1,652 research outputs found

    Communications techniques and equipment: A compilation

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    This Compilation is devoted to equipment and techniques in the field of communications. It contains three sections. One section is on telemetry, including articles on radar and antennas. The second section describes techniques and equipment for coding and handling data. The third and final section includes descriptions of amplifiers, receivers, and other communications subsystems

    Design and Implementation of a FPGA and DSP Based MIMO Radar Imaging System

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    The work presented in this paper is aimed at the implementation of a real-time multiple-input multiple-output (MIMO) imaging radar used for area surveillance. In this radar, the equivalent virtual array method and time-division technique are applied to make 16 virtual elements synthesized from the MIMO antenna array. The chirp signal generater is based on a combination of direct digital synthesizer (DDS) and phase locked loop (PLL). A signal conditioning circuit is used to deal with the coupling effect within the array. The signal processing platform is based on an efficient field programmable gates array (FPGA) and digital signal processor (DSP) pipeline where a robust beamforming imaging algorithm is running on. The radar system was evaluated through a real field experiment. Imaging capability and real-time performance shown in the results demonstrate the practical feasibility of the implementation

    A fully integrated SRAM-based CMOS arbitrary waveform generator for analog signal processing

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    This dissertation focuses on design and implementation of a fully-integrated SRAM-based arbitrary waveform generator for analog signal processing applications in a CMOS technology. The dissertation consists of two parts: Firstly, a fully-integrated arbitrary waveform generator for a multi-resolution spectrum sensing of a cognitive radio applications, and an analog matched-filter for a radar application and secondly, low-power techniques for an arbitrary waveform generator. The fully-integrated low-power AWG is implemented and measured in a 0.18-¥ìm CMOS technology. Theoretical analysis is performed, and the perspective implementation issues are mentioned comparing the measurement results. Moreover, the low-power techniques of SRAM are addressed for the analog signal processing: Self-deactivated data-transition bit scheme, diode-connected low-swing signaling scheme with a short-current reduction buffer, and charge-recycling with a push-pull level converter for power reduction of asynchronous design. Especially, the robust latch-type sense amplifier using an adaptive-latch resistance and fully-gated ground 10T-SRAM bitcell in a 45-nm SOI technology would be used as a technique to overcome the challenges in the upcoming deep-submicron technologies.Ph.D.Committee Chair: Kim, Jongman; Committee Member: Kang, Sung Ha; Committee Member: Lee, Chang-Ho; Committee Member: Mukhopadhyay, Saibal; Committee Member: Tentzeris, Emmanouil

    The GEOSAT Follow-on (GFO) Altimeter

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    The NAVY GEOSAT Mission (1985-1990) demonstrated the ability of an altimeter equipped satellite to provide global measurements of mesoscale ocean features with 3 centimeter precision. The GEOSAT radar altimeter, developed by JHU/APL, was an enormous success. Built with early 1980\u27s technology, the GEOSAT altimeter weighed 191 pounds and consumed 146 watts. The GFO radar altimeter, under development by E-Systems Inc., will achieve the GEOSAT measurement capability, but at one-third the weight and one-half the power (48 pounds, excluding antenna, and 76 watts). The GFO altimeter uses the same proven linear FM waveform, pulse repetition frequency (PRF), pulse compression technique, and alpha-beta tracker design as the GEOSAT radar altimeter, but takes advantage of current RF and digital signal processing technologies to produce an instrument that is both light-weight and reliable. Also, thanks to a cooperative working relationship with JHU/APL, the GFO radar altimeter design encompasses lessons learned from both the GEOSAT and TOPEX programs. Analysis of the range, waveheight, and back-scattering cross section performance indicates that the GFO altimeter will achieve the GEOSAT performance in all areas. Finally, the GFO altimeter design encompasses features allowing economical expansion; including a C-band channel for improved range accuracy, and a 33% higher PRF for improved instrument noise performance. The GFO dual-channel altimeter would weigh 107 pounds and consume 156 watts

    Electronically synthesized Nyquist pulses for photonic sampling of microwave signals

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    We report electronic generation of optical Nyquist pulses using an arbitrary waveform generator (AWG) followed by a Mach Zehnder modulator (MZM), providing a simple, highly stable and flexible technique to perform photonic sampling. Here, we demonstrate the generation of 10 GHz periodic optical Nyquist pulses by synthesizing both all-positive and alternate positive-negative electrical pulse trains using a 25 GHz bandwidth AWG. Biasing the MZM at null ensures the meeting of the Nyquist ISI-free criterion in the optical domain and allows for pulse compression. Moreover, we report the first photonic sampling and demodulation of 1 Gbaud 16- and 32-QAM signals up to 22.5 GHz using 10 GHz optical Nyquist sampling pulse trains

    Application of Soft Computing Techniques to RADAR Pulse Compression

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    Soft Computing is a term associated with fields characterized by the use of inexact solutions to computationally-hard tasks for which an exact solution cannot be derived in polynomial time. Almost contrary to conventional (Hard) computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. Effectively, it resembles the Human Mind. The Soft Computing Techniques used in this project work are Adaptive Filter Algorithms and Artificial Neural Networks. An adaptive filter is a filter that self-adjusts its transfer function according to an optimizing algorithm. The adaptive filter algorithms used in this project work are the LMS algorithm, the RLS algorithm, and a slight variation of RLS, the Modified RLS algorithm. An Artificial Neural Network (ANN) is a mathematical model or computational model that tries to simulate the structure and/or functional aspects of biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. Several models have been designed to realize an ANN. In this project, Multi-Layer Perceptron (MLP) Network is used. The algorithm used for modeling such a network is Back-Propagation Algorithm (BPA). Through this project, there has been analyzed a possibility for using the Adaptive Filter Algorithms to determine optimum Matched Filter Coefficients and effectively designing Multi-Layer Perceptron Networks with adequate weight and bias parameters for RADAR Pulse Compression. Barker Codes are taken as system inputs for Radar Pulse Compression. In case of Adaptive Filters, a convergence rate analysis has also been performed for System Identification and in case of ANN, Function Approximation using a 1-2-1 neural network has also been dealt with. A comparison of the adaptive filter algorithms has been performed on the basis of Peak Sidelobe Ratio (PSR). Finally, SSRs are obtained using MLPs of varying neurons and hidden layers and are then compared under several criteria like Noise Performance and Doppler Tolerance

    Expandable and reconfigurable instrument node arrays

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    An expandable and reconfigurable instrument node includes a feature detection means and a data processing portion in communication with the feature detection means, the data processing portion configured and disposed to process feature information. The instrument node further includes a phase locked loop (PLL) oscillator in communication with the data processing portion, the PLL oscillator configured and disposed to provide PLL information to the processing portion. The instrument node further includes a single tone transceiver and a pulse transceiver in communication with the PLL oscillator, the single tone transceiver configured and disposed to transmit or receive a single tone for phase correction of the PLL oscillator and the pulse transceiver configured and disposed to transmit and receive signals for phase correction of the PLL oscillator. The instrument node further includes a global positioning (GPA) receiver in communication with the processing portion, the GPS receiver configured and disposed to establish a global position of the instrument node

    Transmit Signal Design for MIMO Radar and Massive MIMO Channel Estimation

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    The widespread availability of antenna arrays and the capability to independently control signal emissions from each antenna make transmit signal design increasingly important for radar and wireless communication systems. In the rst part of this work, we develop the framework for a MIMO radar transmit scheme which trades o waveform diversity for beampattern directivity. Time-division beamforming consists of a linear precoder that provides direct control of the transmit beampattern and is able to form multiple transmit beams in a single pulse. The MIMO receive ambiguity function, which incorporates the receiver structure, reveals a space and delay-Doppler separability that emphasizes the importance of the transmit-receive beampattern and single-input single-output (SISO) ambiguity function. The second part of this work focuses on channel estimation for massive MIMO systems. As the size of arrays increase, conventional channel estimation techniques no longer remain practical. In current systems, training sequences probe wireless channels in orthogonal directions to obtain channel state information for block fading channels. The training overhead becomes signicant as the number of transmit antennas increases, thereby creating a need for alternative channel estimation techniques. In this work, we relax the orthogonal restriction on the sounding vectors and introduce a feedback channel to enable closed-loop sounding vector design. A probability of misalignment framework is introduced, which provides a measure to sequentially design sounding vectors
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