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Real-time implementation of an asynchronous vision-based target tracking system in an unmanned aerial vehicle

机译:无人机中基于视觉的异步目标跟踪系统的实时实现

摘要

Currently, small unmanned aerial vehicles developed by NPS have been able to locate and track stationary and moving targets on the ground. New methods of continuous target tracking are always being developed to improve speed and accuracy, ultimately aiding the user of the system. This thesis describes one such method, utilizing an open loop filter as well as an external correction source: Perspective View Nascent Technologies (PVNT). While the PVNT correction can theoretically improve the accuracy from 20-30 meters to 1-2 meters, it does have a disadvantage in that the target position updates are delayed anywhere from 1-10 seconds. In order to account for the delay, an asynchronous filter is used to update the target position data given the external position correction from PVNT. Two cases have been tested including the general filter and one that utilizes a road model in the calculations. While an earlier thesis developed the basic simulation for the system, this thesis discusses improvements and corrections to the simulation model as well as the necessary steps for real-time implementation.
机译:目前,由NPS开发的小型无人机已经能够在地面上定位并跟踪静止和运动的目标。一直在开发新的连续目标跟踪方法,以提高速度和准确性,最终帮助系统用户。本文介绍了一种利用开环滤波器以及外部校正源的方法:Perspective View Nascent Technologies(PVNT)。虽然从理论上讲PVNT校正可以将精度从20-30米提高到1-2米,但它确实有一个缺点,就是目标位置更新会延迟1-10秒。为了解决延迟问题,在通过PVNT进行外部位置校正的情况下,使用异步滤波器更新目标位置数据。测试了两种情况,包括通用过滤器,一种在计算中利用道路模型。虽然较早的论文开发了系统的基本仿真,但本文讨论了对仿真模型的改进和修正以及实时实现的必要步骤。

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  • 作者

    Schenk Michael A.;

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  • 年度 2007
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