Radio Frequency (RF) Tomography is proposed to detect underground voids, such as tunnels or caches, over relatively wide areas of interest.The RF tomography approach requires a set of low-cost transmitters and receivers deployed randomly on the surface of the ground, or slightly buried. Using the principles of inverse scattering and diffraction tomography, it is possible to develop a simplified theory for below-ground imaging, thus revealing and locating buried objects and hidden targets.In this work, we introduce the principles and our motivations in support of RF tomography. Furthermore, we derive simple inversion schemes for sensors randomly deployed in a 3D region. Then, we assess limitations to performance, and discuss some system considerations. Finally, we demonstrate the effectiveness of RF Tomography by presenting images reconstructed via the processing of synthetic data.

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Three extensions to RF Tomography for imaging of voids under extended areas of regard are presented.These extensions are motivated by three challenges. One challenge is the lateral wave, which propagates in proximity of the air-earth interface, and represents the predominant radiation mechanism for wide area surveillance, sensing of denied terrains, or close-in sensing. A second challenge is the direct path coupling between Tx and Rx, that affects the measurements. A third challenge is the generation of clutter by the unknown distribution of anomalies embedded in the ground.These challenges are addressed and solved using the following strategies: 1) A forward model for RF Tomography that includes lateral waves expressed in closed-form (for fast computation); 2) a strategy that reduces the direct-path coupling between any Tx-Rx pair; 3) an improved inversion scheme that is robust with respect to noise, clutter, and high attenuation.An FDTD simulation of a scenario representing close-in sensing of a denied area is performed, and reconstructed images obtained using the improved and the classical model of RF Tomography are compared.

Radio-frequency (RF) tomography is extended for imaging underground structures and tunnels assuming rough terrain. The theory of RF tomography described in an earlier paper remains applicable, provided that a numerical Green's function is computed. An FFT-based and intrinsically parallel method for obtaining numerical Green's functions is described. This method is corroborated with explicit formulas and implemented for RF tomography. Simulated data computed using a finite-difference time-domain code are used to demonstrate performance.

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