Aiming at the problem of reconnaissance and positioning of ground targets by airborne photoelectric detection equipment, this paper firstly studies the problem and model of multi-cooperative positioning based on distance measurement, and analyzes the factors affecting the positioning accuracy. Then, three solving methods of multicooperative target location based on distance measurement are proposed: least square algorithm, traditional particle swarm optimization algorithm and improved particle swarm optimization algorithm based on least square. The positioning accuracy and efficiency of the above three algorithms are simulated and compared in MATLAB, and the above algorithms are verified by flight test data. The experimental results show that the improved particle swarm optimization algorithm based on least squares has high computational accuracy and efficiency for solving the location equation of cooperative distance measurement.
MEMS-IMU is internally integrated with three-axis gyroscope and three-axis accelerometer, which are used to measure the angular velocity and acceleration information of the stabilized platform in three-dimensional space, respectively. With these information, attitude angle, velocity, displacement and other information can be obtained, and then the photoelectric stabilized platform can be controlled to ensure the stability of the optical axis in the inertial space. Because the gyro and accelerometer have certain error problems such as zero deviation, scale factor and orthogonality coupling, which will cause large errors to the measured results, this paper analyzes the error sources, establishes a deterministic error model, selects appropriate mathematical methods, determines the physical quantities to be measured and collects experimental data, so as to obtain the unknown coefficients in the model, The output angular velocity and acceleration error after calibration meet the control error accuracy requirements of the stable platform.
Air-to-ground photoelectric tracking platforms are often installed in unmanned aerial vehicles or various military weapons, and they play a major role in terrain mapping and military investigation. In the course of implementing tasks such as UAV reconnaissance and weapon strikes, the photoelectric tracking platform plays the role of identification and tracking. This paper proposes and compares the methods for calculating the position of the target detected by the platform based on the information of the photoelectric tracking platform attitude, the attitude of the platform carrier, such as the drone or the weapon body attitude, and the target distance. First, a conventional method is proposed, which is to obtain the target's latitude and longitude using coordinate transformation and other methods based on the information such as the target distance, platform and carrier attitude. In order to better meet the needs of rapidity, a method for obtaining the target latitude and longitude according to the distance of the target from the carrier in all directions is proposed. This method has a simple calculation process but a reduced accuracy. To ensure accuracy on the basis of improving real-time performance, consider For the spherical nature of the earth, a method of using spherical triangles to solve the target position is also proposed. Finally, use actual measured data to test and compare the practicability and accuracy of various methods. After testing, the three methods can achieve precise positioning of the target and meet the performance indicators.
The photoelectric tracking platform is often installed in various military and civilian equipment such as unmanned aerial vehicles, and has multiple high-precision detection and tracking equipment such as visible light and infrared thermal imaging cameras. In the detection process of various detection imaging systems, because the optical detection equipment is fixed on a carrier aircraft such as an unmanned aerial vehicle, the imaging system often rotates the detection image due to the rolling, pitch and yaw movement of itself and the carrier. In this regard, this article will analyze the principle of the image rotation problem caused by the photoelectric tracking platform in the detection and tracking of the target, and design an algorithm to eliminate the image rotation. First of all, this article clearly understands the purpose and indicators of rotation, carefully analyzes the reasons for the problem of image rotation, improves the definition of the relevant coordinate system and the relationship between them, and finally derives the value of the image rotation angle and performs the operation of eliminating the image rotation. And image post-processing operations. After testing, the designed algorithm can solve the problem of rotation of the image presented by the photoelectric tracking platform, and the processed image is easier to observe and capture manually or by related algorithms.
Kalman filtering is a filtering method based on minimum mean square error. It is a filtering algorithm formed by the state equation of the system, the observation equation and the statistical characteristics of the process noise of the system. It is widely used in the field of target tracking navigation guidance, etc. The Kalman filter requires an accurate state model of the known system, so it has great limitations in practical applications. Because Neural Networks have strong nonlinear mapping capabilities. In this paper, a variety of motion models are selected for reference and simulated by Matlab. The simulation results show that the prediction effect of the filter optimized by neural network is better than that of ordinary Kalman filter.
Micro-Scanning Mechanism (MSM) is the important component of super-resolution imaging/stabilization system. Through the MSM, the resolution of the infrared imaging system can be improved without increasing the total number of detection elements of the infrared focal plane detector, extending the working distance of the thermal imaging system and eliminating the detection blind zone caused by the small filling factor of the detector. This work was focused on the model-based design method of MSM, in order to improve the design efficiency and reduce design costs. The dynamic model of MSM was established, and the MSM design method based on this model was proposed. The structure and working principle of MSM were introduced, and the high-order resonance and axial coupling of MSM were analyzed. Based on this model, the main parameters of a certain MSM were designed. The simulation results meet the design requirements, effectively improving the design efficiency and reducing the design cost.
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