Maryam Ravan

Near-Field Microwave Imaging Based on Aperture Raster Scanning With TEM Horn Antennas

The design, fabrication, and characterization of an ultrawideband (UWB) antenna for near-field microwave imaging of dielectric objects are presented together with the imaging setup. The focus is on an application in microwave breast tumor detection. The new antenna operates as a sensor with the following properties: 1) direct contact with the imaged body; 2) more than 90% of the microwave power is coupled directly into the tissue; 3) UWB performance; 4) excellent de-coupling from the outside environment; 5) small size; and 6) simple fabrication. The antenna characterization includes return loss, total efficiency, near-field directivity, fidelity, and group velocity. The near-field imaging setup employs planar aperture raster scanning. It consists of two antennas aligned along each others boresight and moving together to scan two parallel apertures. The imaged object lies between the two apertures. With a blind de-convolution algorithm, the images are de-blurred. Simulation and experimental results confirm the satisfactory performance of the antenna as an UWB sensor for near-field imaging.

Three-Dimensional Near-Field Microwave Holography Using Reflected and Transmitted Signals

A new 3-D holographic microwave imaging technique is proposed to reconstruct targets in the near-field range. It is based on the Fourier analysis of the wideband transmission and reflection signals recorded by two antennas scanning together along two rectangular parallel apertures on both sides of the inspected region. The complex scattering parameters of the two antennas are collected at several frequencies and then processed to obtain a representation of the 3-D target in terms of 2-D slice images at all desired range locations. No assumptions are made about the incident field and Greens function, which are derived either by simulation or by measurement. Furthermore, an approach is proposed to reduce the image artifacts along range. To validate the proposed technique, predetermined simulated targets are reconstructed. The effects of random noise, number of sampling frequencies, and dielectric contrast of the targets are also discussed.

Two-dimensional near-field microwave holography

A new two-dimensional (2D) holographic microwave imaging technique is proposed to reconstruct the 2D image of a target. It is based on the Fourier analysis of the data recorded by two antennas scanning together two separate rectangular parallel apertures on both sides of a target. The complex back-scattered signals of the two antennas are first processed to localize the target in the range direction. Then, the 2D image of the target is reconstructed. No assumptions are made about the incident fields, which can be derived by either simulation or measurement. Both the back-scattered and forward-scattered signals can be used to reconstruct the image of the target. This makes the proposed technique applicable with near-field measurements. To evaluate the proposed technique, the range localization and the 2D image reconstruction of a predetermined simulated target are examined. Associated resolution limits, sampling constraints and the impact of noise are also discussed.

Sizing of 3-D Arbitrary Defects Using Magnetic Flux Leakage Measurements

In this paper, we propose a new procedure to estimate the shape of the opening and the depth profile of an arbitrary three-dimensional (3-D) defect from magnetic flux leakage (MFL) measurements. We first use the Canny edge detection algorithm to estimate the shape of the defect opening. Then we use an inversion procedure based on the space mapping (SM) methodology in order to approximate the defect depth profile efficiently. To demonstrate the accuracy of the proposed inversion technique, we reconstruct defects of arbitrary shapes from simulated MFL signals. The procedure is then tested with experimental data of two metal-loss defects. In both cases, the proposed approach shows good agreement between the actual and estimated defect parameters.

Canadian HF Over-the-Horizon Radar experiments using MIMO techniques to control auroral clutter

High frequency Over-the-Horizon Radar (OTHR) provides an economical means to track noncooperative air targets over large expanses of land and ocean. However, early attempts to run OTHR in Canada in the 1970s were confounded by the presence of intense radar clutter originating in the auroral zone. Recent advances in Multiple-Input Multiple-Output (MIMO) OTHR technology, namely orthogonal waveform transmit arrays and fully sampled receive arrays, provide an opportunity to revisit the possibility of OTHR in Canada. An OTHR testbed has been built in Ottawa, Canada to determine the capabilities of the technology. The testbed consists of a MIMO OTHR with 4 transmit channels and 4 receive channels. Some preliminary data show that MIMO processing is effective in suppressing the clutter. It is then proposed to upgrade the testbed to a larger-scale system.

Ionospheric and auroral clutter models for HF surface wave and over-the-horizon radar systems

[1] The detection performance of high frequency surface wave radar (HFSWR) and high frequency over-the-horizon radar (OTHR) systems is heavily influenced by the presence of radar clutter. In HFSWR systems, the clutter has its origins in vertical-incidence ionospheric reflections, whereas in OTHR systems, the origin is Bragg backscatter from plasma structures in the auroral zone. This paper models the spreading of the radar clutter signal in the Doppler and angle-of-arrival domains that arises from forward-scattering effects as the radar pulse propagates through regions of ionospheric plasma irregularities. The models use a geometric optics approach to determine the power spectrum of the radar signal phase. This power spectrum is then used to simulate three-dimensional space-time-range radar data cubes. The accuracy of the models is tested by comparing the simulated data to measured data cubes. As an application, the data are then used to evaluate the performance of the newly developed fast fully adaptive (FFA) space-time adaptive processing (STAP) scheme to improve the extraction of target echoes from a clutter background.

Removal of Probe Liftoff Effects on Crack Detection and Sizing in Metals by the AC Field Measurement Technique

In the alternative current field measurement (ACFM) technique, the nonzero value of liftoff distance for the magnetic sensor acts as a low-pass filter on surface crack signals, causing errors in crack detection and sizing. We present a blind deconvolution algorithm for liftoff evaluation and surface crack signal restoration. The algorithm employs the available closed-form expressions for the distribution of electromagnetic fields at the metal surface in the vicinity of a crack. To examine the accuracy of the algorithm, we use the original and the restored signals for crack sizing by a wavelet network inversion method. We present simulated and experimental results to demonstrate the role of the proposed algorithm in improving the inversion process.

A machine learning approach for distinguishing age of infants using auditory evoked potentials

OBJECTIVE To develop a high performance machine learning (ML) approach for predicting the age and consequently the state of brain development of infants, based on their event related potentials (ERPs) in response to an auditory stimulus. METHODS The ERP responses of twenty-nine 6-month-olds, nineteen 12-month-olds and 10 adults to an auditory stimulus were derived from electroencephalogram (EEG) recordings. The most relevant wavelet coefficients corresponding to the first- and second-order moment sequences of the ERP signals were then identified using a feature selection scheme that made no a priori assumptions about the features of interest. These features are then fed into a classifier for determination of age group. RESULTS We verified that ERP data could yield features that discriminate the age group of individual subjects with high reliability. A low dimensional representation of the selected feature vectors show significant clustering behavior corresponding to the subject age group. The performance of the proposed age group prediction scheme was evaluated using the leave-one-out cross validation method and found to exceed 90% accuracy. CONCLUSIONS This study indicates that ERP responses to an acoustic stimulus can be used to predict the age and consequently the state of brain development of infants. SIGNIFICANCE This study is of fundamental scientific significance in demonstrating that a machine classification algorithm with no a priori assumptions can classify ERP responses according to age and with further work, potentially provide useful clues in the understanding of the development of the human brain. A potential clinical use for the proposed methodology is the identification of developmental delay: an abnormal condition may be suspected if the age estimated by the proposed technique is significantly less than the chronological age of the subject.

Three-Dimensional Microwave Holographic Imaging Employing Forward-Scattered Waves Only

We propose a three-dimensional microwave holographic imaging method based on the forward-scattered waves only. In the proposed method, one transmitter and multiple receivers perform together a two-dimensional scan on two planar apertures on opposite sides of the inspected domain. The ability to achieve three-dimensional imaging without back-scattered waves enables the imaging of high-loss objects, for example, tissues, where the back-scattered waves may not be available due to low signal-to-noise ratio or nonreciprocal measurement setup. The simulation and experimental results demonstrate the satisfactory performance of the proposed method in providing three-dimensional images. Resolution limits are derived and confirmed with simulation examples.

Joint waveform optimization and adaptive processing for random phase radar signals

We consider waveform design for multiple-input, multiple-output radar systems for the case where the signal, during propagation, undergoes phase perturbations. We formulate an iterative algorithm to obtain both waveform parameters and the weights of the adaptive matched filter. An example of a clutter and target model is provided to show how the optimal waveform design improves the detection performance of a random-phase radar compared to traditional waveforms.