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Discrimination mode processing for EMI and GPR sensors for hand-held land mine detection

机译:用于手持式地雷检测的EMI和GPR传感器的区分模式处理

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Signal processing algorithms for hand-held mine detection sensors are described. The goals of the algorithms are to provide alarms to a human operator indicating the likelihood of the presence of a buried mine. Two modes of operations are considered: search mode and discrimination mode. Search mode generates an initial detection at a suspected location and discrimination mode confirms that the suspected location contains a land mine. Search mode requires that the signal processing algorithm generate a detection confidence value immediately at the current sample location and no delay in producing an alarm confidence is tolerable. Search mode detection has a high false-alarm rate. Discrimination mode allows the operator to interrogate the entire suspected location to eliminate false alarms. It does not require that the signal processing algorithm produce an alarm confidence immediately for the current sample location, but rather allows the system to process all the data acquired over the region before producing an alarm. This paper proposes discrimination mode processing algorithms for metal detectors (MDs), or electromagnetic induction sensors (EMIs), ground-penetrating radars (GPRs), and their fusion. The MD discrimination mode algorithm employs a model-based approach and uses the target model parameters to discriminate between mines and clutter objects. The GPR discrimination mode algorithm uses the consistency of detection as well as the shape of the detection peaks over several sweeps to improve the discrimination accuracy. The performances of the proposed algorithms were examined on a dataset collected at a government test site, and performance was compared with baseline techniques. Experimental results showed that the proposed method can reduce the probability of false alarm by as much as 70% at a 100% correct detection rate and performed comparable to the best human operator on a blind test with data collected at approximately 1000 locations.
机译:描述了用于手持式探雷传感器的信号处理算法。该算法的目的是向操作员提供警报,指示存在埋藏的地雷的可能性。考虑两种操作模式:搜索模式和判别模式。搜索模式在可疑位置生成初始检测,歧视模式确认可疑位置包含地雷。搜索模式要求信号处理算法立即在当前样本位置生成检测置信度值,并且不能容忍产生警报置信度的延迟。搜索模式检测的误报率很高。区分模式允许操作员询问整个可疑位置,以消除误报。不需要信号处理算法立即为当前样本位置产生警报置信度,而是允许系统在产生警报之前处理该区域上获取的所有数据。本文提出了针对金属探测器(MD)或电磁感应传感器(EMI),探地雷达(GPR)以及它们的融合的判别模式处理算法。 MD识别模式算法采用基于模型的方法,并使用目标模型参数来区分地雷和杂物。 GPR鉴别模式算法使用检测的一致性以及多次扫描中检测峰的形状来提高鉴别精度。在政府测试站点收集的数据集中检查了所提出算法的性能,并将性能与基准技术进行了比较。实验结果表明,该方法可以在100%正确检测率的情况下将错误警报的可能性降低多达70%,并且在大约1000个位置收集的数据的盲法测试中,其性能可媲美最佳操作员。

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