Neuartige Konzepte für die Radarbildgebung in heterogenen Medien

Radar imaging originates from remote sensing. There, the electromagnetic waves are usually assumed to propagate through free space. However, in numerous applications such as, for example, non-destructive testing or security screening, this assumption no longer holds. When there is a multi-material background, the image reconstruction becomes considerably more complex. In that case, refraction and changes in phase velocity have to be taken into account. While many problems have been solved in subsurface imaging before, some issues still require improvement. Therefore, this thesis provides novel concepts for more efficient, high-resolution radar imaging in heterogeneous media. In the thesis, first, fundamentals of wave propagation and radar imaging are recapitulated. Following this, state-of-the-art reconstruction algorithms for imaging objects in heterogeneous backgrounds are introduced. The conceptual, scientific novelties elaborated in this thesis are presented in chapters 4, 5 and 6. In chapter 4, the previously discussed imaging methods are applied and developed further in the context of non-destructive testing. Here, an imaging procedure which includes an estimation of the object’s contour and material is presented. Such a testing strategy makes it possible to reconstruct an image without the need for prior knowledge about the test object’s characteristics. The second development in the context of future non-destructive testing strategies (non-destructive evaluation 4.0) elaborated in this thesis is the integration of artificial intelligence into the post-processing of radar imaging. This not only allows for a highly resolved image of inner structures but also for a fully automated evaluation of the test object. Chapter 5 introduces two new reconstruction algorithms for radar imaging in heterogeneous media which offer an improvement compared to the state of the art with respect to computational efficiency. These are a computationally efficient reconstruction approach for imaging layered dielectrics with arbitrary sparse MIMO arrays and a k-space based concept for imaging irregularly shaped objects. In chapter 6, a novel multimodal imaging concept combining synthetic aperture radar and ultrasound is introduced. Here, ultrasound is used to compensate the surface reflection in the radar image. That way, targets close to the material boundary, which might otherwise be masked, can be made visible.In der Doktorarbeit werden neue Konzepte für die Radarbildgebung, insbesondere für eine hochaufgelöste Abbildung innenliegender, optisch verborgener Strukturen präsentiert. Dafür werden zunächst die zugehörigen Grundlagen der Wellenausbreitung und der Radarbildgebung erarbeitet. Daraufhin wird der Stand der Technik im Bereich der Radarbildgebung in heterogenen Medien vorgestellt. Die konzeptionellen, wissenschaftlichen Neuerungen dieser Arbeit werden in den Kapiteln 4, 5 und 6 präsentiert: Zunächst werden in Kapitel 4 die existierenden Methodiken zur Bildgebung im Kontext der zerstörungsfreien Werkstoffprüfung weiterentwickelt. Hierbei wird zum Einen ein Verfahren erarbeitet, welches Kontur und Material des Testobjekts im Bildgebungsprozess mitschätzt. Somit wird eine Radarbildgebung ohne Vorwissen über das Testobjekt ermöglicht, was beispielsweise für die Abbildung von Objekten aus Komposite-Materialien relevant ist. Für zukünftige Teststrategien („Zerstörungsfreie Prüfung 4.0“) werden zudem Methoden aus dem Bereich der künstlichen Intelligenz mit der Bildgebung kombiniert. In Kapitel 5 werden zwei neuartige, in dieser Arbeit entwickelte Bildgebungsalgorithmen präsentiert, welche eine deutliche Effizienzsteigerung gegenüber dem Stand der Technik bringen. Dies ist zum Einen ein effizientes Verfahren zur Abbildung planar geschichteter Medien für beliebig ausgedünnte MIMO-Arrays und zum Anderen ein Konzept zur Abbildung von Szenarien mit irregulären, aber teilweise ebenen Oberflächen. In Kapitel 6 wird ein neues Konzept vorgestellt, das es ermöglicht, oberflächennahe Ziele, welche durch das Grenzschichtecho maskiert werden, sichtbar zu machen. Hierfür wird die Radarbildgebung mit Luftultraschall-Bildgebung zu einem multimodalen Konzept fusioniert

A Computationally Efficient Reconstruction Approach for Imaging Layered Dielectrics With Sparse MIMO Arrays

This contribution presents a novel, computationally efficient approach to radar imaging of layered dielectrics with sparse MIMO arrays. Our concept does not impose any constraints on the array topology and at the same time promises to be more efficient than the state-of-the-art backprojection algorithm because it can make use of k-space reconstruction schemes. Experimental results with a sparse, non-equidistantly sampled array are provided. These demonstrate the feasibility of the approach and that the computational burden could be reduced by several orders of magnitude in a given practical example related to radar based non-destructive testing

A Realistic Radar Ray Tracing Simulator for Hand Pose Imaging

With the increasing popularity of human-computer interaction applications, there is also growing interest in generating sufficiently large and diverse data sets for automatic radar-based recognition of hand poses and gestures. Radar simulations are a vital approach to generating training data (e.g., for machine learning). Therefore, this work applies a ray tracing method to radar imaging of the hand. The performance of the proposed simulation approach is verified by a comparison of simulation and measurement data based on an imaging radar with a high lateral resolution. In addition, the surface material model incorporated into the ray tracer is highlighted in more detail and parameterized for radar hand imaging. Measurements and simulations show a very high similarity between synthetic and real radar image captures. The presented results demonstrate that it is possible to generate very realistic simulations of radar measurement data even for complex radar hand pose imaging systems.Comment: 4 pages, 5 figures, accepted at European Microwave Week (EuMW 2023) to the topic "R28 Human Activity Monitoring, including Gesture Recognition

Expanding the clinical spectrum associated with defects in CNTNAP2 and NRXN1

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Heterozygous copy-number and missense variants in CNTNAP2 and NRXN1 have repeatedly been associated with a wide spectrum of neuropsychiatric disorders such as developmental language and autism spectrum disorders, epilepsy and schizophrenia. Recently, homozygous or compound heterozygous defects in either gene were reported as causative for severe intellectual disability. Methods 99 patients with severe intellectual disability and resemblance to Pitt-Hopkins syndrome and/or suspected recessive inheritance were screened for mutations in CNTNAP2 and NRXN1. Molecular karyotyping was performed in 45 patients. In 8 further patients with variable intellectual disability and heterozygous deletions in either CNTNAP2 or NRXN1, the remaining allele was sequenced. Results By molecular karyotyping and mutational screening of CNTNAP2 and NRXN1 in a group of severely intellectually disabled patients we identified a heterozygous deletion in NRXN1 in one patient and heterozygous splice-site, frameshift and stop mutations in CNTNAP2 in four patients, respectively. Neither in these patients nor in eight further patients with heterozygous deletions within NRXN1 or CNTNAP2 we could identify a defect on the second allele. One deletion in NRXN1 and one deletion in CNTNAP2 occurred de novo, in another family the deletion was also identified in the mother who had learning difficulties, and in all other tested families one parent was shown to be healthy carrier of the respective deletion or mutation. Conclusions We report on patients with heterozygous defects in CNTNAP2 or NRXN1 associated with severe intellectual disability, which has only been reported for recessive defects before. These results expand the spectrum of phenotypic severity in patients with heterozygous defects in either gene. The large variability between severely affected patients and mildly affected or asymptomatic carrier parents might suggest the presence of a second hit, not necessarily located in the same gene.Peer Reviewe

Epilepsy and mental retardation limited to females: an under-recognized disorder

Epilepsy and Mental Retardation limited to Females (EFMR) which links to Xq22 has been reported in only one family. We aimed to determine if there was a distinctive phenotype that would enhance recognition of this disorder.We ascertained four unrelated families (two Australian, two Israeli) where seizures in females were transmitted through carrier males. Detailed clinical assessment was performed on 58 individuals, using a validated seizure questionnaire, neurological examination and review of EEG and imaging studies. Gene localization was examined using Xq22 microsatellite markers. Twenty-seven affected females had a mean seizure onset of 14 months (range 6^36) typically presenting with convulsions. All had convulsive attacks at some stage, associated with fever in 17 out of 27 (63%). Multiple seizure types occurred including tonic-clonic (26), tonic (4), partial (11), absence (5), atonic (3) and myoclonic (4). Seizures ceased at mean 12 years. Developmental progress varied from normal (7), to always delayed (4) to normal followed by regression (12). Intellect ranged from normal to severe intellectual disability (ID), with 67% of females having ID or being of borderline intellect. Autistic (6), obsessive (9) and aggressive (7) features were prominent. EEGs showed generalized and focal epileptiform abnormalities. Five obligate male carriers had obsessional tendencies. Linkage to Xq22 was confirmed (maximum lod 3.5 at h = 0).We conclude that EFMR is a distinctive, under-recognized familial syndrome where girls present with convulsions in infancy, often associated with intellectual impairment and autistic features. The unique inheritance pattern with transmission by males is perplexing. Clinical recognition is straightforward in multiplex families due to the unique inheritance pattern; however, this disorder should be considered in smaller families where females alone have seizures beginning in infancy, particularly in the setting of developmental delay. In single cases, diagnosis will depend on identification of the molecular basis. Keywords: epilepsy; intellectual disability; females; X-linked inheritance; autistic features Abbreviations: BAC = bacterial artificial chromosome; CFNS = craniofrontonasal syndrome; EFMR = epilepsy and mental retardation limited to females; ID = intellectual disability

A Novel, Efficient Algorithm for Subsurface Radar Imaging below a Non-Planar Surface

In classical radar imaging, such as in Earth remote sensing, electromagnetic waves are usually assumed to propagate in free space. However, in numerous applications, such as ground penetrating radar or non-destructive testing, this assumption no longer holds. When there is a multi-material background, the subsurface image reconstruction becomes considerably more complex. Imaging can be performed in the spatial domain or, equivalently, in the wavenumber domain (k-space). In subsurface imaging, to date, objects with a non-planar surface are commonly reconstructed in the spatial domain, by the Backprojection algorithm combined with ray tracing, which is computationally demanding. On the other hand, objects with a planar surface can be reconstructed more efficiently in k-space. However, many non-planar surfaces are partly planar. Therefore, in this paper, a novel concept is introduced that makes use of the efficient k-space-based reconstruction algorithms for partly planar scenarios, too. The proposed algorithm forms an image from superposing sub-images where as many image parts as possible are reconstructed in the wavenumber domain, and only as many as necessary are reconstructed in the spatial domain. For this, a segmentation scheme is developed to determine which parts of the image volume can be reconstructed in the wavenumber domain. The novel concept is verified by measurements, both from monostatic synthetic aperture radar data and multiple-input–multiple-output radar data. It is shown that the computational efficiency for imaging irregularly shaped geometries can be significantly augmented when applying the proposed concept

Millimeter-wave imaging and near-field spectroscopy for burn wound assessment

Diagnostic applications for skin in the microwave range have developed significantly in recent years, due the non-invasiveness of these applications and their ability to assess tissue water content. Despite their capabilities, however, there is still no appropriate clinically applicable microwave tool for the assessment of burn wounds. A common practice is the visual inspection and evaluation of burns by the doctor, which is a challenging task even for experienced medical professionals. An incorrect assessment can have far-reaching consequences, such as unnecessary surgery or surgery that is necessary but omitted. In this paper, two different approaches of millimeter-wave burn wound assessment are presented: millimeter-wave imaging and near-field spectroscopy. For imaging, a MIMO sparse array was used to assess ex vivo burns on porcine skin in the frequency range of 70–80 GHz. With a resonant millimeter-wave near-field probe, reflective spectroscopy at individual sites of an ex vivo burn on porcine skin in the frequency range of 75–110 GHz was performed. The results showed individual advantages and drawbacks for both approaches, with surprising benefits of the spectroscopic method. Nevertheless, both approaches were shown to be suitable for clinical usage in diagnosing burns

Wall-less Flow Phantoms with 3D printed Soluble Filament for Ultrasonic Experiments

Tissue-mimicking materials (TMMs) typically used for ultrasound phantoms include gelatin, agarose and polyvinyl alcohol (PVA). These materials have shown sufficient similarity in ultrasound parameters compared to human tissue. Despite their extensive use for years to generate ultrasound phantoms, no simple and easily reproducible way to generate complex, wall-less ultrasound flow phantoms has been introduced. Commercially available ultrasound flow phantoms are limited to simple flow geometries that do not reflect the complex blood flow in humans. Flow phantoms with complex geometries presented in scientific publications either have walls between TMMs and the flow channel, are limited to one material, or are complicated to produce. In this contribution, we present a method using 3D printing and soluble filament that allows for the reliable and consistent production of complex flow geometries with the typical materials used for ultrasound phantoms and without any walls

A Survey on Radar-Based Continuous Human Activity Recognition

Radar-based human motion and activity recognition is currently a topic of great research interest, as the aging population increases and older individuals prefer an independent lifestyle. This technology has a wide range of applications, such as fall detection in assisted living, gesture recognition for human-machine interfaces, and many more. Numerous studies exist on various approaches for radar-based activity capture and classification. However, most of these employ rather artificial data, often obtained in laboratory environments, and typically collected under particular conditions. Specifically, most research so far has aimed at distinguishing a predefined set of single activities with a defined start, stop and duration. This paper aims at drawing the attention to a so far less researched issue, one that will be of vital importance for future real-world application of radar-based human activity recognition: continuous activity recognition, i.e. recognizing specific activities in a stream of several sequential activities with unknown duration and arbitrary transitions between different classes of activities. A review on the current state of the art in this relatively new topic is given, followed by a discussion on future research directions.Microwave Sensing, Signals & System

Deep learning for terahertz image denoising in nondestructive historical document analysis

Abstract Historical documents contain essential information about the past, including places, people, or events. Many of these valuable cultural artifacts cannot be further examined due to aging or external influences, as they are too fragile to be opened or turned over, so their rich contents remain hidden. Terahertz (THz) imaging is a nondestructive 3D imaging technique that can be used to reveal the hidden contents without damaging the documents. As noise or imaging artifacts are predominantly present in reconstructed images processed by standard THz reconstruction algorithms, this work intends to improve THz image quality with deep learning. To overcome the data scarcity problem in training a supervised deep learning model, an unsupervised deep learning network (CycleGAN) is first applied to generate paired noisy THz images from clean images (clean images are generated by a handwriting generator). With such synthetic noisy-to-clean paired images, a supervised deep learning model using Pix2pixGAN is trained, which is effective to enhance real noisy THz images. After Pix2pixGAN denoising, 99% characters written on one-side of the Xuan paper can be clearly recognized, while 61% characters written on one-side of the standard paper are sufficiently recognized. The average perceptual indices of Pix2pixGAN processed images are 16.83, which is very close to the average perceptual index 16.19 of clean handwriting images. Our work has important value for THz-imaging-based nondestructive historical document analysis