Microwave UWB sensors for measurements under non-stationary conditions: detection of human being beneath rubble for rescue applications

UWB (Ultra-Wide Band) -Radar ist eine vielversprechende Möglichkeit, Menschen unter eingestürzten Gebäuden zu lokalisieren. Diese Arbeit widmet sich unterschiedlichen Wegen diese Anwendung zu verbessern. Zu Beginn wird umfassend analysiert, wie kleine unregelmäßige Bewegungen vom Radar erfasst werden. Es wird festgestellt, dass minimale Objektbewegungen im Bereich weniger Mikrometer detektierbar sind, was viel weniger ist, als die Atembewegung eines Menschen. Weiterhin wird dargestellt, dass für die Erfassung von sehr kleinen Objektbewegungen ein sehr geringer Jitter notwendig ist. Daher wird in dieser Arbeit ein MLBS (Maximum Length Binary Sequence) Radar mit sehr geringem Jitter verwendet. Zusätzlich wird eine quantitative Bewertung der Durchschnittswertbildung vorgenommen. Als ein Hauptergebnis wurden die genauen Bedingungen für die Geschwindigkeit der Datenerfassung ermittelt, die notwendig sind, um bei gegebener Objektgeschwindigkeit die blockweise Durchschnittswertbildung für die Erfassung kleiner Objektbewegungen zu verbessern. Eine Analyse, wie kleine periodische Bewegungen sich äußern wird gegeben. Die mathematischen Betrachtungen bestätigen, dass die menschliche Atmung vorwiegend Sinusanteile enthält, die hauptsächlich an den Taktflanken auftreten. Daher ist der Stand der Technik zur Erfassung von Atembewegungen gerechtfertigt. Analysen zeigen aber, dass Signaleigenschaften existieren, die eine Verbesserung gegenüber dem Stand der Technik zulassen. Weitergehend wird dargestellt, dass theoretisch zwei Typen von Harmonischen in den Radardaten vorhanden sind, die von der Standard-FFT nicht berücksichtigt werden. Diese Harmonischen werden genutzt, um mittels der Bispectrum-Slice-Technik das Signal zu verstärken. Es wird der Schluss gezogen, dass dieser Ansatz in der Praxis die Detektierbarkeit nur verbessert, wenn die Level der Harmonischen groß genug sind. Eine weitere Signaleigenschaft, die in der horizontalen Standard FFT (Fast Fourier Transform) Technik nicht berücksichtigt wird, ist die Spreizung der Laufzeit in der Atmungssignatur. Es werden Algorithmen vorgestellt, die dieses Phänomen nutzen, um das Auffinden verschütteter Personen zu verbessern. Es wird die Leistungsfähigkeit dieser Algorithmen theoretisch analysiert und praktisch mit simulierten und gemessenen Radardaten überprüft. Es zeigt sich, dass sich der Störabstand durch diesen Ansatz gegenüber den Standardtechniken um mehrere dB verbessert. Eines der Hauptprobleme beim Suchen von Überlebenden sind bewegte Objekte im Strahlengang der Antenne. In dieser Arbeit werden zwei Algorithmen zur Beseitigung dieser Störung vorgeschlagen. Beide Methoden nutzen die Tatsache, dass Atembewegungen im Radargramm sehr spezifisch ausgeprägt sind und sich daher sehr gut von anderen Signalkomponenten unterscheiden lassen. Beide Algorithmen funktionieren sehr gut mit simulierten und gemessenen Radardaten. Abschließend wird die Positionsbestimmung einer verschütteten Person beschrieben. Es wird ein entsprechender Algorithmus dargestellt und mit Messdaten in 2D und 3D getestet. Es kann der Schluss gezogen werden, dass die Positionsbestimmung erfolgreich durchgeführt werden kann, indem die Methoden der Ankunftszeitbestimmung und Differenzankunftszeitbestimmung kombiniert werden.UWB (Ultra-Wide Band) radar is a promising tool for finding victims beneath collapsed buildings. Therefore, this thesis concentrates on different ways of improving the performance of abovementioned device. At first thorough theoretical analysis of how minor irregular motion is seen by radar is given. It is concluded that minimal object shift detectable via radar device is in the order of dozens of micrometers, which is much lower than the amplitude of human respiration. It is also derived that in case of detecting minor motion low jitter is a key to successful performance and thus, radar unit with minimal jitter has to be used (like MLBS (Maximum Length Binary Sequence) radar considered in this thesis). Besides, the effect of averaging is analyzed quantitatively. As a main result precise condition is established on how fast we need to acquire data so that blockwise averaging would improve detectability of target displacement. Analysis of how minor periodical motion manifests itself in the radargram is presented. It is confirmed by our mathematical considerations that respiration is to high extent sinusoidal and that it mainly appears at the pulse edge. That is, state-of-the art technique for detecting respiratory motion (FFT (Fast Fourier Transform) and maximum search) is justified. However, analysis also shows signal features that allow improvement in comparison with state of the art technique. In particular, it is derived theoretically that harmonics of two different types are present in the measured radar data (which is not respected in standard FFT data processing). These harmonics are used to amplify useful signal by means of bispectrum-slice technique. The conclusion is made that in practice this approach improves the detectability only when level of harmonics is high enough. Another signal feature that was not respected in standard horizontal FFT technique is that respiratory signature is spread in propagation time. I propose algorithms that help to improve victim detectability via making use of this phenomenon. Performance of these algorithms is analyzed both theoretically and by means of experiments with simulated and measured radar data. It is concluded that SNR (Signal to Noise Ratio) improvement introduced via this approach over standard technique is in the order of several dB. With respect to radar as a tool for search and rescue, major problem is identified as strongly moving objects within antenna beam. In this thesis, two original algorithms for removing this perturbation are proposed. Both methods make use of respiratory motion looking very specific in the radargram which fact helps to separate it from other signal components. Algorithms show high performance in tests both with simulated and measured datasets. At the end problem of finding the person position is addressed. I present localization algorithm and test it with experimental radar data both in 2D and in 3D .It can be concluded that localization can be performed successfully we combining TOA/TDOA (Time of Arrival/ Time Difference of Arrival) estimates

Radar target classification by micro-Doppler contributions

This thesis studies non-cooperative automatic radar target classification. Recent developments in silicon-germanium and monolithic microwave integrated circuit technologies allows to build cheap and powerful continuous wave radars. Availability of radars opens new applications in different areas. One of these applications is security. Radars could be used for surveillance of huge areas and detect unwanted moving objects. Determination of the type of the target is essential for such systems. Microwave radars use high frequencies that reflect from objects of millimetre size. The micro-Doppler signature of a target is a time-varying frequency modulated contribution that arose in radar backscattering and caused by the relative movement of separate parts of the target. The micro-Doppler phenomenon allows to classify non-rigid moving objects by analysing their signatures. This thesis is focused on designing of automatic target classification systems based on analysis of micro-Doppler signatures. Analysis of micro-Doppler radar signatures is usually performed by second-order statistics, i.e. common energy-based power spectra and spectrogram. However, the information about phase coupling content in backscattering is totally lost in these energy-based statistics. This useful phase coupling content can be extracted by higher-order spectral techniques. We show that this content is useful for radar target classification in terms of improved robustness to various corruption factors. A problem of unmanned aerial vehicle (UAV) classification using continuous wave radar is covered in the thesis. All steps of processing required to make a decision out of the raw radar data are considered. A novel feature extraction method is introduced. It is based on eigenpairs extracted from the correlation matrix of the signature. Different classes of UAVs are successfully separated in feature space by support vector machine. Within experiments or real radar data, achieved high classification accuracy proves the efficiency of the proposed solutions. Thesis also covers several applications of the automotive radar due to very high growth in technologies for intelligent vehicle radar systems. Such radars are already build-in in the vehicle and ready for new applications. We consider two novel applications. First application is a multi-sensor fusion of video camera and radar for more efficient vehicle-to-vehicle video transmission. Second application is a frequency band invariant pedestrian classification by an automotive radar. This system allows us to use the same signal processing hardware/software for different countries where regulations vary and radars with different operating frequency are required. We consider different radar applications: ground moving target classification, aerial target classification, unmanned aerial vehicles classification, pedestrian classification. The highest priority is given to verification of proposed methods on real radar data collected with frequencies equal to 9.5, 10, 16.8, 24 and 33 GHz

Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring:A Review

Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made

時間と周波数領域情報に基づいたシステムモデリングとその応用

System modeling is required to deal with the time-varying system dynamics or the experimental data with insufficient information. However, the existing methods cannot construct satisfactory models for rapidly varying systems or severely band-limited signals. This thesis focuses on the new approaches to solve such system modeling problems based on time and frequency-domain information and illustrates their applications in time-varying channel identification and localization system. For the rapid time-varying systems, parameters can be approximated by the cosine series using virtual even periodic functions. Following the orthogonality of the trigonometric functions, the parameter estimation is recursively implemented by estimating the coefficients of each degree of the cosine harmonic term. For the localization system with insufficient frequency components, the spectral characteristics including phase information in frequency domain and the information evaluation in time domain are applied to improve the convergence performance. Numerical simulations demonstrate the effectiveness of the new approaches.北九州市立大

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Summary of Research 1994

The views expressed in this report are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.This report contains 359 summaries of research projects which were carried out under funding of the Naval Postgraduate School Research Program. A list of recent publications is also included which consists of conference presentations and publications, books, contributions to books, published journal papers, and technical reports. The research was conducted in the areas of Aeronautics and Astronautics, Computer Science, Electrical and Computer Engineering, Mathematics, Mechanical Engineering, Meteorology, National Security Affairs, Oceanography, Operations Research, Physics, and Systems Management. This also includes research by the Command, Control and Communications (C3) Academic Group, Electronic Warfare Academic Group, Space Systems Academic Group, and the Undersea Warfare Academic Group

SPICA:revealing the hearts of galaxies and forming planetary systems : approach and US contributions

How did the diversity of galaxies we see in the modern Universe come to be? When and where did stars within them forge the heavy elements that give rise to the complex chemistry of life? How do planetary systems, the Universe's home for life, emerge from interstellar material? Answering these questions requires techniques that penetrate dust to reveal the detailed contents and processes in obscured regions. The ESA-JAXA Space Infrared Telescope for Cosmology and Astrophysics (SPICA) mission is designed for this, with a focus on sensitive spectroscopy in the 12 to 230 micron range. SPICA offers massive sensitivity improvements with its 2.5-meter primary mirror actively cooled to below 8 K. SPICA one of 3 candidates for the ESA's Cosmic Visions M5 mission, and JAXA has is committed to their portion of the collaboration. ESA will provide the silicon-carbide telescope, science instrument assembly, satellite integration and testing, and the spacecraft bus. JAXA will provide the passive and active cooling system (supporting the

The Apertif Surveys:The First Six Months

Apertif is a new phased-array feed for the Westerbork Synthesis Radio Telescope (WSRT), greatly increasing its field of view and turning it into a natural survey instrument. In July 2019, the Apertif legacy surveys commenced; these are a time-domain survey and a two-tiered imaging survey, with a shallow and medium-deep component. The time-domain survey searches for new (millisecond) pulsars and fast radio bursts (FRBs). The imaging surveys provide neutral hydrogen (HI), radio continuum and polarization data products. With a bandwidth of 300 MHz, Apertif can detect HI out to a redshift of 0.26. The key science goals to be accomplished by Apertif include localization of FRBs (including real-time public alerts), the role of environment and interaction on galaxy properties and gas removal, finding the smallest galaxies, connecting cold gas to AGN, understanding the faint radio population, and studying magnetic fields in galaxies. After a proprietary period, survey data products will be publicly available through the Apertif Long Term Archive (ALTA, https://alta.astron.nl). I will review the progress of the surveys and present the first results from the Apertif surveys, including highlighting the currently available public data