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Time-Delay Estimation Using Ground-Penetrating Radar With a Support Vector Regression-Based Linear Prediction Method
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DOI：10.1109/TGRS.2017.2784567.png)
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Abstract
En 中文
Ground-penetrating radars (GPR) are widely used in media parameters' estimation and targets' localization. This paper focuses on time-delay estimation (TDE) using the GPR signal, which contains important information about the probed media structure. However, TDE tends to be a challenging task in GPR applications, in the scenarios of overlapping, coherent signals and limited snapshots. Forward-backward linear prediction (FBLP) is a high time-resolution method, which is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. Therefore, we propose to combine the theory of FBLP and SVR together to enhance the robustness of TDE in the case of coherent, overlapping signals as well as limited snapshots. The proposed method is tested with both numerical and experimental data. Both the results demonstrate the effectiveness of the proposed method.
Keywords:
Forward-backward linear prediction (FBLP)
ground-penetrating radar (GPR)
low snapshots
support vector regression (SVR)
time-delay estimation (TDE)
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