Through-wall imaging: Historical perspective and future directions

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Abstract

Through-wall imaging approaches are highly desirable for a range of applications including police, fire and rescue, first responder, and military applications. The ultimate desire of such systems is to provide detailed information in areas that cannot be seen through conventional measures. Borrowing from successes in geological and medical imaging environments, researchers have attempted to apply radio frequency (RF) and other sensing modes to penetrate wall materials and optimally estimate the content and structure of rooms and buildings. There are many propagation differences that provide unique challenges that must be addressed to make through-wall penetration sensors operationally viable. This paper outlines the historical context of early research and provides new directions for future research in the exciting interplay between electromagnetic propagation, signal processing, and knowledge-based reasoning algorithms.

Introduction

The field of remote sensing has developed a range of interesting imaging approaches for a variety of applications. Through-wall and through-building sensing are relatively new areas that address the desire to see inside structures to determine the layout of buildings, where occupants may be, and even identify materials within the building. Through-wall sensing is highly desired by police, fire and rescue, emergency relief workers, and military operations. Accurate sensing and imaging can allow a police force to obtain an accurate description of a building in a hostage crisis, or allow firefighters to locate people trapped inside a burning building. The goals of through-wall sensing technology are to provide vision into otherwise obscured areas.

Each remote-sensing application area has driven different sensing modalities and imaging algorithm development based upon propagation characteristics, sensor positioning, and safety issues. Traditional optical, radar, and sonar image processing all begin with basic wave physics equations to provide focusing to individual points. In many radar applications, for example, data sampled from many sensors are mathematically integrated to provide equivalent focusing using free-space propagation assumptions. Free-space imaging is commonly seen in synthetic aperture radar (SAR) techniques [1] since atmospheric distortions are often negligible and can be safely ignored in first-order calculations.

Conventional imaging approaches exploit the wave equation to compute the expected phase at each point in space and time over which the data are collected. The complex phase front is similar to the spatial representation of the wavefront captured by a hologram [2]. The complex returns can then be compared against the predicted returns from points in the imaging target space to focus on each point in that space. The focusing is analogous to image reconstruction in holography, where a spatial pattern is projected back into the originating target image space. In true free-space conditions, this focusing approach represents a mathematically accurate way to perform imaging. More sophisticated approaches extend beyond free-space assumptions to allow for more complicated propagation effects, such as adaptive optics [3], atmospheric correction for radar [1], and matched field processing for sonar [4]. Correction approaches range from simple wavefront calibration to more sophisticated volumetric propagation corrections.

Free-space propagation does not apply for many interesting applications where transmission through scattering media is encountered, including many modern imaging approaches such as geophysical sensing, medical imaging, and more recently through-building sensing. In these applications, propagated signals diffract through a volume. As examples, geophysical imaging techniques generally measure seismic propagation through the earth to look for discontinuities that are often indicators of oil, gas, water, or mineral deposits [5]. In medical imaging, ultrasound tomographic approaches account for propagation through different tissue classes [6].

Non-free-space scattering applications are more representative of the through-building sensing problem, albeit each has its own distinct challenges and approaches. In geophysical and medical applications, the propagation medium is discontinuous but still fills the sensing volume of the earth or tissue, respectively. To better propagate into the volume, sensors are placed in direct contact with the medium (e.g., seismometers for geophysical sensing, ultrasound transducers for medical imaging). In through-building sensing, there are many air–material interfaces that dramatically change the wavefront. Through-building sensors may be located some distance away from the structure and attenuation is largely seen only in the building materials and contents rather than in the large volumes of air that occupy most of the space within a building. Sensor standoff provides unique opportunities and challenges for exploiting building-dependent features. The rich through-wall scattering environment makes volumetric tomographic imaging approaches most relevant for through-building sensing. Rather than using free-space focusing assumptions, correcting propagation effects may greatly improve the imaging solution [7], [8].

This paper will first go over a brief historical look at the state of through-wall and through-building applications in Section 2. It will then evaluate basic propagation elements of through-wall sensing in Section 3, and identify future directions of research in Section 4.

Section snippets

Through-wall applications

Through-wall sensing is best motivated by looking at the applications primarily driving its development. Through-wall sensing grew from the application of ground-penetrating radar systems to walls, with specific applications documented in the literature since the late 1990s showing abilities to sense beyond a single wall from near range [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28]. Applications can be divided based upon

Propagation effects

The significant problem with conventional imaging approaches in through-wall applications is that propagation effects are generally not included in the imaging process. Consider the high-level imaging architecture represented in Fig. 1. A state vector x represents the true building structure. A sensor (defined by a sensor state vector p) collects data vector y that presumably captures all the relevant information about the building structure x. The data vector y is then a propagation function H

Future through-wall imaging directions

The DARPA VisiBuilding program [33] is developing future systems technologies for reconstruction of building layouts and localization of occupants. Under the VisiBuilding program, three core technical areas are being addressed: phenomenology of signal penetration into buildings, sensor positioning and utilization to maximize information about the building, and model-based 3-D building deconvolution that operates in a multipath-rich, diffractive environment. Let us examine each technical area in

Summary

Through-building imaging is an important area for first responder and military applications. Past sensing approaches have tried to extrapolate free-space sensing algorithms to form images through the dispersive medium of walls. Recent advances in propagation modeling and processing power can greatly extend through-wall sensing capability, exploiting model-based building decomposition to probe deeper into building structures beyond the limit of conventional open-loop imaging approaches. New

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