Compressive Sensing (CS) is a recently developed technique, which can reconstruct the sparse signal with an overwhelming probability, even though the signal is sampled at highly sub-Nyquist rate. Based on the observation that the electromagnetic scattering structure (ESS) of a metal landmine is composed of two scattering centers, whose geometrical parameters are tightly related to its physical dimensions, a new physics-based landmine discrimination approach is proposed in this paper. Firstly, the approach uses the Multi-Measurement Iterative Pixel Discrimination method to reconstruct the landmine's ESS in noisy environments. Secondly, the geometrical parameters of the landmine's ESS are extracted from the sparse image. Thirdly, landmine discrimination is conducted according to the measured geometrical features and apriori knowledge. Finally, the field experimental results demonstrate the effectiveness of the proposed approach.
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