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In this paper, a technique that can automatically detect and classify objects buried under the ground is proposed. The technique employs a ground‐penetrating radar that transmits electromagnetic waves in order to strike the objects and then receives the backscattering electromagnetic wave to perform signal processing. This signal processing is divided into four main steps as follows. First, preprocessing is used to reduce the clutter due to the effect of the media layer interface. Second, the late time of the scattering signal is estimated using a simple cross correlation. Third, a few successive poles are extracted from the scattering response at the estimated late time by using the short‐time matrix pencil method. Finally, the extracted poles are fed for object classification with different constitutions and/or shapes using a support vector machine. Simulations according to the practical situation in three southern provinces of Thailand to counter the improvised explosive devices were set up. The performance of the proposed technique was evaluated. The simulation results showed that the proposed technique can efficiently detect and classify buried objects for counter‐improvised explosive device operations in the military.

This paper proposes a conceptual technique for the simple estimation of the late‐time response for radar target identification without a priori knowledge of the target geometry or orientation. In the proposed technique, the cross correlation between the backscattering response and transmitted wave is performed. Peaks will occur in the cross‐correlation output when the transmitted wave is aligned with the same features in the received backscattering response. The commencement of the late‐time response corresponds with the peak resulting from a superimposed pattern between the transmitted wave and late‐time response. The matrix pencil method was exploited in order to extract the poles from the received backscattering response. Several simulations were performed to evaluate the performance of the proposed estimation technique. The simulation results confirmed the superiority of the proposed approach. In the special case of the transmission with a monocycle pulse, the commencement of the late‐time response can be automatically selected from the third peak of the resulting cross‐correlation output.

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