2,660 research outputs found

    Multi-Core DSP Based Parallel Architecture for FMCW SAR Real-Time Imaging

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    This paper presents an efficient parallel processing architecture using multi-core Digital Signal Processor (DSP) to improve the capability of real-time imaging for Frequency Modulated Continuous Wave Synthetic Aperture Radar (FMCW SAR). With the application of the proposed processing architecture, the imaging algorithm is modularized, and each module is efficiently realized by the proposed processing architecture. In each module, the data processing of different cores is executed in parallel, also the data transmission and data processing of each core are synchronously carried out, so that the processing time for SAR imaging is reduced significantly. Specifically, the time of corner turning operation, which is very time-consuming, is ignored under computationally intensive case. The proposed parallel architecture is applied to a compact Ku-band FMCW SAR prototype to achieve real-time imageries with 34 cm x 51 cm (range x azimuth) resolution

    Motion Compensation for Near-Range Synthetic Aperture Radar Applications

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    The work focuses on the analysis of influences of motion errors on near-range SAR applications and design of specific motion measuring and compensation algorithms. First, a novel metric to determine the optimum antenna beamwidth is proposed. Then, a comprehensive investigation of influences of motion errors on the SAR image is provided. On this ground, new algorithms for motion measuring and compensation using low cost inertial measurement units (IMU) are developed and successfully demonstrated

    Head and Neck MRA at 3.0T

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    3.0T MRI scanners are becoming more widely used in clinical practice, particularly for neurological applications. The increased signal‐to‐noise ratio (SNR) provided by 3.0T compared to 1.5T is particularly useful for applications like magnetic resonance angiography (MRA). A protocol to image the intracranial circulation with 3‐D time of flight (3DTOF), and a protocol to image the carotid, vertebral, and basilar arteries with contrast‐enhanced MRA are presented. The increased SNR at 3.0T is used to increase the spatial resolution. For the 3DTOF exam, the acquisition time is also reduced with the use of parallel imaging.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145280/1/cpmia0708.pd

    Head and Neck MRA at 3.0T

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    3.0T MRI scanners are becoming more widely used in clinical practice, particularly for neurological applications. The increased signal‐to‐noise ratio (SNR) provided by 3.0T compared to 1.5T is particularly useful for applications like magnetic resonance angiography (MRA). A protocol to image the intracranial circulation with 3‐D time of flight (3DTOF), and a protocol to image the carotid, vertebral, and basilar arteries with contrast‐enhanced MRA are presented. The increased SNR at 3.0T is used to increase the spatial resolution. For the 3DTOF exam, the acquisition time is also reduced with the use of parallel imaging.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145280/1/cpmia0708.pd

    Amicus Curiae, October 20, 1953

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    https://scholarship.law.gwu.edu/amicus_curiae_1953/1000/thumbnail.jp

    Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 314)

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    This bibliography lists 139 reports, articles, and other documents introduced into the NASA scientific and technical information system in August, 1988

    RF MEMS reference oscillators platform for wireless communications

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    A complete platform for RF MEMS reference oscillator is built to replace bulky quartz from mobile devices, thus reducing size and cost. The design targets LTE transceivers. A low phase noise 76.8 MHz reference oscillator is designed using material temperature compensated AlN-on-silicon resonator. The thesis proposes a system combining piezoelectric resonator with low loading CMOS cross coupled series resonance oscillator to reach state-of-the-art LTE phase noise specifications. The designed resonator is a two port fundamental width extensional mode resonator. The resonator characterized by high unloaded quality factor in vacuum is designed with low temperature coefficient of frequency (TCF) using as compensation material which enhances the TCF from - 3000 ppm to 105 ppm across temperature ranges of -40˚C to 85˚C. By using a series resonant CMOS oscillator, phase noise of -123 dBc/Hz at 1 kHz, and -162 dBc/Hz at 1MHz offset is achieved. The oscillator’s integrated RMS jitter is 106 fs (10 kHz–20 MHz), consuming 850 μA, with startup time is 250μs, achieving a Figure-of-merit (FOM) of 216 dB. Electronic frequency compensation is presented to further enhance the frequency stability of the oscillator. Initial frequency offset of 8000 ppm and temperature drift errors are combined and further addressed electronically. A simple digital compensation circuitry generates a compensation word as an input to 21 bit MASH 1 -1-1 sigma delta modulator incorporated in RF LTE fractional N-PLL for frequency compensation. Temperature is sensed using low power BJT band-gap front end circuitry with 12 bit temperature to digital converter characterized by a resolution of 0.075˚C. The smart temperature sensor consumes only 4.6 μA. 700 MHz band LTE signal proved to have the stringent phase noise and frequency resolution specifications among all LTE bands. For this band, the achieved jitter value is 1.29 ps and the output frequency stability is 0.5 ppm over temperature ranges from -40˚C to 85˚C. The system is built on 32nm CMOS technology using 1.8V IO device

    Small business innovation research. Abstracts of completed 1987 phase 1 projects

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    Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

    A multivariable sampled-data model of an automobile driver

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    In this thesis, a multivariable system model of driver performance in the basic driving tasks is presented. The driver model described acts as a serial-process, priority-accessed, time-sharing computer. This model processes the input or output task which currently possesses the highest priority. Input tasks are represented by continuous signals sampled intermittently according to priority laws. Output tasks are modeled as simple analog processes operating on the last few intermittently generated output controls. An individual priority rule is constructed for each input and output task. The performance of the driver in the lateral control task involves a feedforward pattern which is consequence of the fact the driver looks several feet ahead of the pathway. A laboratory analysis of the feedforward aspects of the driver in the single-input single-output lateral control task is described --Abstract, page ii

    A Short-Range FMCW Radar-Based Approach for Multi-Target Human-Vehicle Detection

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    In this article, a new microwave-radar-based technique for short-range detection and classification of multiple human and vehicle targets crossing a monitored area is proposed. This approach, which can find applications in both security and infrastructure surveillance, relies upon the processing of the scattered-field data acquired by low-cost off-The-shelf components, i.e., a 24 GHz frequency-modulated continuous wave (FMCW) radar module and a Raspberry Pi mini-PC. The developed method is based on an ad hoc processing chain to accomplish the automatic target recognition (ATR) task, which consists of blocks performing clutter and leakage removal with an infinite impulse response (IIR) filter, clustering with a density-based spatial clustering of applications with noise (DBSCAN) approach, tracking using a Benedict-Bordner alphaalpha -etaeta filter, features extraction, and finally classification of targets by means of a kk-nearest neighbor ( kk-NN) algorithm. The approach is validated in real experimental scenarios, showing its capabilities in correctly detecting multiple targets belonging to different classes (i.e., pedestrians, cars, motorcycles, and trucks)
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