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A method for classifying underground targets and simultaneously estimating their burial conditions

机译:一种对地下目标进行分类并同时估计其埋葬条件的方法

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摘要

Ultra-wideband ground penetrating radar (GPR) systems are useful for extracting and displaying information for target recognition purposes. The frequency content of projected signals is designed to match the size and type of prospective targets and environments. Target signatures whether in the time, frequency, or joint time-frequency domains, will substantially depend on the target's burial conditions such as the type of soil, burial depth, and the soil's moisture content. Such returned echoes from two targets for several moisture contents and burial depths in a soil with known electrical properties were simulated earlier by using a Method-of-Moments (MoM) code. The signature template of each target was computed using a time-frequency distribution of the returned echo when the target was buried at standard conditions, namely, a selected depth in the soil with a selected moisture content. For any returned echo the relative difference between the likewise computed target signature and a template signature was computed. That signature difference, chosen as objective function, or cost function, could then be minimized by adjusting the depth and moisture content, now taken to be unknown parameters. This can be done using the differential evolution method (DEM) together with our target translation method (TTM). The template that gave the smallest value of the minimized objective function for the returned echo signified the classification, and the corresponding values of the depth and moisture parameters turned out to be good predictions of the actual target depth and soil moisture content. Here, we implement a more efficient and faster running version of this classification method on a stepped-frequency continuous-wave (SFCW) GPR system. We demonstrate the ability to classify mines or mine-like targets buried underground from measured GPR signals. The targets are buried either in- an indoor sandbox or in a test field at the Swedish Explosive Ordnance Disposal and Demining Center (SWEDEC) at Eksjo, Sweden.
机译:超宽带探地雷达(GPR)系统可用于提取和显示信息以进行目标识别。投影信号的频率内容旨在匹配预期目标和环境的大小和类型。无论是在时域,频域还是在联合时频域中,目标物的签名都将主要取决于目标物的埋葬条件,例如土壤的类型,埋藏深度和土壤的水分含量。通过使用矩量法(MoM)编码,可以较早地模拟从两个目标返回的,具有已知电特性的土壤中几种水分含量和埋藏深度的回波。当目标被埋在标准条件下,即具有选定水分含量的土壤中选定深度时,使用返回回波的时频分布来计算每个目标的签名模板。对于任何返回的回波,都计算了同样计算出的目标签名和模板签名之间的相对差。然后可以通过调整深度和水分含量(现在被视为未知参数)来最小化被选为目标函数或成本函数的特征差异。可以使用差分进化方法(DEM)和我们的目标翻译方法(TTM)来完成。对于返回的回波,给出最小目标函数最小值的模板表示分类,并且相应的深度和湿度参数值可以很好地预测实际目标深度和土壤湿度。在这里,我们在步进频率连续波(SFCW)GPR系统上实现了此分类方法的更高效,运行速度更快的版本。我们展示了根据测得的GPR信号对埋在地下的地雷或类雷目标进行分类的能力。这些目标被掩埋在室内沙箱中,或在瑞典埃克舍的瑞典爆炸物处置和排雷中心(SWEDEC)的测试场中。

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