Flash-LADAR辅助惯性导航仪的实现

M. Uijt de Haag, D. Venable, A. Soloviev
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引用次数: 6

摘要

GPS辅助惯性系统可以在许多作战场景中提供高精度的位置和姿态信息;然而,它们的使用仅限于GPS信号可用的环境。另一种方法可以基于Flash-LADAR或其他3D成像传感器数据在没有gps的环境中导航,或者将这些3D成像传感器与惯性测量单元集成在一起。Flash LADAR(激光雷达)和3D成像技术由激光或透射光源组成,该光源通过相对较大的孔径发射,再加上焦平面阵列探测器,能够创建观测场景的ldquoimagerdquo,其中每个像素不仅具有相关的强度值,而且还具有对被观测对象的距离的估计。随着最近短程低成本(10万美元)3D成像仪技术的发展,使用这种技术来辅助低成本惯性测量单元(IMU)已经变得切实可行并引起了人们的极大兴趣。目前的低成本3D成像仪或Flash LADAR技术能够在30 Hz帧速率下以5 mm深度分辨率实现100倍以上的100像素分辨率。从这个3D范围内,可以高精度地测量由墙壁创建的平面,平面相交处创建的线以及线相交处的点等特征。本文将重点讨论三维成像仪特征提取性能方面的问题,并为基于图像和imu的特征关联和集成架构奠定基础。来自室内测试的数据将用于说明本文中解释的一些概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of a Flash-LADAR aided inertial navigator
GPS aided inertial systems can provide high accuracy position and attitude information in many operational scenarios; however, their use is limited to environments where GPS signals are available. An alternative method can be based on the use of Flash-LADAR or other 3D imaging sensor data to navigate in the GPS-devoid environments or the integration of these 3D imaging sensors with an inertial measurement unit. Flash LADAR (laser radar) and 3D imaging technology consists of a laser or light transmission source that is being emitted over a relatively large aperture coupled with a focal plane array detector capable of creating an ldquoimagerdquo of the observed scene where each pixel not only has an associated intensity value but also an estimate of the range to the observed object. With the recent development of short-range low-cost (Lt $10 k) 3D imager technology, the use of such technology to aid a low-cost inertial measurement unit (IMU) has become practical and of great interest. Current low-cost 3D imager or Flash LADAR technology is capable of greater than 100 times 100 pixel resolution with 5 mm depth resolution at a 30 Hz frame rate. From this 3D range, features such as planar surfaces created by the walls, lines created where planes intersect, and points from the intersection of lines can be measured with high precision. In this paper we will focus the discussion on the 3D imager feature extraction performance aspects and lay the basis for the image and IMU-based feature association and integration architecture. Data from an indoor test will be utilized to illustrate some of the concepts explained in this paper..
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