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Detection versus false alarm characterisation of a vision-based airborne dim-target collision detection system

机译:基于视觉的机载昏暗目标碰撞检测系统的检测与虚假警报表征

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摘要

This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.
机译:本文介绍了一种初步的基于飞行测试的探测距离与基于形态的隐马尔可夫模型滤波方法的基于视觉的机载弱目标碰撞检测的虚警性能表征。基于引人注目的机上碰撞场景数据,我们计算了系统运行特性(SOC)曲线,该曲线简明地说明了检测范围与误报率性能设计之间的权衡。这些初步的SOC曲线比以前的研究提供了更完整的暗目标检测性能描述(由于涉及实验困难,以前的研究仅限于非常短的飞行数据样本集,因此无法量化错误警报行为)。此处的初步调查基于从4次受控碰撞遭遇中收集的数据,并支持非目标飞行数据。这项研究表明,在蓝天背景条件下(约1.26 km),在蓝天背景条件下的正面探测范围约为2.22 km,而误报率低于每小时1.7次误报(即每36分钟少于一次) 。目前正在进行进一步的数据收集。

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