283 research outputs found

    Turbo Bayesian Compressed Sensing

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    Compressed sensing (CS) theory specifies a new signal acquisition approach, potentially allowing the acquisition of signals at a much lower data rate than the Nyquist sampling rate. In CS, the signal is not directly acquired but reconstructed from a few measurements. One of the key problems in CS is how to recover the original signal from measurements in the presence of noise. This dissertation addresses signal reconstruction problems in CS. First, a feedback structure and signal recovery algorithm, orthogonal pruning pursuit (OPP), is proposed to exploit the prior knowledge to reconstruct the signal in the noise-free situation. To handle the noise, a noise-aware signal reconstruction algorithm based on Bayesian Compressed Sensing (BCS) is developed. Moreover, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is developed for joint signal reconstruction by exploiting both spatial and temporal redundancy. Then, the TBCS algorithm is applied to a UWB positioning system for achieving mm-accuracy with low sampling rate ADCs. Finally, hardware implementation of BCS signal reconstruction on FPGAs and GPUs is investigated. Implementation on GPUs and FPGAs of parallel Cholesky decomposition, which is a key component of BCS, is explored. Simulation results on software and hardware have demonstrated that OPP and TBCS outperform previous approaches, with UWB positioning accuracy improved by 12.8x. The accelerated computation helps enable real-time application of this work

    Compressed Sensing Applied to Weather Radar

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    We propose an innovative meteorological radar, which uses reduced number of spatiotemporal samples without compromising the accuracy of target information. Our approach extends recent research on compressed sensing (CS) for radar remote sensing of hard point scatterers to volumetric targets. The previously published CS-based radar techniques are not applicable for sampling weather since the precipitation echoes lack sparsity in both range-time and Doppler domains. We propose an alternative approach by adopting the latest advances in matrix completion algorithms to demonstrate the sparse sensing of weather echoes. We use Iowa X-band Polarimetric (XPOL) radar data to test and illustrate our algorithms.Comment: 4 pages, 5 figrue

    Decentralized Turbo Bayesian ompressed Sensing with application to UWB Systems

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    In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is proposed to provide an efficient approach to transfer and incorporate this redundant information for joint sparse signal reconstruction. As a case study, the TBCS algorithm is applied in Ultra-Wideband (UWB) systems. A space-time TBCS structure is developed for exploiting and incorporating the spatial and temporal a priori information for space-time signal reconstruction. Simulation results demonstrate that the proposed TBCS algorithm achieves much better performance with only a few measurements in the presence of noise, compared with the traditional Bayesian Compressed Sensing (BCS) and multitask BCS algorithms

    Noncontact Vital Signs Detection

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    Human health condition can be accessed by measurement of vital signs, i.e., respiratory rate (RR), heart rate (HR), blood oxygen level, temperature and blood pressure. Due to drawbacks of contact sensors in measurement, non-contact sensors such as imaging photoplethysmogram (IPPG) and Doppler radar system have been proposed for cardiorespiratory rates detection by researchers.The UWB pulse Doppler radars provide high resolution range-time-frequency information. It is bestowed with advantages of low transmitted power, through-wall capabilities, and high resolution in localization. However, the poor signal to noise ratio (SNR) makes it challenging for UWB radar systems to accurately detect the heartbeat of a subject. To solve the problem, phased-methods have been proposed to extract the phase variations in the reflected pulses modulated by human tiny thorax motions. Advance signal processing method, i.e., state space method, can not only be used to enhance SNR of human vital signs detection, but also enable the micro-Doppler trajectories extraction of walking subject from UWB radar data.Stepped Frequency Continuous Wave (SFCW) radar is an alternative technique useful to remotely monitor human subject activities. Compared with UWB pulse radar, it relieves the stress on requirement of high sampling rate analog-to-digital converter (ADC) and possesses higher signal-to-noise-ratio (SNR) in vital signs detection. However, conventional SFCW radar suffers from long data acquisition time to step over many frequencies. To solve this problem, multi-channel SFCW radar has been proposed to step through different frequency bandwidths simultaneously. Compressed sensing (CS) can further reduce the data acquisition time by randomly stepping through 20% of the original frequency steps.In this work, SFCW system is implemented with low cost, off-the-shelf surface mount components to make the radar sensors portable. Experimental results collected from both pulse and SFCW radar systems have been validated with commercial contact sensors and satisfactory results are shown

    A Mobile, Multichannel, UWB Radar for Potential Ice Core Drill Site Identification in East Antarctica: Development and First Results

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    We developed a high-performance, multichannel, ultra-wideband radar system for measurements of the base and interior of the East Antarctic Ice Sheet. We designed the radar to be of high power (4000-W peak) yet portable and to be able to operate with 60-MHz bandwidth at a center frequency of 200 MHz, providing high sensitivity and fine vertical resolution relative to current technology. We used the radar to perform extensive measurements as a part of a multinational collaboration. We collected data onboard a tracked vehicle outfitted with an array of high-gain antennas. We sounded 2- to 3-km thick ice near Dome Fuji. Preliminary ice thickness data match those obtained via semicoincident measurements performed with a different surface-based pulse-modulated radar system operated during the same field campaign, as well as previous airborne measurements. In addition, we mapped internal reflection horizons with fine vertical resolution from 300 m below the ice surface to ~100 m above the bed. In this article, we provide a detailed overview of the radar instrument design, implementation, and field measurement setup. We present sample data to illustrate its capabilities and discuss how the data collected with it will be valuable for the assessment of promising drilling sites to recover ice cores that are 0.9-1.5 million years old

    A Mobile, Multichannel, UWB Radar for Potential Ice Core Drill Site Identification in East Antarctica: Development and First Results

    Get PDF
    We developed a high-performance, multichannel, ultra-wideband radar system for measurements of the base and interior of the East Antarctic Ice Sheet. We designed the radar to be of high power (4000-W peak) yet portable and to be able to operate with 60-MHz bandwidth at a center frequency of 200 MHz, providing high sensitivity and fine vertical resolution relative to current technology. We used the radar to perform extensive mea- surements as a part of a multinational collaboration. We collected data onboard a tracked vehicle outfitted with an array of high-gain antennas. We sounded 2- to 3-km thick ice near Dome Fuji. Prelim- inary ice thickness data match those obtained via semicoincident measurements performed with a different surface-based pulse- modulated radar system operated during the same field campaign, as well as previous airborne measurements. In addition, we mapped internal reflection horizons with fine vertical resolution from 300 m below the ice surface to ∼100 m above the bed. In this article, we provide a detailed overview of the radar instrument design, implementation, and field measurement setup. We present sample data to illustrate its capabilities and discuss how the data collected with it will be valuable for the assessment of promising drilling sites to recover ice cores that are 0.9–1.5 million years old
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