Use of principal component images for classification of the EM response of unexploded ordnance
Use of principal component images for classification of the EM response of unexploded ordnance
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DOI：
10.1071/aseg2009ab102
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发表时间：
2009-09
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影响因子：
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通讯作者：
M. Asten
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文献类型：
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作者：
M. Asten
摘要 未爆炸弹药（UXO）的定位和识别是前军事射击场和轰炸目标区环境恢复的主要挑战。电磁方法广泛用于金属物体的定位，但是，成功引爆弹药后会产生大量废金属，因此必须区分弹药和各种尺寸的废料和弹药，以便有效定位、挖掘和清除未爆炸弹药。最近的几篇论文表明，详细的三分量电磁测量，然后反演电磁目标的偶极矩，可以有效地表征目标，但此类技术需要精确的数据，通常来自固定数据采集。从用于未爆炸弹药检测的移动地面平台获取的电磁数据通常含有大量运动引起的噪声，这限制了衰减曲线分析在目标表征中的有用性。我们使用来自新南威尔士州阿米代尔的澳大利亚空军纽霍姆未爆炸弹药测试场的数据集，结果表明：a）时间窗口数据图像无法成功区分不同类型的弹药，b）由于观察到的衰减曲线上的高噪声水平，自适应衰减指数方法无效，c）数据的主成分变换可以成功区分不同类型的弹药。该方法提供了对调查区域的异常进行初步分类和优先排序的工具，从而有助于制定有效的后续调查和现场清理计划。
Abstract The location and identification of unexploded ordnance (UXO) is a major challenge for environmental rehabilitation of former military firing ranges and bombing target areas. EM methods are in widespread use for the location of metal objects, however the presence of large quantities of scrap metal from successful detonation of munitions makes discrimination between munitions and scrap and munitions of various sizes a necessity in order for efficient location, digging and removal of UXOs to proceed. Several recent papers show that detailed three- component EM measurements followed by inversion to dipole moments of an EM target is effective in characterising a target, however such techniques require precise data, usually from stationary data acquisition. EM data acquired from a moving ground platform for UXO detection is typically high in motion-induced noise which limits the usefulness of decay-curve analysis in target characterization. We use a data set from the Australian Air Force Newholme UXO Test Range, Armidale, NSW, and show that a) images of time-window data are unsuccessful in discriminating between different types of munitions, b) adaptive decay index methods are ineffective due to high noise levels on the observed decay curves, and c) principal-component transforms of the data are successful in differentiating between different types of munitions. The method provides a tool for initial classification and prioritization of anomalies from a surveyed area, thus facilitating preparation of an efficient program of follow-up surveys and site clean-up.