loop reference is added with a target deviation to perform position tracking, and a given speed loop reference is output, the speed loop performs a vector transformation on the given speed loop reference, and outputs three mutually 120° sinusoidal current signals to drive the three-axis servo motor to calibrate the deviation in real time, and complete the tracking control of the target calibration object; The principle of the outer-loop tracking loop control is: the imaging system of the small optical sensor assembly calculates the angular error signal of the target calibration object and transmits it to the inner-loop stabilization loop control; the inner-loop stabilization loop control adjusts the optical axis to move in the direction of reducing the error angle to form a closed-loop negative feedback, thereby completing the unmanned platform's tracking of the target calibration object at the line of sight angle.

9. A servo control method based on unmanned platform target tracking, characterized in that: The servo control system according to any one of claims 1 to 7 comprises: Acquire an optical image of a target calibration object according to a small optical sensor component of the UAV platform, and transmit the optical image to an image tracking unit to extract feature information of a plurality of target calibration objects; After the image tracking unit converts the received feature information into a photoelectric signal, the target surface tracking distance between the target calibration object and the UAV platform is calculated, and the tracking signal corresponding to the minimum value of the target surface tracking distance is output to the image navigation unit and the servo control unit respectively; parsing the tracking signal according to a path optimization strategy of the image navigation unit to generate a first navigation path, and transmitting the first navigation path back to the servo control unit step by step; The original posture information of the target calibration object is collected according to the three-axis sensor of the gyro IMU unit, the original posture information is calibrated by temperature segmentation to obtain the corrected posture information, and the posture information is periodically sent to the servo control unit; Acquire the absolute position of the start-up time of the three-axis servo motor according to the position encoding unit, start the inner loop stabilization loop control according to the absolute position control, and detect the device position information of the small optical sensor assembly, and transmit the device position information to the servo control unit to adjust the small optical sensor assembly to move to a specified position; The three-axis servo motor receives the servo control signal output by the servo control unit, so as to lock the posture and position of the unmanned platform in the rolling direction, azimuth direction and pitch direction respectively according to the posture and position of the target calibration object; The servo control unit adopts multi-closed-loop nested loop control to perform path optimization calculation on the received device position information, the posture information and the first navigation path to generate a servo control signal, and the servo control signal is fed along the multi-closed-loop nested loop.

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