This SBIR research project will extend surface electrical impedance spectroscopy and tomography to identify and classify objects, such as tunnels, hidden deep in soil or other infrastructure media. Innovative shape-based approaches will be developed to address the under-determined and ill-posed nature of the inversion problem. Advanced finite element techniques will be used to produce a forward model of the sensor, ancillary electronics, and the soil medium. Maximum use of a-priori knowledge will be used to condition and guide the inversion approach. The new inversion algorithms will be supported by new sensor and electronics configurations combined with improved signal processing to improve signal to noise ratio and reduce the effects of noise. A surface following linear array of geo-referenced sensing elements will be scanned over the surface to produce the measurement data. Impedance spectroscopy will use the highly dispersive characteristic of soil in the radio frequency band to provide additional information to improve discrimination of target objects.
The newly developed technology will provide a framework that can be directly applied to other sensing modalities, such as acoustic and seismic, and other applications, such as preservation of historic infrastructure. Rapid, non-invasive identification of anomalies in materials is a problem with wide application to construction, infrastructure mapping and preservation, foodstuffs preparation, and biological systems.
