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Filter and bounding algorithm development for a helmet mounted micromechanical inertial sensor array

机译:头盔式微机械惯性传感器阵列的滤波和边界算法开发

摘要

The technical evolution of head mounted displays (HMDs) and micromechanical inertial sensor arrays (MMISAs) have, until recently, occurred independently. This thesis details the development and simulation results of an inertial helmet-mounted head tracker for a T- 38 jet aircraft flight environment. Primary focuses are the state error estimation filter and the bounding algorithms used to estimate the head position and orientation during various flight conditions. Also included is a discussion of the application of the Draper MMISA to a cueing system for an HMD in a military air vehicle environment. Particular attention is paid to necessary requirements to meet pointing accuracies for fire control system handoff applications for the next generation of air to air missiles, such as the AIM-9X Sidewinder missile. A Markov process coupling technique used in this research is shown to achieve pointing accuracies of 4 to 11 milliradians. A generalization of the navigation filter to any number of inertial navigators with known relative positioning and attitude coupled using Markov process propagation matrices is also included, along with examples of future applications, in addition to helmet-mounted cueing systems, for vehicle applications.
机译:直到最近,头戴式显示器(HMD)和微机械惯性传感器阵列(MMISA)的技术发展都是独立发生的。本文详细介绍了用于T-38喷气飞机飞行环境的惯性头盔式头部跟踪器的开发和仿真结果。主要关注点是状态误差估计滤波器和用于估计各种飞行条件下头部位置和方向的边界算法。还讨论了Draper MMISA在军用飞机环境中HMD提示系统中的应用。特别注意必要的要求,以满足下一代空空导弹(如AIM-9X响尾蛇导弹)的火控系统切换应用的指示精度。研究中使用的马尔可夫过程耦合技术显示出达到4到11毫弧度的指向精度。除头盔安装的提示系统外,还将导航过滤器推广到使用马尔可夫过程传播矩阵耦合的具有已知相对定位和姿态的任意数量的惯性导航器,以及未来的应用示例,以及用于车辆应用的头盔式提示系统。

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