Self-contained charge-coupled split-electrode filters using a novel sensing technique

Self-contained single-chip charge-coupled split-electrode filters with 55 taps and a novel channel structure have been built with a double-level polysilicon NMOS process. Operating at a sample rate of 32 kHz, these devices provide a low-pass filter function with a passband from 0 to 3.2 kHz and a stopband above 4 kHz. The image charge on the sense electrodes is detected with a novel sensing circuit employing two on-chip operational amplifiers, one of which suppresses the common-mode signal on the two sense buses while the other one integrates the difference signal. In addition, the chips carry antialiasing prefilters, a correlated double sample-and-hold circuit to minimize reset noise and to restore the output signal, and all the necessary peripheral logic and biasing circuitry so that the devices can be operated from a single master clock and two power supplies of +12 and -5 V, respectively.     

Noninvasive optical polarimetric glucose sensing using a true phasemeasurement technique

The focus of this paper was to describe the development and testing of a noninvasive true phase optical polarimetry sensing system to monitor in vivo glucose concentrations. To demonstrate the applicability of this optical sensor for glucose measurement, we first calibrated the system and then tested it in vitro using both a glass test cell filled with glucose solution in the physiologic range, with a path length of 0.9 cm to approximate one centimeter path length present in the anterior chamber of the eye, and then on an excised human eye. Our technique used helium neon laser light which was coupled through a rotating linear polarizer along with two stationary linear polarizers and two detectors to produce reference and signal outputs whose amplitudes varied sinusoidally with a frequency of twice the angular velocity of the rotating polarizer, and whose phase was proportional to the rotation of the linear polarization vector passing through the glucose solution.     

Forward-scatter frequency-derived distributed optical fibre sensing using the optical Kerr effect

A novel technique is proposed for forward-scatter frequency-derived distributed sensing along a birefringent singlemode optical fibre. This uses a pump probe scheme to generate a signal frequency in forward-scattered light by means of the optical Kerr effect. The sensing action has been demonstrated by applying transverse pressure to a section of the fibre.<>     

Performance of a WDM network based on stimulated Brillouinscattering

The use of stimulated Brillouin scattering as a tunable narrowband amplifier to demodulate, amplify, and select channels in a densely packed WDM (wave-division multiplexed) network is discussed. A 128-channel system configuration is tested with channel separation as small as 1.5 GHz and error rates below 10^-10. Direct FSK (frequency-shift-keyed) modulation of AlGaAs lasers and direct detection receivers are used. The experimental margin and noise analysis indicate that a 1000-channel system can be constructed with only these same components     

Joint channel estimation and data detection in MIMO-OFDM using distributed compressive sensing

Channel impulse response of a multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) channel contains a smaller number of nonzero components. In addition, locations of nonzero taps coincide in delay domain. So channel impulse responses can be modeled into an approximately group sparse signals. In this work we use extended sparse Bayesian learning (ESBL), a new method for multichannel compressive sensing for channel estimation in MIMO-OFDM. In joint extended sparse Bayesian learning (JESBL), both pilot and data subcarriers are utilized for channel estimation. These methods can reduce the number of pilot subcarriers in OFDM and improve the spectral efficiency of the MIMO-OFDM system.     

MFCC based real-time speech reproduction and recog-nition using distributed acoustic sensing technology

The distributed acoustic sensing technology was used for real-time speech reproduction and recognition,in which the voiceprint can be extracted by the Mel frequency cepstral coefficient(MFCC)method.A classic ancient Chinese poem\"You Zi Yin\",also called\"A Traveler's Song\",was analyzed both in time and frequency domains,where its real-time reproduction was achieved with a 116.91 ms time delay.The smaller scaled MFCC0 at 1/12 of MFCC matrix was tak-en as a feature vector of each line against the ambient noise,which provides a recognition method via cross-correlation among the 6 original and recovered verse pairs.The averaged cross-correlation coefficient of the matching pairs is calculated to be 0.580 6 higher than 0.188 3 of the nonmatched pairs,promising an accurate and fast method for real-time speech reproduction and recognition over a passive optical fiber.     

A distributed source coding technique for correlated images using turbo-codes

The Slepian-Wolf (1973) theorem states that the output of two correlated sources can be compressed to the same extent without loss, whether they communicate with each other or not, provided that decompression takes place at a joint decoder. We present a distributed source coding scheme for correlated images which uses modulo encoding of pixel values and encoding (compression) of the resulting symbols with binary and nonbinary turbo-codes, so that larger rate savings than using modulo encoding. alone are achieved, practically without loss.     

Magnetic levitation of a one DOF system using simultaneous actuation and displacement sensing technique

This paper discusses the development of a displacement self-sensing estimator for a one degree of freedom (DOF) magnetically levitated system using the parameter estimation technique. Current demodulation technique is known to be capable of extracting the air gap length from the coil current with demodulation filters. However, one of its main disadvantages is that its output is a function of the air gap length and the duty cycle of the PWM amplifiers. It is therefore demonstrated here, through computer simulation and experimental investigation, that the self-sensing parameter estimation technique is capable of removing the variable duty cycle from the estimated output. It is composed of two identical demodulation filters, one coil inductance simulator and one PI convergence controller. Benefiting from the closed loop characteristics of the self-sensing parameter estimation, not only is the influence of the duty cycle removed, but the dynamic characteristics of the selfsensing system are also greatly enhanced. The design of the analogue circuitries implementing the algorithm of the self-sensing parameter estimator is described. Very good agreement in the static and dynamic calibrations of the estimator output is observed, when compared with a dial gauge and commercial eddy current probe. While the self-sensing active magnetic bearing (AMB) system is levitated, excellent signal tracking capability of the parameter estimator is noted.     

Fiber Bragg grating period reconstruction using time-frequencysignal analysis and application to distributed sensing

The period and length of a fiber grating structure can be reconstructed from its corresponding complex reflection coefficient using time-frequency signal analysis based on Wigner-Ville and spectrogram distributions. We provide an experimental demonstration of this synthesis technique on two fiber grating structures and obtain good agreement between the reconstructed values and those expected based on the parameters used in their fabrication. We then propose and numerically demonstrate how this technique can be applied to distributed strain (or temperature) sensing     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

Radar ECCM based on phase-aid distributed compressive sensing

This paper proposes an electronic counter countermeasure (ECCM) technique to suppress randomly distributed multiple false targets generated by digital radio frequency memory-based electronic warfare equipment. Firstly, we present the modulation behaviors of deceptive multiple false targets jamming. Afterward, we discuss the ECCM potential of distributed compressive sensing (DCS) which not only could eliminate random distributed jamming signals but also could preserve the target echo. Further, an approach is proposed relying on phase-aided DCS to improve the performance against a special case of jamming signals that fall in the same range cell but with random amplitudes and phases. Finally, the suppression performances are evaluated through simulations illustrating the feasibility and validity of proposed algorithm.     

Frequency-derived distributed optical fibre sensing: signal-frequency downshifting

A method for downshifting the frequency of polarisation-optical time domain reflectometry signals has been demonstrated by optically mixing backscattered light from two semiconductor lasers simultaneously launched into a single mode fibre with bending birefringence. For lasers with wavelengths of 670 and 780 nm and 140 m of the fibre wound around a cylinder of radius 7.5 cm, approximately five downshifted beat cycles were obtained.<>     

微振动光纤传感系统光源的选择

搭建长距离分布式微振动光纤传感系统时光源的选择非常重要.结合传感系统实际使用背景,详细讨论了光源选择时需要考虑的功率、线宽、噪声等问题.针对上述问题,提出了具体选择的标准和减少光源相位噪声的方法.     

Current mirror saturation sensing technique

A technique for sensing the conduction state of the output transistor of a current mirror is shown to be more discriminating than a scheme previously described. The proposed circuit is applicable to the design of monolithic timers.     

压缩感知分布式多输入多输出高频雷达信息处理

为了提高高频雷达的空间分辨力,将分布式多载频多输入多输出(MIMO)体制应用于高频雷达。推导了分布式多载频MIMO雷达回波表达式,利用空间波数理论分析该体制不同区域的空间分辨能力。依据空间分辨力将观测区域进行网格化处理,构造速度信息的超完备字典。针对多角度同一分辨单元不同多普勒回波能量无法聚集及二维目标速度搜索导致的计算量过大问题,应用压缩感知算法,通过凸优化理论求解出不同信道下回波的散射系数,较好的解决了分布式MIMO雷达系统检测前相参综合问题。多视角频谱缺失导致目标回波较高旁瓣问题,也得到显著改善。     

Analysis of a laser phased array using a distributed Y-junctionanalog

An analysis is presented of a semiconductor-laser linear phased array which uses a distributed, evanescent-coupled version of Y-junction branches to achieve mode discrimination. As in the Y-junction array, the in-phase fundamental mode has the inherently highest round-trip gain. The advantage of easier mask generation and fabrication for the distributed coupler is offset by its poorer discrimination against higher order modes     

Dictionary learning based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient reconstruction by leveraging more realistic signal models that go beyond simple sparsity is still an open challenge. In this paper, we propose a novel “undersampled” correlation noise model to describe compressively sampled video signals, and present a maximum-likelihood dictionary learning based reconstruction algorithm for DCVS, in which both the correlation and sparsity constraints are included in a new probabilistic model. Moreover, the signal recovery in our algorithm is performed during the process of dictionary learning, instead of being employed as an independent task. Experimental results show that our proposal compares favorably with other existing methods, with 0.1–3.5 dB improvements in the average PSNR, and a 2–9 dB gain for non-key frames when key frames are subsampled at an increased rate.     

Spectrum sensing: A distributed approach for cognitive terminals

Cognitive radios is emerging in research laboratories as a promising wireless paradigm, which will integrate benefits of software defined radio with a complete aware communication behavior. To reach this goal many issues remain still open, such as powerful algorithms for sensing the external environment. This paper presents a further step in the direction of allowing cooperative spectrum sensing in peer-to-peer cognitive networks by using distributed detection theory. The approach aims at improving the radio awareness with respect to stand alone scenario as it is shown with theoretical and experimental results