Doug Gray

T-ray computed tomography

We demonstrate a tomographic imaging modality that uses pulsed terahertz (THz) radiation to probe the optical properties of three-dimensional (3D) structures in the far-infrared. This THz-wave computed tomography (T-ray CT) system provides sectional images of objects in a manner analogous to conventional CT techniques such as x-ray CT. The transmitted amplitude and phase of broadband pulses of THz radiation are measured at multiple projection angles. The filtered backprojection algorithm is then used to reconstruct the target object, including both its 3D structure and its frequency-dependent far-infrared optical properties.

Towards functional 3D T-ray imaging

We review the recent development of T-ray computed tomography, a terahertz imaging technique that allows the reconstruction of the three-dimensional refractive index profile of weakly scattering objects. Terahertz pulse imaging is used to obtain images of the target at multiple projection angles and the filtered backprojection algorithm enables the reconstruction of the objects frequency-dependent refractive index. The application of this technique to a biological bone sample and a plastic test structure is demonstrated. The structure of each target is accurately resolved and the frequency-dependent refractive index is determined. The frequency-dependent information may potentially be used to extract functional information from the target, to uniquely identify different materials or to diagnose medical conditions.

Three-dimensional space-borne synthetic aperture radar (SAR) imaging with multiple pass processing

Three-dimensional (3D) synthetic aperture radar (SAR) imaging via multiple-pass processing is an extension of interferometric SAR imaging. It exploits more than two flight passes to achieve a desired resolution in elevation. In this paper, a novel approach is developed to reconstruct a 3D space-borne SAR image with multiple-pass processing. It involves image registration, phase correction and elevational imaging. An image model matching is developed for multiple image registration, an eigenvector method is proposed for the phase correction and the elevational imaging is conducted using a Fourier transform or a super-resolution method for enhancement of elevational resolution. 3D SAR images are obtained by processing simulated data and real data from the first European Remote Sensing satellite (ERS-1) with the proposed approaches.

Three-dimensional SAR imaging via multiple pass processing

This paper develops a novel approach to reconstruct a three-dimensional (3D) SAR image with multiple pass processing. It involves image registration, phase correction and beamforming in elevation. An eigenvector method is proposed for the phase correction and the beamforming in elevation is carried out by a DFT or a subspace method for superresolution. 3D SAR images are demonstrated by processing ERS-1 real data with the proposed approach.

CLEAN deconvolution for sidelobe suppression in random noise radar

The term random noise radar (RNR) refers to a class of radar using random noise as its transmitted signal. Noise waveforms have proven useful in a number of radar applications; however, dynamic range performance suffers due to high range sidelobes. This paper investigates the use of the CLEAN deconvolution algorithm to suppress range sidelobes in noise radar. Simulation results are presented demonstrating the algorithms effectiveness, using both point and contiguous radar targets.

Bias Compensation for Least-Squares Multi-Pulse TDOA Localization Algorithms

A weighted least squares (WLS) estimator is presented for time difference of arrival (TDOA) localization of an emitter using multiple TDOA measurements collected by moving receivers. A comprehensive bias analysis for this estimate is provided. Based on the outcomes of the bias analysis, a bias compensation algorithm is developed to reduce the severe WLS estimation bias. The proposed algorithm utilizes an estimate of the instantaneous bias derived from the WLS estimate itself. The significant bias reduction capability of the proposed bias compensation algorithm is illustrated with simulation examples involving geolocation of a pulse radar by unmanned aerial vehicles (UAVs).

Closed-form estimators for multi-pulse TDOA localization

Most time difference of arrival (TDOA) localization algorithms process only one set of TDOA measurements to compute the emitter location. In certain applications such as pulse radar localization we are presented with a large number of TDOA measurements over very short time intervals. The paper develops new closed-form multi-pulse localization algorithms that exploit additional information available from multiple TDOA measurements. Reduced bias estimators are also developed. The superior bias performance of the new algorithms is demonstrated by way of computer simulations.

Space variant filtering of polar format spotlight SAR images for wavefront curvature correction and interferometric processing

In repeat pass SAR interferometry the scene coherence can be used to detect subtle scene changes that occur in the interval between image collections. In spotlight SAR mode the azimuth resolution of the baseline and repeat pass imagery may be improved by collecting an extended aperture therefore allowing finer resolution estimates of the scene coherence. The formation of the imagery however requires adequate compensation of the wavefront curvature effects which become increasing significant in finer resolution imagery. In N. E. Doren (1997) it is shown that for spotlight SAR imagery, formed using the Polar Format Algorithm (PFA), wavefront curvature effects give rise to residual phase errors that may be removed using an image domain filtering technique. The analysis however is based on the formation of a slant plane image obtained by projection of the scene reflectivity along circular arcs centered on the flight track. In this paper a full 3D imaging geometry is considered to derive an appropriate post PFA image domain filter to form a ground plane image. This allows multipass images to be formed in a common image plane for subsequent interferometric processing. The technique is used to generate a fine resolution coherence map using data collected in a repeat pass SAR experiment using the DSTO Ingara SAR.

Features for high resolution radar range profile based ship classification

This study investigates a variety of features in the context of automated ship classification of high resolution radar range profile. The features used are length, scatterer count, centres of mass, quantised range profile and Fourier modified direct Mellin transform coefficients. The results of evaluation using a modest database of high resolution range profiles, collected using an airborne radar, are then presented.

Classifying ships using low resolution maritime radar

The classification of shipping using commercially available low resolution incoherent radars has useful applications in both harbour surveillance and naval defence. However, one major drawback is the relatively low resolution of the radar images. We present a brief overview of a real-time classification system currently under development, and present results of applying various classification schemes to low resolution radar images, in conjunction with track data, to classify surface craft into broad categories.