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首页> 美国政府科技报告 >Kalman Filter-Based Approach to Target Detection and Target- Background Separation in Ground Penetrating Radar Data
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Kalman Filter-Based Approach to Target Detection and Target- Background Separation in Ground Penetrating Radar Data

机译：基于卡尔曼滤波的探地雷达数据目标检测与目标背景分离方法

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The returns from shallowly buried targets measured using Ground Penetrating Radar (GPR) are typically obscured by a strong background signal comprised of the reflections from the air-soil interface. A Kalman filter-based approach is proposed to estimate this background signal and to separate it from the target return. In the absence of the target the filter operates using a 'quiescent state model' in which it computes the background estimate. A statistic based on measurement innovation is applied to detect the target position. Upon detection the state is augmented by a new component which allows for the change of the signal corresponding to the presence of the target return. The augmented state model is used until it is reverted to the quiescent model by another decision.

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