【作者】 盛磊；

【导师】 吴志勇；

【作者基本信息】 中国科学院研究生院(长春光学精密机械与物理研究所) ， 电路与系统， 2014， 博士

【摘要】 随着现代武器装备的飞速发展，对靶场光电测量设备的精度及作用距离等技术指标要求越来越高，针对不同测控任务，光测设备布站组网方式也随之变化，在具备固定观测位置测量方式，即固定站光测设备的基础上，研发机动性能好，布站简便灵活的车载不落地或船载动基座光测设备成为一种趋势。本文基于国内首台应用于靶场测量，且明确提出一定测量精度要求的某型船载光电测量设备，针对靶场光测设备最为重要的测角精度指标，提出了一套完整的精度分析和数据处理方法。在跟踪测量过程中，承载平台发生姿态和位置变化是船载设备与固定站光测设备的本质区别，本文从船载设备所特有的三轴姿态测量误差对光测设备测角误差的影响入手，建立综合3个姿态量和2个设备测角量的偏导误差模型，估算由姿态误差引入的测角误差，并分析多组典型姿态角所引入测角误差的规律，提出最优测量方案，通过限制设备测角范围使姿态测量误差造成的测角误差小于预设值，从而保证光测设备的测角精度。针对船上GPS测量位置与站址不在同一点的情况，提出由测量点坐标经船摇修正获得设备站址的算法，并据此分析修正后站址误差对测角精度的影响。综合各主要误差，估算设备测角精度，以及采用最优测量方案后的最优理论测角精度。提出对船载光测设备输出数据，包括三轴姿态角度，速度和加速度，编码器测角数据，图像及判读脱靶量，以及GPS差分定位坐标的完整数据处理方法，包括数据合理性检查，平滑滤波，插值和对齐，经一系列处理获得修正后测角数据和站址坐标。基于精度分析的结果和2个多元线性偏导误差函数，以统计回归方式估算平台姿态测量平均误差，总结采用一般多元和逐次回归算法存在的问题，提出附加观测方案，通过测量在多个预设测角范围内的合作靶标，将2个多元回归转化为4个一元回归，引入融合参数，并由任务段内双GPS差分定位数据计算该参数，将2组回归结果融合为1组姿态误差估计，整个回归过程覆盖全任务段的7个数据集合，保证了回归过程的稳定性。建立回归数据库和海况参数，存储和检索摇摆台上大量的实验数据和回归结果，在任务时进行附加观测，计算实测姿态误差估计，以任务时海况参数从数据库内获得此海况条件下的先验误差估计，以先验估计修正实测估计，并以修正值对任务段平台姿态角进行补偿，减小姿态测量误差，从而提高光测设备的测角精度。在摇摆台上多次多类型实验和最终的设备出海验收测试结果表明，本文对船载光测设备的精度分析是准确的，最优测量方案是有效的，数据处理方法满足要求，回归与补偿能够稳定减小设备测角误差。最终的结果为：在姿态测量精度（误差极大值）为航向≤72″，纵横摇≤24″，定位误差（极大值）≤5cm时，船载光测设备达到了最优理论测角精度（误差均方根）：方位≤38″，俯仰≤21″。更多还原

【Abstract】 With the rapid development of modern weaponry, the accuracy and operatingrange of optoelectronic measuring equipment (OME) in shooting range have becomeincreasingly demanding, OME’s station arranging and networking also changes fordifferent monitoring tasks, on the basis of a fixed station equipment (FOME) with afixed observer position, the research of the on-board or shipboard mobile equipmentwith good mobility and flexible station arranging have becoming a trend. Based on afirst domestic certain type of shipboard OME (SOME) applied to target rangemeasurement with clear indicators, a complete set of accuracy analysis and dataprocessing method is proposed for the most important indicator of angularmeasuring accuracy.In the process of tracking and measuring, the essential difference between theSOME and FOME is the attitude and position changes of the platform, fromSOME’s unique OME’s angle measuring error caused by triaxis attitude measuringerror, a partial derivative model include of3attitude and2measuring angle variableshas been built, measuring angle error caused by attitude error has been calcuated,and by analysis of the pattern of angle error caused by a few sets of typical attitudeangle value, a optimal measuring scheme has been proposed, which by making theangle error caused by attitude error less than the preset value through limiting anglemeasuring range, so as to ensure the SOME’s measuring angle accuracy. For onboard GPS loacation and site position are different, the algorithm to abtain siteposition through correting the measuring coordinates by ship’s attitude has beenproposed, and analyzing the measuring angle error caused by site position’s errorafter correting based on the algorithm. Estimating the measuring angle accuracy byconsidering all main error, and the theory of optimal measuring angel accuracy byusing optimal measuring scheme.A complete data processing method to deal with all SOME’s data has beenproposed, the data includs triaxis attitude angel, velocity and acceleration, angularecoder data, image and interpretation miss distance data, as well as GPS differentialpositioning coordinates, the method includes data plausibility check, smooth filtering,interpolation and alignment, and after those processing the modified angle data andsite position have been obtained.Based on the accuracy analysis and2multiple linear partial derivative errorfunctions, estimating the average attitude measuring error by using statisticalregression method, and the additional observation scheme is put forward bysummarizing the problems when using the general multiple and successiveregression algorithm, and transforming2multiple regression into4unary regressionby measuring some cooperative targets in the preset range, and bringing in a fusionparameter calculated by the dual GPS differential positioning data during the task, byusing the parameter fusing two groups of regression results as a set of attitudemeasuring error estimation, and the process of regression use7datasets covering thewhole task time, therefore to ensure the stability of regression process. A regressiondatabase and sea-state parameter have been established, and they are used to storeand retrieve a large number of experimental data and regression results measured onthe swing table, performing the additional observation in the task and calculating thereal-task attitude error estimates, getting the transcendental error estimates form thedatabase by the sea-state parameter in task, and correcting the real estimates bytranscendental estimates, and compensating for the attitude angel by using thecorrected estimates, reducing the attitude measuring error, so as to improve the SOME’s measuring angle accuracy.Data of several different types of experiments on the swing table and the finalacceptance test at sea show that: the SOME’s accuracy analysis is accurate, theoptimal measuring scheme is effective, the method of data processing meet therequirements, regression and compensation can steadily reduce the measuring angleerror. The final result is: when the attitude measurement precision(error’s maximum)is the heading≤72″, the roll and pitch≤24″, the positioning error(maximum)≤5cm,the accuracy of the Shipboard Optical Measuring Equipment reach the theory ofoptimal accuracy(error’s RMS): the azimuth≤38″, the pitch≤21″.更多还原