Research

Gordon-CenSSIS Approach: Diverse Problems, Similar Solutions

The problem of imaging under a surface arises in a wide variety of contexts, and these problems are among the most difficult and intractable system challenges known. The Subsurface Sensing and Imaging (SSI) challenge is to extract information about a subsurface target from scattered and distorted waves received above the surface.

Imaging techniques, whether ultrasound sensors in tissue or electromagnetic probes in soil, can be described by the properties of the probe wave, the wave propagation characteristics of the medium and the surface, and the nature of the target and probe interaction. The framework describes not only underground imagery, but also underwater imaging, medical imagery inside the body, and 3-D biological microscopy inside a cell or collection of cells. Gordon-CenSSIS research impacts all of these areas.

The fundamental problem of SSI is to differentiate the target of interest from irrelevant clutter and scattered radiation, i.e., to distinguish a landmine from roots, stones, shell-casings, or ground-surface reflections. For example, in pulse-reflection ground-penetrating radar (GPR), the signal from a plastic cylinder could be obscured by the rough-surface reflection above the object. The task is to extract the signal from the complex scattered field of random surface irregularities.

An Integrated Systems Approach

A systems solution is required so that a priori information from the fundamental science of the target phenomenon and its interaction with the subsurface probe can be used to advantage in the processing, imaging, and decision steps that follow. Conversely, the physical probes and sensors can be optimally configured based on processing and recognition criteria. We have created an integrated "end-to-end" approach of the design of next generation SSI systems by teaming multi-disciplinary researchers who have deep knowledge of fundamental science with pragmatic systems engineers. Our three research thrusts (R1, R2, and R3) are engineered to address the barriers at every stage of this "end-to-end" systems approach.

• R1: Subsurface Sensing and Modeling explores the physics of promising new non-linear and multi-modal subsurface probes and develops accurate, efficient, wave-based forward modeling algorithms. These models are essential to the understanding of new subsurface probes and form the basis of the R2 inverse methods.
• R2: Physics-Based Signal Processing and Image Understanding creates and verifies inverse algorithms to infer subsurface details from measurement of above-surface sensors. This thrust focuses on optimizing the entire detection system, from the sensor data to the information desired, particularly addressing problems where the map from data to decision is non-linear or multi-modal.
• R3: Image and Data Information Management develops fast, efficient computational processing and visualization tools as well as means to organize, catalog, and retrieve data sets for algorithm verification.

We test and verify the advances in these research thrusts on fully characterized ground-truth data from our validation testbeds in the biological, medical, underground, and underwater regimes (BioBED, MedBED, SeaBED, and SoilBED). Finally, we apply our methods to real problems of societal significance. We have strong collaborative partnerships with our strategic affiliate institutions (MGH, MSKCC, INL, LLNL, and WHOI) to help us identify significant unsolved biomedical and environmental problems, and we have additional industry and government partners that ensure that our technological innovations are extracted and appropriately applied to the real world.

The Grand Challenge

The Gordon-CenSSIS grand challenge is to use our unifying framework and integrated systems approach to solve important real-world subsurface problems.We aim to achieve critical technical advances that will dramatically improve subsurface imaging for important societal problems. The vehicle for these advances is an Integrated Process for Looking under Surfaces (I PLUS). This engineered system contains the following elements:

• A unifying physical and analytical framework to produce optimal solutions to diverse SSI problems;
• Validating testbeds that combine unique sensors with innovative modeling and inversion algorithms;
• An integration of the sensors, lessons, and tools of subsurface system solutions from a wide range of real-world applications.

Products that we envision emanating from I PLUS include new multi-sensor instruments and capabilities such as a 3-D fusion microscope to observe subcellular reproduction processes, a portable, non-invasive breast scanning device that provides diagnostic readout of incipient cancer development and functions in real time, sea-floor visualization and satellite based coastal ecosystem erosion monitoring, and large-area buried waste mapping.