机载光电探测系统定位误差分析与标定研究

发布时间：2018-12-12 12:58

【摘要】：光电探测系统作为现代探测、成像系统的核心部件,主要作用是对目标的识别、定位、测量、跟踪。由于光机电一体化学科的快速发展,光电探测系统已普遍运用于侦测、定位、瞄准、跟踪、导航等各领域。定位精度作为系统工作性能的决定性评价指标,对于实现定位、成像、跟踪等工作具有重要意义,不仅关系图像的观测质量,还会影响到后续跟踪、瞄准的准确性。本文针对光电探测系统定位精度问题,分析了工作机理、总体结构与误差来源,对目标定位误差进行分析、建模、评价,并标定指向误差模型、修正指向误差。论文主要研究内容如下:一、总结了机载光电探测系统目标定位过程的原理、结构组成与综合性能评价指标。按照光电探测系统结构特征与目标定位流程,详细分析了目标定位误差中各分项误差的误差来源与分布规律。二、在总体结构与分项误差来源分析的基础上,需要建立关于机载光电探测系统目标定位过程的运动学综合模型。首先,将光电探测系统这个多轴复杂机械结构抽象成一个多体系统,利用多体系统理论,划分连续坐标系,按多体系统方法得到由若干齐次坐标变换矩阵组成的相邻坐标系间D-H(Denavit-Hartenberg)变换模型,进而推导出目标定位坐标的D-H基本参数模型。然后,若不考虑光电探测系统的具体结构,按照目标定位的大概运动过程,建立以李群、旋量理论为理论基础的局部指数积(Local POE)模型。同时,根据分项误差源分析和D-H基本参数模型,使用Monte Carlo方法与误差灵敏度公式,计算各分项误差灵敏度系数,对系统设计、装配与定位误差算法修正起到指导作用。三、为了达到高精度目标定位要求,需要修正定位误差中占主导作用的指向误差部分。首先,总结了光电探测系统指向误差的修正原理、研究流程、技术问题、实际应用领域。接着,基于传统线性误差因素的考虑,建立基本参数模型,使用最小二乘法标定模型参数。然后,基于线性误差因素与非线性误差因素共存的情况,建立半参数模型,使用补偿最小二乘法与双三次样条插值相结合的标定算法标定模型参数。最后,针对机载光电探测系统指向误差Local POE模型,改进现有智能算法,融合模拟退火与粒子群算法,并标定Local POE模型。四、搭建实验平台,针对某型光电探测系统进行指向误差分离、标定与修正实验,分离指向误差得到样本数据。分别使用最小二乘标定算法、补偿最小二乘法与双三次样条插值相结合的标定算法、基于模拟退火的粒子群优化算法分别标定光电探测系统指向误差基本参数模型、半参数模型与Local POE模型的待定参数。实验结果表明,各标定算法都能显著提高光电探测系统指向精度与稳定性。
[Abstract]:As the core component of modern detection and imaging system, photoelectric detection system is mainly used to identify, locate, measure and track targets. With the rapid development of optical and mechanical integration, photoelectric detection system has been widely used in detection, positioning, aiming, tracking, navigation and other fields. As the decisive evaluation index of system performance, positioning accuracy is of great significance to the realization of positioning, imaging and tracking. It not only relates to the quality of image observation, but also affects the accuracy of follow-up tracking and aiming. In this paper, the working mechanism, the overall structure and the error source of the photoelectric detection system are analyzed. The target positioning error is analyzed, modeled, evaluated, and the pointing error model is calibrated and the pointing error is corrected. The main contents of this paper are as follows: firstly, the principle, structure composition and comprehensive performance evaluation index of airborne photoelectric detection system are summarized. According to the structural characteristics of photoelectric detection system and the flow chart of target location, the error source and distribution of the sub-errors in target positioning error are analyzed in detail. Secondly, based on the analysis of the overall structure and the source of the sub-error, the kinematics synthesis model of the target location process of the airborne photoelectric detection system should be established. First of all, the photoelectric detection system, a multi-axis complex mechanical structure, is abstracted into a multi-body system, and the theory of multi-body system is used to divide the continuous coordinate system. The D-H (Denavit-Hartenberg) transformation model of adjacent coordinate system composed of several homogeneous coordinate transformation matrices is obtained according to the multi-body system method, and the D-H basic parameter model of target positioning coordinates is derived. Then, the local exponential product (Local POE) model based on Li Qun and spinor theory is established according to the general moving process of target location without considering the specific structure of the photoelectric detection system. At the same time, according to the error source analysis and D-H basic parameter model, Monte Carlo method and error sensitivity formula are used to calculate the sensitivity coefficient of each component error, which plays a guiding role in system design, assembly and positioning error algorithm correction. Third, in order to meet the requirement of high precision target positioning, we need to correct the pointing error which plays a leading role in the positioning error. Firstly, the correction principle, research flow, technical problems and practical application of the pointing error of photoelectric detection system are summarized. Then, based on the consideration of the traditional linear error factors, the basic parameter model is established, and the model parameters are calibrated by the least square method. Then, based on the coexistence of linear error factors and nonlinear error factors, a semi-parametric model is established, and the calibration model parameters are calibrated by using the method of compensating least square and bicubic spline interpolation. Finally, aiming at the pointing error Local POE model of airborne photoelectric detection system, the existing intelligent algorithm is improved, the simulated annealing and particle swarm optimization algorithm are fused, and the Local POE model is calibrated. Fourthly, the experiment platform is built to separate the pointing error for a certain photoelectric detection system, calibrate and correct the experiment, and separate the pointing error to get the sample data. Using least square calibration algorithm, compensating least square method and bicubic spline interpolation, particle swarm optimization algorithm based on simulated annealing is used to calibrate the basic parameter model of pointing error of photoelectric detection system, respectively. The undetermined parameters of semi-parametric model and Local POE model. The experimental results show that each calibration algorithm can significantly improve the pointing accuracy and stability of the photoelectric detection system.
【学位授予单位】：中国科学院研究生院(长春光学精密机械与物理研究所)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：V241

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