Photoelectric Tracking System Research Articles

Mathematical Nonlinear Graph Theory Topology Layer Model for Photoelectric Tracking System

The performance of the photoelectric tracking system mainly depends on the tracking accuracy. In order to achieve the purpose of high precision tracking, controlling the power dragging device, the main component of the photoelectric tracking system, is the main means to achieve this purpose. In order to improve the tracking speed and accuracy of photoelectric tracking systems, the author proposed a mathematical nonlinear graph theory topology layer model for photoelectric tracking systems. The topology layer model and the motion node servo mechanism model of the photoelectric tracking system are studied, and the two-stage disturbance sources that affect the tracking stability are analyzed. The results show that the interference estimation error range designed by the author reaches 0.003 through comparison, it can be seen that the estimation error designed by the author is significantly smaller than the ESO estimation error, and the buffeting is small. Through comparison, it can be concluded that the estimation error of the algorithm and the disturbance observer designed by the author are significantly smaller than the estimation error of ESO, and the buffeting is small, and they have strong compensation ability for the disturbance of different frequencies. The interference observer can quickly and accurately estimate the interference and prove its stability. The effectiveness of the proposed observer and disturbance observer is fully demonstrated. The finite time integrated site selection mode disturbance observer (F-ISMDOB) is designed to quickly estimate and compensate for equivalent interference, and effectively improves the anti-interference performance of the system structure layer.

Fixed-time convergence ZNN model for solving rectangular dynamic full-rank matrices inversion

The Moore–Penrose inverse of dynamic matrices has found widespread application and has garnered significant attention. The zeroing neural network (ZNN) has proven to be an effective solution for computing the Moore–Penrose inverse in dynamic matrices. This paper proposes a novel unified fixed-time ZNN (UFTZNN) model designed to achieve fixed-time convergence and solve both left and right inverse problems using a single model. Theoretical analysis of the convergence and robustness of the UFTZNN model is rigorously presented. Numerical simulations comparing the UFTZNN with existing ZNN models confirm its superiority in addressing left and right inverse problems, convergence time, and robustness. The UFTZNN model is applied to the inverse kinematic tracking problem of a six-degree-of-freedom manipulator-based photoelectric tracking system to demonstrate its potential applications and effectiveness.

Special Issue on Advances in Photoelectric Tracking Systems: An Overview

The photoelectric tracking system, which consists of optical, mechanical, electrical, and computer components, is in charge of tracking targets at extremely long distances [...]

Comparative Analysis of the Effect of Cutting Piezoelectric Ceramics on Optically Oriented Compensation Capability

In a photoelectric tracking system, a deformable mirror can be used to adjust the transmission path of a light beam to achieve accurate measurement and tracking of the target position. The single-piezoelectric-sheet deformable mirror is a commonly used wavefront correction device with outstanding advantages, such as its simple structure, low cost, and easy preparation. However, it usually has a large cross-linking value and a weak ability to correct higher-order wavefront aberrations. To solve this problem, a novel single-piezoelectric-sheet deformable mirror driving structure is proposed in this paper, in which the coupling between the driving units is weakened by laser cutting the piezoelectric ceramics along the electrode gaps to reduce the cross-linking value of the deformable mirror. In order to verify the effectiveness of this driving structure, this paper takes the 85-unit single-piezoelectric-sheet deformable mirror as an example and simulates the influence function for different cutting depth conditions. The simulation results show that the cross-linking value between neighboring drive units decreases significantly as the piezoelectric-ceramic-laser cutting depth of the drive electrode gap increases. When the piezoelectric ceramic was laser cut to a depth of half of the overall thickness, the cross-linking value decreased by 6.8%.

Hybrid Nonsingleton Fuzzy Strong Tracking Kalman Filtering for High Precision Photoelectric Tracking System

This article presents a hybrid nonsingleton fuzzy strong tracking Kalman filter (H-NFSTKF) for the high-precision photoelectric tracking system (PTS) to improve state estimation performance in the complex case of measurement noise change and velocity state mutation. The proposed H-NFSTKF is composed of three parts: A strong tracking Kalman filter (STKF) and two fuzzy logic systems (FLSs) including a singleton FLS (SFLS) and a nonsingleton FLS (NFLS). To compare different nonsingleton firing strength approaches, standard method (Sta-NS), centroid-based method (Cen-NS), similarity-based method (Sim-NS), and subsethood-based method (Sub-NS) are discussed. In addition, two traditional control strategies, i.e, dual closed-loop and feed-forward control, as well as four filtering methods including Kalman filter (KF), STKF, fuzzy STKF (FSTKF), and single nonsingleton FSTKF (S-NFSTKF) are also designed to show the superiority of the proposed H-NFSTKF. Finally, by means of comparative simulation analyses and experimental results, the excellence of the proposed H-NFSTKF is verified.

Application of bilateral sliding mode predictive compound control in photoelectric tracking system

This article focuses on the stable imaging problem of photoelectric imaging system that depends on the synchronous rotation of mirror and detector. When there is a relative movement between the mirror and the detector, it will cause image rotation, resulting in information loss and reduced tracking accuracy. It is difficult to achieve the high-precision synchronous movement between the mirror and the detector using the traditional unilateral control method. Different from the existing results of the traditional unilateral tracking method, this paper introduces the bilateral control structure in the field of robot teleoperation and proposes a novel compound control strategy based on the bilateral control structure. First, a robust disturbance observer is proposed to reduce the disturbance of the system, in which a new robust H∞ mixed sensitivity control algorithm is designed to optimize the filter. Then, a novel generalized sliding mode predictive (NSMP) control strategy based on hybrid reaching law is proposed to eliminate the image rotation problem caused by time delay. Besides, a new power function is designed to replace the switching function in the reaching law to reduce chattering. Finally, the finite time theory and the Lyapunov theory are used to prove that the proposed control scheme can ensure that the system is stable and reach its steady state in a finite time. The simulation results show the effectiveness of the proposed control scheme.

Friction model identification and compensation strategy for photoelectric tracking system

Friction model identification and compensation strategy for photoelectric tracking system

Fractional-Order Active Disturbance Rejection Control with Fuzzy Self-Tuning for Precision Stabilized Platform.

In this paper, a novel fractional-order active disturbance rejection control with fuzzy self-tuning method (FSFOADRC) is proposed for photoelectric tracking system (PTS). Firstly, aiming at the internal uncertainty of PTS and external disturbance, a fraction-order extended state observer (FOESO) is designed, and the FOESO can transform the plant into a simple form, which greatly simplifies the mathematical model. Secondly, a fuzzy regulator is applied to the proportion-differentiation controller (PD), increasing the flexibility and adaptivity of the controller. In addition, the stability of the whole control system can be guaranteed. Eventually, numerical comparative simulations are implemented to verify the feasibility and superiority of the proposed method. Compared with the integral-order active disturbance rejection control (IOADRC), fractional-order active disturbance rejection control (FOADRC) without the fuzzy regulator and proportion-integration-differentiation (PID) controller, the proposed method performs better with faster response, smaller overshoot, and stronger disturbance suppression capability.

Developing a dual axis photoelectric tracking module using a multi quadrant photoelectric device

To determine the distance, presence, or absence of the object by using a transmitter or photoelectric receiver the photoelectric device is used. The potential of a photovoltaic (PV) panel to produce power is roughly dependent on the intensity of sunlight falling on it. This study planned and constructed a dual-axis solar programmable logical controller (PLC) based automatic tracking system, as well as its management and signal conditioning. The suggested automated monitoring system regulates the elevation and orientation angles of solar panels to keep them transverse to the sun at all times. The capacity of the pouring source to right path the position of the sunlight is detracting for the proper functioning of warm excited lasers, which is an essential resource of absorbing light part of every 24 h. The current pursuing electronics, in another way, has poor strength and pursuing accuracy. To view the same issue, a photoelectric tracking system accompanying qual pivot is ingrained. The proposed system is based on the idiosyncratic multi quadrant photoelectric detector is implemented and a tracking scheme with a solar orbital method is included. The cosmic at fixed intervals monitoring device’s control design, in pair with the fine bringing into the harmony of the multi-one of four equal parts photoelectric indicator, substantially increases the effectiveness of the projected model. The pump source’s accurate positioning and tracking capabilities to the solar azimuth enable the pump source’s system reliability.

Data Detection Device for Turret Motion Image Using Photoelectric Tracking Control System and Its Performance Analysis

The photoelectric tracking control system is a system composed of photoelectric signal detection, signal processing, servo control system and mechanical structure, which plays a crucial role in the field of target tracking. The turret needs to be tested when it leaves the factory, including high-low direction, horizontal direction, aiming speed and other indicators. Moreover, there are large errors in the manual testing methods such as recorder and recording pen, so the photoelectric tracking device is used for the detection of the turret system. First, the hardware of the photoelectric tracking system is designed, including the main control circuit, peripheral expansion module circuit, intelligent power drive circuit and a detection circuit. The system is connected to the camera. The optical signal sent by the system will hit the fixed target. The upper computer will track the trajectory of the light in real-time and then track the trajectory of the turret to obtain the coordinates of the optical signal and the offset angular velocity of the turret. First, color conversion is conducted on the image data collected by photoelectric tracking through the weighted average method. The complete motion path of the turret is obtained through an image denoising algorithm to obtain the motion speed of the turret. In the test, the photoelectric tracking system is first connected to the motor, and enters a stable state when the motor rotor is 80 ms. The rotor speed is faster. When the rotor speed decreases, the system’s current ripple is large, and then decreases rapidly. After the control system is installed in the turret, its display can be driven by FPGA programming. The VGA display of influence time is set, the editing program is downloaded to the FPGA development board, and the gray image of the turret motion track can be seen through the VGA display.

Delay-Compound-Compensation Control for Photoelectric Tracking System Based on Improved Smith Predictor Scheme

High control bandwidth is usually restricted in a photoelectric tracking system (PTS) based on a Charge-Couple Device(CCD) with time delay, which hinders a good tracking performance. Generally, a model-based delay-compensation controller called Smith predictor (SP) can help increase the controller gain to promote the bandwidth by separating delay from the control loop. However, the performance promotion is insufficient because the delay still stays in the forward channel which causes errors between output and input. And the increase of the controller gain is still limited due to the effect of model mismatch on stability. In this paper, to solve the problems, a delay-compound-compensation control (DCCC) based on improved SP by trajectory prediction and velocity feedforward is proposed. The additional trajectory prediction is used to further eliminate the effect of delay existing in the forward channel. The additional velocity feedforward is used to further reform the transfer characteristics limited by the controller gain. A Kalman filter-based design method of trajectory prediction is presented and the optimal design principle of feedback and feedforward controllers is given in the face of model mismatch. Experiments demonstrate that the DCCC is valid and could greatly promote the tracking performance in the low frequency.

Research on Target Imaging Scene Simulation for Photoelectronic Tracking

Abstract In this paper, the 3D visual display and generation of target in optoelectronic tracking are researched by simulation. 3ds max software is used to model the target, the target model is converted into code files by Deep Exploration and added into the system model. The key point is to associate the target model track and size ratio with the actual target to approach the real battlefield environment. The image data provided by the scene building is tracked by the internal image processing algorithm of photoelectric tracking such as the Canny-based edge tracking. The experiment will compare the tracking of the same target in same algorithm but different backgrounds, and the same backgrounds but different algorithm. Result can see that through the experimental data, the application of the simulated sky background, and the proportion relationship between real target and target in simulation scene, provides a high authenticity data support for the image processing algorithm of self-propelled gun photoelectric tracking system.

Dynamic High-Type Interval Type-2 Fuzzy Logic Control for Photoelectric Tracking System

This paper proposes a dynamic high-type control (DHTC) method based on an interval type-2 fuzzy logic controller (IT2FLC), which is used in the photoelectric tracking system to improve the steady-state accuracy and response speed. Adding integrators to the traditional multi-loop feedback control loop can increase the system type, thereby speeding up the response speed and improving the steady-state accuracy, but there is a risk of integral saturation. Switching the type dynamically according to the system state can avoid integral saturation while retaining the advantages of the high-type. Fuzzy logic control (FLC) can dynamically change the output value according to the input change and has the advantages of fast response speed and strong ability to handle uncertainties. Therefore, in this paper, the FLC is introduced into the high-type control system, and the output of the FLC is used as the gain of the integrator to control the on-off to achieve the goal of dynamic switching type, which is successfully verified in the experiment. IT2FLC introduces a three-dimensional membership function, which further improves the FLC’s ability to handle uncertainties. From the experimental results, compared with T1FLC, IT2FLC’s ability to handle uncertainties is significantly improved. In addition, in order to speed up the calculation speed of IT2FLC, this paper proposes an improved type-reduction algorithm, which is called weighted-trapezoidal Nie-Tan (WTNT). Compared with the traditional type-reduction algorithm, WTNT has faster calculation speed and better steady-state accuracy, and has been successfully applied to real-time control systems, which has good engineering application value. Finally, in order to reduce the interference of human factors and improve the automation level of the system, a multi-population genetic algorithm (MPGA) is used to iteratively optimize the parameters of the FLC, which improves the output accuracy. On the experimental platform of the flexible fast steering mirror (FFSM), the control effects of the traditional controller, T1FLC and IT2FLC are compared, which proves that the IT2FLC-DHTC system has a faster response performance, higher steady-state accuracy, and stronger ability to handle uncertainties.

Rotation matrix error-decoupling methods for Risley prism closed-loop tracking

In a rotational double-prism photoelectric tracking system based on image feedback, the rotation angle of the prisms must be adjusted to correct the tracking error. This study proposes a rotation matrix error-decoupling method that removes the strong coupling between the tracking errors in the x and y directions and the prism rotation in the rotational double-prism tracking device. Based on the tracking error after decoupling, the rotations of the same and reverse directions are simultaneously applied to both prisms to achieve closed-loop tracking. The high precision and robustness of the method were confirmed in simulation and experimental tracking evaluations.

Target Recognition Algorithm Based on Optical Sensor Data Fusion

Optical sensor data fusion technology is a research hotspot in the field of information science in recent years, which is widely used in military and civilian fields because of its advantages of high accuracy and low cost, and target recognition is one of the important research directions. Based on the characteristics of small target optical imaging, this paper fully utilizes the frontier theoretical methods in the field of image processing and proposes a small target recognition algorithm process framework based on visible and infrared image data fusion and improves the accuracy as well as stability of target recognition by improving the multisensor information fusion algorithm in the photoelectric meridian tracking system. A practical guide is provided for the solution of the small target recognition problem. To facilitate and quickly verify the multisensor fusion algorithm, a simulation platform for the intelligent vehicle and the experimental environment is built based on Gazebo software, which can realize the sensor data acquisition and the control decision function of the intelligent vehicle. The kinematic model of the intelligent vehicle is firstly described according to the design requirements, and the camera coordinate system, LiDAR coordinate system, and vehicle body coordinate system of the sensors are established. Then, the imaging models of the depth camera and LiDAR, the data acquisition principles of GPS and IMU, and the time synchronization relationship of each sensor are analyzed, and the error calibration and data acquisition experiments of each sensor are completed.

Servo stabilization control algorithm in high-precision photoelectric tracking system

针对光电跟踪稳定平台系统中载机振动、系统参数摄动、摩擦力矩及外部扰动等因素直接影响光电跟踪系统稳定精度的问题，从伺服控制器控制角度出发抑制跟踪系统中的偏差，提高稳定精度，保证其在复杂环境下仍具有强鲁棒性。通过建立光电跟踪稳定平台系统的数学模型，分析干扰力矩、陀螺噪声及系统参数的变化对光电稳定平台的影响，设计了基于新型非线性扩张观测器（novel nonlinear extended state observer，NNESO）和滑模变结构控制（sliding mode varianle structure control，SMVSC）的复合控制策略。理论推导和仿真实验结果表明：此种复合控制策略具备对干扰力矩、外界扰动和系统结构参数摄动的完全适应性和强鲁棒性，对比无新型非线性扩张观测器的控制系统，证明其拥有更高的稳定精度和更快的动态响应，在补偿非线性方面具有良好的效果，可增强光电跟踪稳定平台的抗扰动能力。

Multi-optical axis parallelism calibration of space photoelectric tracking and aiming system

Multi-optical axis parallelism calibration of space photoelectric tracking and aiming system

Tracking System and Its Application in Unmanned Automobile Navigation Based on Sparse Photoelectric Sensor Network

Sensor tracking technology has broad prospects of application in the fields of smart home and environmental protection. The passive motion tracking method of sensor networks can realize the perception of location, temperature and other information without carrying sensor nodes. A sparse network tracking system based on infrared sensor nodes is proposed in this study, which can control the running automobiles with unmanned navigation. On the basis of the theory of diffraction, the way of spreading for wireless received signal strength (RSS) can be divided into "scattered waves" and "diffracted waves," which can be regarded as two components of infrared sensing wireless signals so as to further propose the RSS indicators of "long-term testing value" and "short-term test value." Based on these indicators, a measurement model based on diffraction effects and scattering effects is proposed, and an improved particle filter algorithm is used to update the motion tracking. The hardware design of each module in an unmanned vehicle includes the main controller, tracking circuit, serial port circuit, motor control circuit and infrared sensor control circuit of the car. In the experiment, the measurement accuracy of the tracking system based on the sparse infrared photoelectric sensor was first tested. In the simulation experiment, the long-term test value, the short-term test value and the actual measurement value were compared respectively. The test results show that the theoretical RSS value and the actual test result can be matched. Moreover, the infrared photoelectric tracking system is used to design the navigation control system of unmanned cars, helping the car to drive automatically through obstacle avoidance test and tracking obstacle avoidance test.

Novel Generalized Predictive Control for Photoelectric Tracking System Based on Improved Objective Function and Predictive Value Correction

Novel generalized predictive control (GPC) is proposed to deal with the problems of cumulative deviation of the predicted value, long control process and large noise that often encountered in conventional GPC. First, the objective function of GPC is improved based on integral time square error (ITSE) criterion, and the output expression under soft constraint is deduced. Then, the predicted value is corrected by adopting the integral weighting method, the convergence of which is demonstrated. Finally, both the simulations and hardware experiments are conducted in a practical photoelectric tracking system. It turns out that the superiority of the improved GPC in control precision, dynamic response and robustness is verified.

Extraction of Disturbance Signals Based on the Inertial Sensor with a Blind Source Separation Method

The inertial sensor is a key component in the photoelectric tracking system mounted on the moving platform, and its disturbance information extraction is a prerequisite for decoupling the system disturbance. In this paper, to get the specific signal of fs Hz, firstly, source signal of 2xfs Hz from the inertial sensor is needed. Then, single channel signal with frequency 2xfs is constructed into 2 aliased signals with the frequency of fs by down-sampling. Finally, a BSS (Blind Source Separation, BSS) algorithm is used to extract the disturbance signal in the aliased signals. Simulation results of ship borne data show that the algorithm can accurately extract the high-frequency disturbance signal of about 33 Hz in the aliased signals. The experimental results of the platform prove that the spectrum of the disturbance signal (10 Hz) and the spectrum of the target signal (0.1 Hz) do not overlap each other, and the correlation coefficient between the perturbation signal and the perturbation source signal is as high as 0.9976, which means the extraction of disturbance signal in the inertial sensor signals is realized.