Optimal time-domain detection of a deterministic target buried under a randomly rough interface

Abstract

Abstract-We consider pulsed plane-wave scattering from targets buried under a rough air-ground interface. The properties of the interface are parametrized as a random process with known statistics, and therefore the fields scattered from a particular surface constitute one realization of an ensemble, characterized by corresponding statistics. Moreover, since the fields incident upon a buried target must first penetrate the rough interface, they and the subsequent scattered fields are random processes as well. Based on this understanding, an optimal detector is formulated, accounting for the clutter and target-signature statistics (the former due to scattering at the rough surface, and the latter due to transmission); the statistics of these two processes are in general different. Detector performance is compared to that of a matched filter, which assumes the target signature is known exactly (i.e., nonrandom). The results presented here, as a function of angle and polarization, demonstrate that there is often a significant gain in detector performance if the target signature is properly treated as a random process.

Iterative Time-Reversal Mirror Method for Imaging the Buried Object Beneath Rough Ground Surface

“…Unlike the traditional signal processing methods [5][6][7][8][9][10], the information of the propagation environment is well considered here. Unlike the conventional TRM methods which based on the assumption of flat ground or exactly given ground surface [22,23], the proposed method extracts the information of rough ground surface actively from the ground clutters.…”

“…Secondly, the soil attenuates the target echoes badly and makes the situation even worse [4]. In the traditional signal processing methods [5][6][7][8][9][10], the information of the ground surface is treated as clutters or noise to be canceled, for example, the optimal time-domain detection [5], the iterative frequency-domain clutter reduction [6], hidden Markov models for target classification [7], the ultrawide-band synthetic aperture radar (SAR) processing [8,9] and traditional Back Projection (BP) method [10], etc. All signal processing idea of these methods is based on data processing, which means they do not put the electromagnetic wave propagation environment into consideration.…”

Time-domain sensing of targets buried under a Gaussian, exponential, or fractal rough interface

“…The number of projections is determined empirically by studying the convergence of the detector output as a function of . In all the simulations presented in the next section, 40-50 projections were typically sufficient for convergence [3]. The ensemble of target scattered waveforms are computed via our MRTD scattering model, for the target of interest under realizations of the rough surface, the latter described by a prescribed statistical model.…”

“…The statistical analysis of time-domain electromagnetic scattering from a rough surface has been investigated previously [2], [3]. However, the vast majority of work on rough-surface scattering has been addressed in the frequency domain [4]- [7].…”

Subsurface Sensing of Buried Objects Under a Randomly Rough Surface Using Scattered Electromagnetic Field Data

“…A variety of methods have been provided in recent years to solve this category of problems in the frequency or time domain [7]- [16]. Many of these approaches are fully statistical [17]- [19] and are proper for the detection of objects but are not suitable for localization and characterization of them.…”