基于压缩感知的多中继协作通信系统稀疏信道估计算法研究

提出了一种基于压缩感知理论的多中继协作通信系统稀疏信道估计方法.采用正交匹配追踪（Orthogonal Matching Pursuit,OMP）压缩感知算法,对时域信道脉冲响应进行估计.对多中继协作通信系统进行稀疏建模;结合压缩感知理论构建观测矩阵,并给出卷积信道的稀疏表示;利用压缩信道感知算法重建了系统的卷积复合信道.仿真结果表明,与传统的最小二乘法（Least Square,LS）相比,采用压缩感知理论的信道估计算法,能利用较少的导频信号获得很好的信道估计性能,提高了频谱利用率.     

A compressive sensing algorithm using truncated SVD for three-dimensional laser imaging of space-continuous targets

For traditional array 3-D laser radars, the resolution of the intensity image and range profile is limited by the number and accuracy of sensors. Moreover, for a space-continuous target, peak detection in the pulsed time of flight is no longer suitable for super-resolution reconstruction algorithms. Hence, a compressive sensing algorithm for 3-D laser imaging is proposed. A range observation matrix composed of time interval basis vectors is constructed to acquire the range information regarding a target. However, the range observation matrix is generally ill-posed owing to the spatial continuity of the target. To address this shortage, truncated singular value decomposition is utilized to extract the peak values of echo pulses for image reconstruction. Simulation results demonstrate the effectiveness and performance of the proposed algorithm.     

Gated viewing laser imaging with compressive sensing

We present a prototype of gated viewing laser imaging with compressive sensing (GVLICS). By a new framework named compressive sensing, it is possible for us to perform laser imaging using a single-pixel detector where the transverse spatial resolution is obtained. Moreover, combining compressive sensing with gated viewing, the three-dimensional (3D) scene can be reconstructed by the time-slicing technique. The simulations are accomplished to evaluate the characteristics of the proposed GVLICS prototype. Qualitative analysis of Lissajous-type eye-pattern figures indicates that the range accuracy of the reconstructed 3D images is affected by the sampling rate, the image's noise, and the complexity of the scenes.     

Online dynamic cardiac imaging based on the elastic-net model

Purpose: The purpose of this work was to develop an online dynamic cardiac MRI model to reconstruct image frames from partial acquisition of the Cartesian k-space data, which utilizes structural knowledge of consecutive image frames. Materials and methods: Using an elastic-net model, the proposed algorithm reconstructs dynamic images using both L₁ and L₂ norm operations. The L₁ norm enforces the sparsity of the frame difference, while the L₂ norm with motion-adaptive weights catches the internal structure of frame differences. Unlike other online methods such as the Kalman filter (KF) technique, the new model requires no assumption of Gaussian noise, and can faithfully reconstruct the dynamic images within a compressive sensing framework. Results: The proposed method was evaluated using simulated dynamic phantoms with 40 frames of images (128?×?128) and a cardiac MRI cine of 25 frames (256?×?256). Both results showed that the new model offered a better performance than the online KF method in depicting simulated phantom and cardiac dynamics. Conclusion: It is concluded that the proposed imaging model can be used to capture a large variety of objects in motion from highly under-sampled k-space data, and being particularly useful for improving temporal resolution of cardiac MRI.     

Multiple-image encryption scheme via compressive sensing and orthogonal encoding based on double random phase encoding

We propose an optical multiple-image encryption scheme based on compressive sensing and double random phase encoding. The orthogonal encoding method is used for integrating and extracting multiple-image compressed sampling data. In the encryption process, each plain image is sampled by compressive sensing and the sampled data of all the images are integrated into a synthesized ciphertext by orthogonal encoding method. The synthesized ciphertext is re-encrypted through the double random phase encoding technique to form final ciphertext. In order to reduce the data of keys, chaotic matrix, of which only the initial value should be memorized, is employed in the compressive sampling process and double random phase encoding process. Numerical simulation and the analysis of attacks on encrypted image are implemented to demonstrate the security and validity of the proposed approach.     

基于里德堡原子的电场传感技术

概述了基于里德堡原子的电场传感技术的基本原理,分析了里德堡原子电场测量具有的高灵敏度、宽频、可溯源至国际单位制（International System of Units, SI）、高空间分辨力等优势。讨论了激光参数、探测器噪声、环境电磁场干扰等因素对里德堡原子场强测量灵敏度与测量频率响应带宽的影响,介绍了频率调制、重泵浦、参数优化等提高场强测量灵敏度的方式,并阐述了单辅助场原子外差法、双辅助五能级外差法等提升测量频率响应带宽的方法。探讨了里德堡原子电场传感技术在计量、通信、雷达、成像等方面的应用情况,指出应通过优化原子气室结构、设计高性能光电探测器、提升光学腔性能等方式进一步提高里德堡原子电场测量灵敏度;应深入研究里德堡原子电场测量的不确定度来源,并对里德堡原子传感器进行全面的测试和表征;应开展里德堡原子电场测量相关装置的小型化、工程化设计研究,从而进一步提升里德堡原子电场测量技术的实际应用性能。     

基于深度压缩感知的语音增强模型

随着压缩感知的深入研究,压缩感知在语音增强方面的应用也备受关注。针对传统压缩感知语音增强算法中存在的不足,将压缩感知与深度学习结合构建名为基于深度压缩感知的语音增强模型(Speech Enhancement based on Deep Compressed Sensing, SEDCS)。基于压缩感知原理使用编解码模型代替压缩感知中语音信号稀疏过程,使用卷积神经网络代替测量矩阵实现语音信号观测降维过程,通过联合训练的方式实现语音增强。实验结果表明：该模型能够完成语音增强任务,并且与现有的压缩感知语音增强算法相比,该模型能取得较好的语音增强效果;相比利用深度学习的语音增强算法,该模型虽性能一般,但在模型泛化性能和测试阶段的增强时间效率上有一定提升。     

A New Platform for Modeling Ferroelectric Devices

High-performance models are required during the design (phase) of sensing devices in order to take their physical behavior into account and to include these models in calculations and simulations aimed at optimizing the performance of devices in fixed operating conditions. In this paper, the problem of model fitting for ferroelectric devices is addressed; in particular, a model of the behavior of a ferroelectric capacitor is accomplished. The static behavior of such devices is investigated, and an experimental setup for both characterization and model estimation is proposed. The model obtained is assessed, and the uncertainty introduced by the measurement system is estimated     

Space-time compressive imaging

Compressive imaging systems typically exploit the spatial correlation of the scene to facilitate a lower dimensional measurement relative to a conventional imaging system. In natural time-varying scenes there is a high degree of temporal correlation that may also be exploited to further reduce the number of measurements. In this work we analyze space-time compressive imaging using Karhunen-Loève (KL) projections for the read-noise-limited measurement case. Based on a comprehensive simulation study, we show that a KL-based space-time compressive imager offers higher compression relative to space-only compressive imaging. For a relative noise strength of 10% and reconstruction error of 10%, we find that space-time compressive imaging with 8×8×16 spatiotemporal blocks yields about 292× compression compared to a conventional imager, while space-only compressive imaging provides only 32× compression. Additionally, under high read-noise conditions, a space-time compressive imaging system yields lower reconstruction error than a conventional imaging system due to the multiplexing advantage. We also discuss three electro-optic space-time compressive imaging architecture classes, including charge-domain processing by a smart focal plane array (FPA). Space-time compressive imaging using a smart FPA provides an alternative method to capture the nonredundant portions of time-varying scenes.     

An iterative synthetic aperture imaging algorithm with correction of diffraction effects

In this paper we present an iterative version of the synthetic aperture imaging algorithm extended synthetic aperture technique (ESAFT) proposed recently. The algorithm is based on a linear model that accounts for the distortions effects of an imaging system used for acquisition of ultrasonic data. Improved resolution (both lateral and temporal) in the reconstructed image is obtained as a result of minimizing the reconstruction mean square error. In this work, the minimization is extended to parameters that characterize expected amplitudes of each image element in the area of interest. An iterative optimization scheme is proposed, which in each step performs minimization of the reconstruction error based on the parameter matrix found in the previous step. Comparing to ESAFT, the proposed approach yields a significant improvement in resolution and a high degree of robustness with regard to initial choice of the parameter matrix. Performance of the proposed algorithm is evaluated using both real and simulated ultrasonic data.     

Folic acid mediated synthesis of hierarchical ZnO micro-flower with improved gas sensing properties

The microscale structure and size are extremely important factors for gas sensing materials. In this study, hierarchical flower-like ZnO architectures were synthesized by a biomolecular mediated route. The influence of various experiment parameters including reaction time, pH value, and reaction temperature on the formation of ZnO architectures was studied. When used as sensing material, this material possesses a higher sensing response towards ethanol and formaldehyde. Towards 100 ppm of ethanol and formaldehyde, the ZnO sensor can display remarkable sensing responses (R_a/R_g) of 13.6 and 16.5, respectively. These values are higher than or comparable to most of reported ZnO-based gas sensors. In addition, the sensors can show obvious sensing response to 5 ppm of ethanol and formaldehyde, indicating the lower limit of detection. It is proposed that the unique hierarchical microstructure contributes to the enhanced sensing performance.     

Optical image encryption based on compressive sensing and chaos in the fractional Fourier domain

We propose a novel image encryption algorithm based on compressive sensing (CS) and chaos in the fractional Fourier domain. The original image is dimensionality reduction measured using CS. The measured values are then encrypted using chaotic-based double-random-phase encoding technique in the fractional Fourier transform domain. The measurement matrix and the random-phase masks used in the encryption process are formed from pseudo-random sequences generated by the chaotic map. In this proposed algorithm, the final result is compressed and encrypted. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys for distribution simultaneously. Numerical experiments verify the validity and security of the proposed algorithm.     

Genetic algorithm-least squares support vector regression based predicting and optimizing model on carbon fiber composite integrated conductivity

Support vector machine (SVM), which is a new technology solving classification and regression, has been widely used in many fields. In this study, based on the integrated conductivity(including conductivity and tensile strength) data obtained by carbon fiber/ABS resin matrix composites experiment, a predicting and optimizing model using genetic algorithm-least squares support vector regression (GA-LSSVR) was developed. In this model, genetic algorithm (GA) was used to select and optimize parameters. The predicting results agreed with the experimental data well. By comparing with principal component analysis-genetic back propagation neural network (PCA-GABPNN) predicting model, it is found that GA-LSSVR model has demonstrated superior prediction and generalization performance in view of small sample size problem. Finally, an optimized district of performance parameters was obtained and verified by experiments. It concludes that GA-LSSVR modeling method provides a new promising theoretical method for material design.     

碳纤维和SiO2纳米颗粒增强环氧树脂复合材料的压缩性能

纤维增强聚合物复合材料的压缩性能与聚合物基体力学性质密切相关。本文利用连续碳纤维（CF）和含有均匀分散的SiO₂纳米颗粒改性的环氧树脂基体,制备了CF-nano SiO₂/Epoxy微纳米多相复合材料单向层合板,并对其轴向压缩性能进行了系统的研究。试验表明,将纳米颗粒引入基体能够有效提高纤维增强聚合物基复合材料的压缩强度,占nano SiO₂/Epoxy体积为8.7%的纳米颗粒可将复合材料的压缩强度提升约62.7%。基于单向层合板的弹塑性微屈曲模型对纳米颗粒的增强效应进行了理论分析。根据含纳米颗粒的环氧树脂在压缩过程中的损伤行为,提出了一套基于加卸载试验建立纳米复合材料基体压缩本构关系的方法。将模型获得的基体本构关系与经典复合材料弹塑性微屈曲模型耦合,能够较为准确地预测本研究制备的微纳米多相复合材料的压缩强度。经试验检验,预测结果与实测数值达到很好的一致性。      

Informative Sensor and Feature Selection via Hierarchical Nonnegative Garrote

Placing sensors in every station of a process or every element of a system to monistor its state or performance is usually too expensive or physically impossible. Therefore, a systematic method is needed to select important sensing variables. The method should not only be capable of identifying important sensors/signals among multistream signals from a distributed sensing system, but should also be able to extract a small set of interpretable features from the high-dimensional vector of a selected signal. For this purpose, we develop a new hierarchical regularization approach called hierarchical nonnegative garrote (NNG). At the first level of hierarchy, a group NNG is used to select important signals, and at the second level, the individual features within each signal are selected using a modified version of NNG that possesses good properties for the estimated coefficients. Performance of the proposed method is evaluated and compared with other existing methods through Monte Carlo simulation. A case study is conducted to demonstrate the proposed methodology that can be applied to develop a predictive model for the assessment of vehicle design comfort based on the tested drivers’ motion trajectory signals. This article has supplementary material online.     

Crosswind sensing from optical-turbulence-induced fluctuations measured by a video camera

We present a novel method for remote sensing of crosswind using a passive imaging device, such as a video recorder. The method is based on spatial and temporal correlations of the intensity fluctuations of a naturally illuminated scene induced by atmospheric turbulence. Adaptable spatial filtering, taking into account variations of the dominant spatial scales of the turbulence (due to changes in meteorological conditions, such as turbulence strength, or imaging device performance, such as frame rate or spatial resolution), is incorporated into this method. Experimental comparison with independent wind measurement using anemometers shows good agreement.     

压缩感知在医学超声成像中的仿真应用研究

为了解决医学超声成像系统中面临的采样率高,数据量大的问题,提出将压缩感知理论方法用于医学超声成像。首先建立了超声信号在时域的稀疏表达模型,然后利用模拟信息转换器对信号进行稀疏采样,最后使用最优化方法完成回波信号重建,利用合成发射孔径方式完成最终超声成像。为了验证算法的有效性,利用Field II对点目标以及复杂组织目标进行了仿真实验,在均方误差、分辨率、对比度以及成像质量上与常规成像结果对比分析。结果表明,采用1/2奈奎斯特采样频率,以30%原始数据所完成的成像仍然可保证良好的图像质量。采用压缩感知理论可以大幅度降低医学超声系统的采样率及总数据量。     

Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materials

In this study, we propose and evaluate a method for spectral characterization of acousto-optic tunable filter (AOTF) hyperspectral imaging systems in the near-infrared (NIR) spectral region from 900 nm to 1700 nm. The proposed spectral characterization method is based on the SRM-2035 standard reference material, exhibiting distinct spectral features, which enables robust non-rigid matching of the acquired and reference spectra. The matching is performed by simultaneously optimizing the parameters of the AOTF tuning curve, spectral resolution, baseline, and multiplicative effects. In this way, the tuning curve (frequency-wavelength characteristics) and the corresponding spectral resolution of the AOTF hyperspectral imaging system can be characterized simultaneously. Also, the method enables simple spectral characterization of the entire imaging plane of hyperspectral imaging systems. The results indicate that the method is accurate and efficient and can easily be integrated with systems operating in diffuse reflection or transmission modes. Therefore, the proposed method is suitable for characterization, calibration, or validation of AOTF hyperspectral imaging systems.     

Comparison of conventional parallel beamforming with plane wave and diverging wave imaging for cardiac applications: a simulation study

When imaging the heart, good temporal resolution is beneficial for capturing the information of short-lived cardiac phases (in particular, the isovolumetric phases). To increase the frame rate, parallel beamforming is a commonly used technique for fast cardiac imaging. Conventionally, a 4 multiple-line-acquisition (4MLA) system increases the frame rate by a factor of 4, making use of a broadened transmit beam to reduce block-like artifacts. As an alternative, it has been proposed to transmit an unfocused beam (i.e., plane wave or diverging wave) for which a large number of parallel receive beams (i.e., 16) can be formed for each transmit. However, to keep the spatial resolution acceptable in these approaches, spatial compounding of overlapping successive transmits is required. As a result, the effective gain in frame rate is similar to that of a 4MLA system. To date, it remains unclear how conventional 4MLA compares to plane-wave or diverging-wave imaging when operating at similar frame rate. The goal of this study was therefore to directly contrast the performance of these beamforming methods by computer simulation. In this study, the performance of 4 different imaging systems was investigated by quantitatively evaluating the characteristics of their beam profiles. The results showed that the conventional 4MLA and plane wave imaging were very competitive imaging strategies when operating at a similar frame rate. 4MLA performed better in the near field (i.e., 10 to 50 mm), whereas plane-wave imaging had better beam profiles in the far field (i.e., 50 to 90 mm). Although diverging-wave imaging had the poorest performance in the present study, it could potentially be improved by optimizing the settings.     

Effect of aberrations and scatter on image resolution assessed by adaptive optics retinal section imaging

The effect of increased high-order wavefront aberrations on image resolution was investigated, and the performance of adaptive optics (AO) for correcting wavefront error in the presence of increased light scatter was assessed in a model eye. An AO section imaging system provided an oblique view of a model retina and incorporated a wavefront sensor and deformable mirror for measurement and compensation of wavefront aberrations. Image resolution was quantified by the width of a Lorentzian curve fitted to a laser line image. Wavefront aberrations were significantly reduced with AO, resulting in improvement of image resolution. In the model eye, image resolution was degraded with increased high-order wavefront aberrations (horizontal coma and spherical) and improved with AO correction of wavefront error in the presence of increased light scatter. The findings of the current study suggest that AO imaging systems can potentially improve image resolution in aging eyes with increased aberrations and scatter.