Purpose - The purpose of this paper is to obtain the long-wave approximations for the effective electromagnetic response of two-dimensional sandwich composite structure, as infinite chain of infinitely long metal cylinders symmetrically immersed in an infinite metamaterial slab are obtained. The slab is an infinite magneto-dielectric matrix with periodically imbedded infinitely long metal cylinders whose diameter is smaller than those of the chain cylinders. The case of ferrite-like metallic saturated inclusions is considered in the study.Design/methodology/approach - The result is presented as a generalized expression of the electromagnetic response of the infinite periodic chain of infinitely long metallic cylinders immersed into the flat magneto-dielectric host medium. Those expressions were obtained utilizing S-and T-matrices approaches.Findings - A good coincidence between the results of analytical modeling and numerical simulations was found.Research limitations/implications - Low values of the metal volume fraction; microwave frequency range.Practical implications - An improving of directivity of patch antennas; a minimization of patch antennas.Originality/value - The analytical characterization of new artificial substrate-like structure to be utilized for designing patch antennas of a new generation.

Purpose The purpose of this paper is to study the microwave behaviour of effective magnetic permeability for two‐component ferrite like metamaterial medium in the direction of a biasing magnetic field. The metamaterial medium is presented as an infinite host dielectric material (air) with periodically embedded ferric cylindrical and spherical inclusions saturated with an external dc magnetic field. The study is based on the effective medium theory developed for polycrystalline metaferrites. The simulations show that the presented metamaterial can exhibit the ultra‐low refractive index (ULI) phenomenon and the phenomenon of negative magnetic permeability for the case of microwave propagation in the direction of bias. Design/methodology/approach The obtained results are based on the wave long approximation of permeability tensor of the presented metamaterial media obtained earlier by the first author. Using the standard approach, the authors apply the above expressions for the microwave propagation in direction of biasing dc magnetic field considering different polarization of the incident microwave. Findings The considered artificial material media can become either material with a ULI or with negative values in the GHz frequencies. Originality/value The paper is concerned with part of the theory of a new generation of artificial ferrites.

This paper deals with waveform design for improved detection and classification of targets behind walls and enclosed structures. The target impulse response is incorporated in an optimum design of the transmitted waveform which aims at maximizing the signal-to-interference and noise ratio (SINR) at the receiver output. The interference represents signal-dependent clutter which, along with the wall, degrades the receiver performance compared to the free-space and zero-clutter case. Computer simulations show sensitivity of the optimum waveform to target orientation but depict an SINR enhancement over chirped waveform radar emissions at all aspect angles. Numerical electromagnetic modeling is used to provide the impulse response of typical indoor stationary targets, namely, tables, chairs, and humans.

In this paper, we describe and utilize polarization contrast techniques of the adaptive polarization difference imaging algorithm and its transient modification for through-wall microwave imaging (TWMI) applications. Originally developed for optical imaging and sensing of polarization information in nature, this algorithm is modified to serve for target detection purposes in a through-wall environment. The proposed techniques exploit the polarization statistics of the observed scene for the detection and identification of changes within the scene and are not only capable of mitigating and substantially removing the wall effects but also useful in detecting motion, when conventional Doppler techniques are not applicable. Applications of the techniques to several TWMI scenarios including both homogeneous and periodic wall cases are presented.

Metallic objects and liquid supplies around a reader and/or tags may significantly affect the read range of RFID systems. Strong reflecting signals may be generated by the metallic and liquid surface. Depending on the phase of the reflected signal relative to that of the signal transmitted by the reader or reflected by the tag, the reflected signal may affect the signal strength constructively or destructively. Thus, in some situations the read range may be extended due to the reflection, and in other situations the read range may be significantly reduced. The most significant impact is achieved when the metallic objects and liquid supplies are relatively large and close to the reader and/or tag. It is advised that the RFID system is operated away from metallic material and liquid supplies. Multiple RFID antennas may achieve spatial diversity and improve the link reliability over an extended read range.

Target detection and classification are considered the primary tasks in through-the-wall radar imaging. Indoor targets can be stationary or in motion. In this paper, we apply the matched illumination concept to the scattered electromagnetic field of two stationary targets that are commonly found in an indoor environment, namely, a wooden chair and a wooden table. The optimal waveform was obtained by choosing the eigenvector corresponding to the largest eigenvalue of the target's autocorrelation matrix. The scattered field over the frequency band of 1-3 GHz was obtained by full wave numerical simulations using a commercially available Finite-Difference Time Domain solver (XFDTD from REMCOM). The detection performance of the optimum waveform against the commonly used linear frequency modulated (LFM) signal of the same bandwidth was compared.

Cross-correlation based image subtraction for detection of targets within an urban structure from synthetic aperture radar images is presented. In surveillance operations requiring re-imaging of the same scene, small displacements in array element locations may cause large phase and amplitude offsets. Subsequently, clutter will not cancel out, but will rather persist when subtracting two images, one without the target and the other with the target present. We propose a correlation-based robust technique that mitigates image offsets and rotations and is applicable to synthetic aperture radar urban sensing where the statistics are highly non-Gaussian. Simulation results demonstrating the effectiveness of the proposed technique are also presented.

In this paper we first briefly outline important areas of research in design of through-the-wall imaging and sensing systems from an electromagnetic perspective. Then we review some of our work in the applications of various polarization contrast techniques for detection of changes due to an object motion and/or orientation behind the wall. Finally, we discuss development of a low-profile wideband antenna array for a portable radar system that can be used in conjunction with polarization contrast algorithms.

Adaptive polarization-contrast techniques were applied to a model of human arm motion inside the room. Simulated results show the possible utility of the method for the case where reflections from multiple walls are present. Polarization-contrast sensing in the frequency domain may help us estimate the relative position of the arm with respect to the torso. This is achieved by analysis of optimal angles in the principal component analysis. Other results for targets in more complicated multipath environments will be given in the presentation.

Shadow is omnipresent in natural scenes. Conventional imaging methodologies are less effective in detecting features in shadow regions. Polarization imaging exploits another dimension of light that increases detection sensitivity in shadow and reveals hidden features.

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.

Shadow is an inseparable aspect of all natural scenes. When there are multiple light sources or multiple reflections several different shadows may overlap at the same location and create complicated patterns. Shadows are a potentially good source of information about a scene if the shadow regions can be properly identified and segmented. However, shadow region identification and segmentation is a difficult task and improperly identified shadows often interfere with machine vision tasks like object recognition and tracking. We propose here a new shadow separation and contrast enhancement method based on the polarization of light. Polarization information of the scene captured by our polarization-sensitive camera is shown to separate shadows from different light sources effectively. Such shadow separation is almost impossible to realize with conventional, polarization-insensitive imaging.

The polarization of light carries much useful information about the environment. Biological studies have shown that some animal species use polarization information for navigation and other purposes. It has been previously shown that a bioinspired polarization-difference imaging (PDI) technique can facilitate detection and feature extraction of targets in scattering media. It has also been established [J. Opt. Soc. Am. A 15, 359 (1998)] that polarization sum and polarization difference are the optimum pair of linear combinations of images taken through two orthogonally oriented linear polarizers of a scene having a uniform distribution of polarization directions. However, in many real environments the scene has a nonuniform distribution of polarization directions. Using principal component analysis of the polarization statistics of the scene, we develop a method to determine the two optimum information channels with unequal weighting coefficients that can be formed as linear combinations of the images of a scene taken through a pair of linear polarizers not constrained to the horizontal and vertical directions of the scene. We determine the optimal orientations of linear polarization filters that enhance separation of a target from the background, where the target is defined as an area with distinct polarization characteristics as compared to the background. Experimental results confirm that in most situations adaptive PDI outperforms conventional PDI with fixed channels.

Most existing latent fingerprints lifting methods are invasive and often induce deleterious side effects. Based on the optical reflection and polarization we present a completely non-invasive method to lift latent fingerprints into good quality images.

The polarization-based segmentation algorithm, which is an extension of our adaptive polarization-difference technique, has been developed. Notable increase in target-against-background separation is achieved.

The preliminary results of application of the adaptive polarization-imaging algorithm for through-the-wall microwave imaging problems are presented. Use of complete polarization information in the scattered field from the object together with the adaptation technique provides enhancement in detection of target movement.

For scenes with different polarization statistics with non-uniform distributions, we develop algorithms that adaptively determine the two or three optimal polarization channels using the principal component analysis and signal detection theory. This increases the sensitivity index for detection of a target against these scenes and is adaptive to scene statistics.