223 research outputs found

    Design of large polyphase filters in the Quadratic Residue Number System

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    MEMS based radar sensor for automotive collision avoidance

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    This dissertation presents the architecture of a new MEMS based 77 GHz frequency modulated continuous wave (FMCW) automotive long range radar sensor. The design, modeling, and fabrication of a novel MEMS based TE10 mode Rotman lens. MEMS based Single-pole-triple-throw (SP3T) RF switches and an inset feed type microstrip antenna array that form the core components of the newly developed radar sensor. The novel silicon based Rotman lens exploits the principle of a TE10 mode rectangular waveguide that enabled to realize the lens in silicon using conventional microfabrication technique with a cavity depth of 50 Όm and a footprint area to 27 mm x 36.2 mm for 77 GHz operation. The microfabricated Rotman lens replaces the conventional microelectronics based analog or digital beamformers as used in state-of-the-art automotive long range radars to results in a smaller form-factor superior performance less complex low cost radar sensor. The developed Rotman lens has 3 beam ports, 5 array ports, 6 dummy ports and HFSS simulation exhibits better than -2 dB insertion loss and better than -20 dB return loss between the beam ports and the array ports. A MEMS based 77 GHz SP3T cantilever type RF switch with conventional ground connecting bridges (GCB) has been designed, modelled, and fabricated to sequentially switch the FMCW signal among the beam ports of the Rotman lens. A new continuous ground (CG) SP3T switch has been designed and modeled that shows a 4 dB improvement in return loss, 0.5 dB improvement in insertion loss and an isolation improvement of 3.5 dB over the conventional GCB type switch. The fabrication of the CG type switch is in progress. Both the switches have a footprint area of 500 ”m x 500 Όm. An inset feed type 77 GHz microstrip antenna array has been designed, modelled, and fabricated on a Duroid 5880 substrate using a laser ablation technique. The 12 mm x 35 mm footprint area antenna array consists of 5 sub-arrays with 12 microstrip patches in each of the sub-arrays. HFSS simulation result shows a gain of 18.3 dB, efficiency of 77% and half power beam width of 9°

    Ultra-Wideband Secure Communications and Direct RF Sampling Transceivers

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    Larger wireless device bandwidth results in new capabilities in terms of higher data rates and security. The 5G evolution is focus on exploiting larger bandwidths for higher though-puts. Interference and co-existence issues can also be addressed by the larger bandwidth in the 5G and 6G evolution. This dissertation introduces of a novel Ultra-wideband (UWB) Code Division Multiple Access (CDMA) technique to exploit the largest bandwidth available in the upcoming wireless connectivity scenarios. The dissertation addresses interference immunity, secure communication at the physical layer and longer distance communication due to increased receiver sensitivity. The dissertation presents the design, workflow, simulations, hardware prototypes and experimental measurements to demonstrate the benefits of wideband Code-Division-Multiple-Access. Specifically, a description of each of the hardware and software stages is presented along with simulations of different scenarios using a test-bench and open-field measurements. The measurements provided experimental validation carried out to demonstrate the interference mitigation capabilities. In addition, Direct RF sampling techniques are employed to handle the larger bandwidth and avoid analog components. Additionally, a transmit and receive chain is designed and implemented at 28 GHz to provide a proof-of-concept for future 5G applications. The proposed wideband transceiver is also used to demonstrate higher accuracy direction finding, as much as 10 times improvement

    Temperature aware power optimization for multicore floating-point units

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    Distributed digital subarray antennas

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    A system that incorporates distributed digital subarrays working cooperatively as a single array can potentially increase the output signal-to-noise ratio and provide better spatial resolution compared with using the subarrays individually. However, collectively combining periodic widely separated subarrays results in unacceptable grating lobes, and these lobes cannot be suppressed using traditional windowing methods. In this research, we focus on distributed subarray antennas that are comprised of subarrays that can operate individually or collectively. We develop techniques for grating lobe suppression on both the transmitting and receiving sides of the distributed array system. Traditional solutions and new methods are examined in detail via numerical simulation to quantify the performance limitations when applied in combination. One contribution of this research is a hybrid approach that uses a combination of suppression techniques on both the transmitting and receiving sides. Another contribution is the development of new receiving processing methods to suppress grating lobes and improve the signal-to-clutter ratio and signal-to-interference ratio. A final contribution shows the relationship between thermal noise, array errors, and the grating lobe suppression effectiveness. The consideration of array errors addresses the issue of array calibration and synchronization, which are critical concerns when multiple arrays operate coherently.http://archive.org/details/distributeddigit1094538927Major, Taiwan ArmyApproved for public release; distribution is unlimited

    Applications of compressive sensing to direction of arrival estimation

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    Die SchĂ€tzung der Einfallsrichtungen (Directions of Arrival/DOA) mehrerer ebener Wellenfronten mit Hilfe eines Antennen-Arrays ist eine der prominentesten Fragestellungen im Gebiet der Array-Signalverarbeitung. Das nach wie vor starke Forschungsinteresse in dieser Richtung konzentriert sich vor allem auf die Reduktion des Hardware-Aufwands, im Sinne der KomplexitĂ€t und des Energieverbrauchs der EmpfĂ€nger, bei einem vorgegebenen Grad an Genauigkeit und Robustheit gegen Mehrwegeausbreitung. Diese Dissertation beschĂ€ftigt sich mit der Anwendung von Compressive Sensing (CS) auf das Gebiet der DOA-SchĂ€tzung mit dem Ziel, hiermit die KomplexitĂ€t der EmpfĂ€ngerhardware zu reduzieren und gleichzeitig eine hohe Richtungsauflösung und Robustheit zu erreichen. CS wurde bereits auf das DOA-Problem angewandt unter der Ausnutzung der Tatsache, dass eine Superposition ebener Wellenfronten mit einer winkelabhĂ€ngigen Leistungsdichte korrespondiert, die ĂŒber den Winkel betrachtet sparse ist. Basierend auf der Idee wurden CS-basierte Algorithmen zur DOA-SchĂ€tzung vorgeschlagen, die sich durch eine geringe RechenkomplexitĂ€t, Robustheit gegenĂŒber Quellenkorrelation und FlexibilitĂ€t bezĂŒglich der Wahl der Array-Geometrie auszeichnen. Die Anwendung von CS fĂŒhrt darĂŒber hinaus zu einer erheblichen Reduktion der Hardware-KomplexitĂ€t, da weniger EmpfangskanĂ€le benötigt werden und eine geringere Datenmenge zu verarbeiten und zu speichern ist, ohne dabei wesentliche Informationen zu verlieren. Im ersten Teil der Arbeit wird das Problem des Modellfehlers bei der CS-basierten DOA-SchĂ€tzung mit gitterbehafteten Verfahren untersucht. Ein hĂ€ufig verwendeter Ansatz um das CS-Framework auf das DOA-Problem anzuwenden ist es, den kontinuierlichen Winkel-Parameter zu diskreditieren und damit ein Dictionary endlicher GrĂ¶ĂŸe zu bilden. Da die tatsĂ€chlichen Winkel fast sicher nicht auf diesem Gitter liegen werden, entsteht dabei ein unvermeidlicher Modellfehler, der sich auf die SchĂ€tzalgorithmen auswirkt. In der Arbeit wird ein analytischer Ansatz gewĂ€hlt, um den Effekt der Gitterfehler auf die rekonstruierten Spektra zu untersuchen. Es wird gezeigt, dass sich die Messung einer Quelle aus beliebiger Richtung sehr gut durch die erwarteten Antworten ihrer beiden Nachbarn auf dem Gitter annĂ€hern lĂ€sst. Darauf basierend wird ein einfaches und effizientes Verfahren vorgeschlagen, den Gitterversatz zu schĂ€tzen. Dieser Ansatz ist anwendbar auf einzelne Quellen oder mehrere, rĂ€umlich gut separierte Quellen. FĂŒr den Fall mehrerer dicht benachbarter Quellen wird ein numerischer Ansatz zur gemeinsamen SchĂ€tzung des Gitterversatzes diskutiert. Im zweiten Teil der Arbeit untersuchen wir das Design kompressiver Antennenarrays fĂŒr die DOA-SchĂ€tzung. Die Kompression im Sinne von Linearkombinationen der Antennensignale, erlaubt es, Arrays mit großer Apertur zu entwerfen, die nur wenige EmpfangskanĂ€le benötigen und sich konfigurieren lassen. In der Arbeit wird eine einfache Empfangsarchitektur vorgeschlagen und ein allgemeines Systemmodell diskutiert, welches verschiedene Optionen der tatsĂ€chlichen Hardware-Realisierung dieser Linearkombinationen zulĂ€sst. Im Anschluss wird das Design der Gewichte des analogen Kombinations-Netzwerks untersucht. Numerische Simulationen zeigen die Überlegenheit der vorgeschlagenen kompressiven Antennen-Arrays im Vergleich mit dĂŒnn besetzten Arrays der gleichen KomplexitĂ€t sowie kompressiver Arrays mit zufĂ€llig gewĂ€hlten Gewichten. Schließlich werden zwei weitere Anwendungen der vorgeschlagenen AnsĂ€tze diskutiert: CS-basierte VerzögerungsschĂ€tzung und kompressives Channel Sounding. Es wird demonstriert, dass die in beiden Gebieten durch die Anwendung der vorgeschlagenen AnsĂ€tze erhebliche Verbesserungen erzielt werden können.Direction of Arrival (DOA) estimation of plane waves impinging on an array of sensors is one of the most important tasks in array signal processing, which have attracted tremendous research interest over the past several decades. The estimated DOAs are used in various applications like localization of transmitting sources, massive MIMO and 5G Networks, tracking and surveillance in radar, and many others. The major objective in DOA estimation is to develop approaches that allow to reduce the hardware complexity in terms of receiver costs and power consumption, while providing a desired level of estimation accuracy and robustness in the presence of multiple sources and/or multiple paths. Compressive sensing (CS) is a novel sampling methodology merging signal acquisition and compression. It allows for sampling a signal with a rate below the conventional Nyquist bound. In essence, it has been shown that signals can be acquired at sub-Nyquist sampling rates without loss of information provided they possess a sufficiently sparse representation in some domain and that the measurement strategy is suitably chosen. CS has been recently applied to DOA estimation, leveraging the fact that a superposition of planar wavefronts corresponds to a sparse angular power spectrum. This dissertation investigates the application of compressive sensing to the DOA estimation problem with the goal to reduce the hardware complexity and/or achieve a high resolution and a high level of robustness. Many CS-based DOA estimation algorithms have been proposed in recent years showing tremendous advantages with respect to the complexity of the numerical solution while being insensitive to source correlation and allowing arbitrary array geometries. Moreover, CS has also been suggested to be applied in the spatial domain with the main goal to reduce the complexity of the measurement process by using fewer RF chains and storing less measured data without the loss of any significant information. In the first part of the work we investigate the model mismatch problem for CS based DOA estimation algorithms off the grid. To apply the CS framework a very common approach is to construct a finite dictionary by sampling the angular domain with a predefined sampling grid. Therefore, the target locations are almost surely not located exactly on a subset of these grid points. This leads to a model mismatch which deteriorates the performance of the estimators. We take an analytical approach to investigate the effect of such grid offsets on the recovered spectra showing that each off-grid source can be well approximated by the two neighboring points on the grid. We propose a simple and efficient scheme to estimate the grid offset for a single source or multiple well-separated sources. We also discuss a numerical procedure for the joint estimation of the grid offsets of closer sources. In the second part of the thesis we study the design of compressive antenna arrays for DOA estimation that aim to provide a larger aperture with a reduced hardware complexity and allowing reconfigurability, by a linear combination of the antenna outputs to a lower number of receiver channels. We present a basic receiver architecture of such a compressive array and introduce a generic system model that includes different options for the hardware implementation. We then discuss the design of the analog combining network that performs the receiver channel reduction. Our numerical simulations demonstrate the superiority of the proposed optimized compressive arrays compared to the sparse arrays of the same complexity and to compressive arrays with randomly chosen combining kernels. Finally, we consider two other applications of the sparse recovery and compressive arrays. The first application is CS based time delay estimation and the other one is compressive channel sounding. We show that the proposed approaches for sparse recovery off the grid and compressive arrays show significant improvements in the considered applications compared to conventional methods
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