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Adapting Physically Complete Models to Vehicle-Based EMI Array Sensor data: Data inversion and Discrimination Studies

机译:使物理完整模型适应基于车辆的EMI阵列传感器数据:数据反演和判别研究

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This paper reports vehicle based electromagnetic induction (EMI) array sensor data inversion and discrimination results. Recent field studies show that EMI arrays, such as the Minelab Single Transmitter Multiple Receiver (STMR), and the Geophex GEM-5 EMI array, provide a fast and safe way to detect subsurface metallic targets such as landmines, unexploded ordnance (UXO) and buried explosives. The array sensors are flexible and easily adaptable for a variety of ground vehicles and mobile platforms, which makes them very attractive for safe and cost effective detection operations in many applications, including but not limited to explosive ordnance disposal and humanitarian UXO and demining missions. Most state-of-the-art EMI arrays measure the vertical or full vector field, or gradient tensor fields and utilize them for real-time threat detection based on threshold analysis. Real field practice shows that the threshold-level detection has high false alarms. One way to reduce these false alarms is to use EMI numerical techniques that are capable of inverting EMI array data in real time. In this work a physically complete model, known as the normalized volume/surface magnetic sources (NV/SMS) model is adapted to the vehicle-based EMI array, such as STMR and GEM-5, data. The NV/SMS model can be considered as a generalized volume or surface dipole model, which in a special limited case coincides with an infinitesimal dipole model approach. According to the NV/SMS model, an object's response to a sensor's primary field is modeled mathematically by a set of equivalent magnetic dipoles, distributed inside the object (i.e. NVMS) or over a surface surrounding the object (i.e. NSMS). The scattered magnetic field of the NSMS is identical to that produced by a set of interacting magnetic dipoles. The amplitudes of the magnetic dipoles are normalized to the primary magnetic field, relating induced magnetic dipole polarizability and the primary magnetic field. The magnitudes of the NSMS are determined directly by minimizing the difference between measured and modeled data for any known object and any type of EMI sensor data. The EMI array data are inverted via the combined NV/SMS and differential evolution inversion method that uses a search scheme to estimate the location of the target. First, the applicability of the NV/SMS and DE algorithms to STMR and GEM-5 data sets is demonstrated by comparing the modeled data against the actual data, and finally the discrimination studies are conducted using as discrimination parameters the total NV/SMS and the principal axis of the induced magnetic polarizability tensor for each target.
机译:本文报告了基于车辆的电磁感应(EMI)阵列传感器数据反演和判别结果。最近的现场研究表明,EMI阵列(例如Minelab单发射机多接收器(STMR)和Geophex GEM-5 EMI阵列)提供了一种快速安全的方法来检测地下金属目标,例如地雷,未爆炸弹药(UXO)和掩埋炸药。阵列传感器灵活且易于适应各种地面车辆和移动平台,这使其在许多应用中对安全且具成本效益的检测操作非常有吸引力,包括但不限于爆炸物处理,人道主义爆炸物和排雷任务。大多数最新的EMI阵列都可测量垂直或全矢量场或梯度张量场,并基于阈值分析将其用于实时威胁检测。实际实践表明,阈值检测具有较高的误报率。减少这些误报的一种方法是使用EMI数值技术,该技术能够实时反转EMI阵列数据。在这项工作中,一个物理上完整的模型(称为归一化体积/表面磁源(NV / SMS)模型)适用于基于车辆的EMI阵列(例如STMR和GEM-5)数据。 NV / SMS模型可以被视为广义体积或表面偶极子模型,在特殊的有限情况下,它与无穷小偶极子模型方法相吻合。根据NV / SMS模型,对象通过一组等效的磁偶极子在数学上进行建模,这些等效偶极子分布在对象内部(即NVMS)或对象周围的表面上(即NSMS)。 NSMS的散射磁场与一组相互作用的磁偶极子产生的磁场相同。磁偶极子的振幅被归一化到初级磁场,这与感应磁偶极子极化率和初级磁场有关。通过最小化任何已知物体的测量数据和建模数据之间的差异以及任何类型的EMI传感器数据,可以直接确定NSMS的大小。 EMI阵列数据通过结合NV / SMS和差分进化反演方法进行反演,该方法使用搜索方案来估计目标的位置。首先,通过将建模数据与实际数据进行比较,论证了NV / SMS和DE算法在STMR和GEM-5数据集上的适用性,最后,使用总NV / SMS和每个目标的感应磁极化率张量的主轴。

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