Marijke Vandewal

Aeronautics composite material inspection with a terahertz time-domain spectroscopy system

Abstract. The usability of pulsed broadband terahertz radiation for the inspection of composite materials from the aeronautics industry is investigated, with the goal of developing a mobile time-domain spectroscopy system that operates in reflection geometry. A wide range of samples based on glass and carbon fiber reinforced plastics with various types of defects is examined using an imaging system; the results are evaluated both in time and frequency domain. The conductivity of carbon fibers prevents penetration of the respective samples but also allows analysis of coatings from the reflected THz pulses. Glass fiber composites are, in principle, transparent for THz radiation, but commonly with significant absorption for wavelengths >1  THz. Depending on depth, matrix material, and size, defects like foreign material inserts, delaminations, or moisture contamination can be visualized. If a defect is not too deep in the sample, its location can be correctly identified from the delay between partial reflections at the surface and the defect itself.

Efficient and precise processing for squinted spotlight SAR through a modified stolt mapping

Processing of squinted SAR spotlight data is a challenge because of the significant range migration effects of the raw data over the coherent aperture time. Although in theory the ()-algorithm takes care of these aspects, its digital implementation requires a time-consuming interpolation step. Moreover, the limited precision of this interpolation can introduce distortions at the edges of the final image especially for squinted geometries. A wave number domain processing using a modified Stolt mapping will be developed and analyzed to enhance the quality of the final SAR image. Additionally, the proposed algorithm has a decreased computational load compared to the original ()-algorithm. Simulation results will validate the focusing and efficiency performances of the modified wave number domain algorithm.

Nondestructive testing potential evaluation of a terahertz frequency-modulated continuous-wave imager for composite materials inspection

Abstract. The sub-terahertz (THz) frequency band has proved to be a noteworthy option for nondestructive testing (NDT) of nonmetal aeronautics materials. Composite structures or laminates can be inspected for foreign objects (water or debris), delaminations, debonds, etc., using sub-THz sensors during the manufacturing process or maintenance. Given the harmless radiation to the human body of this frequency band, no special security measures are needed for operation. Moreover, the frequency-modulated continuous-wave sensor used in this study offers a very light, compact, inexpensive, and high-performing solution. An automated two-dimensional scanner carrying three sensors partially covering the 70- to 320-GHz band is operated, using two complementary measurement approaches: conventional focused imaging, where focusing lenses are used; and synthetic aperture (SA) or unfocused wide-beam imaging, for which lenses are no longer needed. Conventional focused imagery offers finer spatial resolutions but imagery is depth-limited due to the beam waist effect, whereas SA measurements allow imaging of thicker samples with depth-independent but coarser spatial resolutions. The present work is a compendium of a much larger study and describes the key technical aspects of the proposed imaging techniques and reports on results obtained from human-made samples (A-sandwich, C-sandwich, solid laminates) which include diverse defects and damages typically encountered in aeronautics multilayered structures. We conclude with a grading of the achieved results in comparison with measurements performed by other NDT techniques on the same samples.

Efficient SAR Raw Data Generation Including Low Squint Angles and Platform Instabilities

The performance of high-resolution synthetic aperture radar (SAR) systems under degrading conditions such as uncontrolled platform motion can only be analyzed and evaluated by modeling the whole imaging system through simulation. A major scientific problem, however, is the generation of spotlight mode SAR raw data because of the need for high numerical and modeling accuracy, and restricted computer time and space. Taking into account a squinted geometry and platform instabilities, the common generation of raw data in the time domain becomes time inefficient. This letter proposes a raw data generator with which the spotlight mode raw data set of an extended scene can be simulated and which combines the precision obtainable when working in the time domain with the efficiency of work in the frequency domain. The generated raw data are processed and analyzed to quantify the quality of the proposed simulation tool.

Synthetic aperture imaging extended towards novel THz sensors

The purpose of this paper is to extend the technology of synthetic aperture (SA) imaging used in radar (SAR) and sonar (SAS) to the THz range (SAT). This novel approach in THz will be applied in the domain of non-destructive testing (NDT). The paper presents simulated SAT images which are demonstrating the performance of a synthetic aperture time domain reconstruction processing. The generated SAT target responses of broadband radiation show high resolution and high signal-to-noise ratio (SNR) which lead to an improvement of non-destructive defect identification.

Compressed sensing mm-wave SAR for non-destructive testing applications using side information

This paper evaluates the applicability of an innovative strategy for applying Compressed Sensing (CS) on Synthetic Aperture Radar (SAR) imaging, in the mm-wave range, using prior or structural side information. The studied technique adds the side information to the conventional CS minimization problem using an l1-l1 minimization approach, allowing for lower sub-Nyquist sampling than standard CS predicts. The applicability of this strategy on ultra-wideband SAR measurements is tested through simulations and real Non-Destructive Testing (NDT) experiments on a 3D-printed polymer object.

Fusion of Optical and Thermal Imagery and LiDAR Data for Application to 3-D Urban Environment and Structure Monitoring

For many years, panchromatic aerial photographs have been the main source of remote sensing data for detailed inventories of urban areas. Traditionally, building extraction relies mainly on manual photo-interpretation which is an expensive process, especially when a large amount of data must be processed (Ameri, 2000). The characterization of a given object bases on its visible information, such as: shape (external form, outline, or configuration), size, patterns (spatial arrangement of an object into distinctive forms), shadow (indicates the outlines, length, and is useful to measure height, or slopes of the terrain), tone (color or brightness of an object, smoothness of the surface, etc.) (Ridd 1995). Automated assessment of urban surface characteristics has been investigated due to the high costs of visual interpretation. Most of those studies used multispectral satellite imagery of medium to low spatial resolution (Landsat-TM, SPOT-HRV, IRS-LISS, ALI and CHRIS-PROBA) and were based on common image-analysis techniques (e.g. maximum likelihood (ML) classification, principal components analysis (PCA) or spectral indices (Richards and Jia 1999)). The problems of limited spatial resolution over urban areas have been overcome with the wider availability of space-borne systems, which characterized by large swath and high spatial and temporal resolutions (e.g. Worl-View2). However, the limits on spectral information of nonvegetative material render their exact identification difficult. In this regard, the hyperspectral remote sensing (HRS) technology, using data from airborne sensors (e.g. AVIRIS, GER, DAIS, HyMap, AISA-Dual), has opened up a new frontier for surface differentiation of homogeneous material based on spectral characteristics (Heiden et al. 2007). This capability also offers the potential to extract quantitative information on biochemical, geochemical and chemical parameters of the targets in question (Roessner et al. 1998).

Statistical real-time model for performance prediction of ship detection from microsatellite electro-optical imagers

For locating maritime vessels longer than 45 meters, such vessels are required to set up an Automatic Identification System (AIS) used by vessel traffic services. However, when a boat is shutting down its AIS, there are no means to detect it in open sea. In this paper, we use Electro-Optical (EO) imagers for noncooperative vessel detection when the AIS is not operational. As compared to radar sensors, EO sensors have lower cost, lower payload, and better computational processing load. EO sensors are mounted on LEO microsatellites. We propose a real-time statistical methodology to estimate sensor Receiver Operating Characteristic (ROC) curves. It does not require the computation of the entire image received at the sensor. We then illustrate the use of this methodology to design a simple simulator that can help sensor manufacturers in optimizing the design of EO sensors for maritime applications.

Applicability of compressive sensing on three-dimensional terahertz imagery for in-depth object defect detection and recognition using a dedicated semisupervised image processing methodology

Abstract. The quality control of composite multilayered materials and structures using nondestructive tests is of high interest for numerous applications in the aerospace and aeronautics industry. One of the established nondestructive methods uses microwaves to reveal defects inside a three-dimensional (3-D) object. Recently, there has been a tendency to extrapolate this method to higher frequencies (going to the subterahertz spectrum) which could lead to higher resolutions in the obtained 3-D images. Working at higher frequencies reveals challenges to deal with the increased data rate and to efficiently and effectively process and evaluate the obtained 3-D imagery for defect detection and recognition. To deal with these two challenges, we combine compressive sensing (for data rate reduction) with a dedicated image processing methodology for a fast, accurate, and robust quality evaluation of the object under test. We describe in detail the used methodology and evaluate the obtained results using subterahertz data acquired of two calibration samples with a frequency modulated continuous wave system. The applicability of compressive sensing within this context is discussed as well as the quality of the image processing methodology dealing with the reconstructed images.

In-depth high-resolution SAR imaging using Omega-k applied to FMCW systems

Imagery applied to non-destructive testing implicitly includes the ability of imaging defects or foreign inclusions inside materials. Within a certain frequency range some nonmetal materials become highly transparent and only media interfaces or defects will scatter signals back to the sensor. Three-dimensional in-depth imaging is therefore possible and synthetic aperture processing can be applied to compensate cost-efficiently several main disadvantages present in typical high-resolution microwave imagery systems using focused beams. This work investigates under the framework of the DOTNAC Project (an FP7 project funded by the European Commission) the possibilities of applying synthetic aperture radar processing to a high-resolution frequency-modulated continuous-wave system for non-destructive testing purposes. The Omega-k range migration algorithm is used to perform efficient range migration of the raw data. This paper shows in-depth SAR images from real composite materials including ad-hoc defects. Assessment of results as well as discussion on the proposed 3-D in-depth imaging system will be presented.