Multidimensional signal processing and detection for storage systems with data-dependent transition noise

In the last decade, significant research on detection algorithms capable of mitigating the effects of colored Gaussian thermal noise and transition noise in storage systems, has been performed. In this paper, we present a new detection scheme based on a multidimensional detector front end and multidimensional linear prediction, applied to maximum a posteriori probability (MAP) sequence detection. This method improves the bit-error-rate (BER) performance with respect to previous approaches and makes the detector quite insensitive to transition noise. We show that the gain in terms of BER versus signal-to-noise ratio with our detector increases with the user density. The results obtained for a magnetic storage channel are extendable to optical storage systems as well.     

Intersymbol interference channels with signal-dependent non-Gaussian noise: estimation of achievable information rates

In this letter, we calculate the achievable information rates for the intersymbol interference channels with general signal-dependent correlated noise under the constraint that the inputs are chosen from a finite alphabet. The proposed method employs canonical multivariate density estimation techniques. This method is important in that it can be used for accurate estimation of the achievable information rates for magnetic recording channels with media noise, where higher order media noise models can be taken into account instead of the first-order model.     

Discrete magnitude-squared channel modeling, equalization, and detection for volume holographic storage channels

As storage density increases, the performance of volume holographic storage channels is degraded, because intersymbol interference and noise also increase. Equalization and detection methods must be employed to mitigate the effects of intersignal interference and noise. However, the output detector array in a holographic storage system detects the intensity of the incident light's wave front, leading to loss of sign information. This sign loss precludes the applicability of conventional equalization and detection schemes. We first address channel modeling under quadratic nonlinearity and develop an efficient model named the discrete magnitude-squared channel model. We next introduce an advanced equalization method called the iterative magnitude-squared decision feedback equalization (IMSDFE), which takes the channel nonlinearity into account. The performance of IMSDFE is quantified for optical-noise-dominated channels as well as for electronic-noise-dominated channels. Results indicate that IMSDFE is a good candidate for a high-density, high-intersignal-interference volume holographic storage channel.     

Multivariate numerical derivative by solving an inverse heat source problem

A method for approximating multivariate numerical derivatives is presented from multidimensional noise data in this paper. Starting from solving a direct heat conduction problem using the multidimensional noise data as an initial condition, we conclude estimations of the partial derivatives by solving an inverse heat source problem with an over-specified condition, which is the difference of the solution to the direct problem and the given noise data. Then, solvability and conditional stability of the proposed method are discussed for multivariate numerical derivatives, and a regularized optimization is adopted for overcoming instability of the inverse heat source problem. For achieving partial derivatives successfully and saving amount of computation, we reduce the multidimensional problem to a one-dimensional case, and give a corresponding algorithm with a posterior strategy for choosing regularization parameters. Finally, numerical examples show that the proposed method is feasible and stable to noise data.     

Quantization noise and its reduction in lensless Fourier digital holography

Digital holography is an imaging technique that enables recovery of topographic 3D information about an object under investigation. In digital holography, an interference pattern is recorded on a digital camera. Therefore, quantization of the recorded hologram is an integral part of the imaging process. We study the influence of quantization error in the recorded holograms on the fidelity of both the intensity and phase of the reconstructed image. We limit our analysis to the case of lensless Fourier off-axis digital holograms. We derive a theoretical model to predict the effect of quantization noise and we validate this model using experimental results. Based on this, we also show how the resultant noise in the reconstructed image, as well as the speckle that is inherent in digital holography, can be conveniently suppressed by standard speckle reduction techniques. We show that high-quality images can be obtained from binary holograms when speckle reduction is performed.     

Position sensing for high track density recording

Progress towardhigher digital areal densities is related to the data track position sensing accuracy obtainable in future disk drives. In most systems available, position sensing is done remotely from the data track and subject to different dimensional stability conditions. To obtain higher track densities, position sensing reference information must be moved near the data track. Several techniques are available to embed reference information in the data track. All the techniques described have one of two basic principles of operation. One method uses comparison of reference signal amplitudes and the second method uses arrival time differences of reference signals. The time method is relatively unknown but offers the designer some new alternatives. This paper describes an overview of several methods. Relationships are derived to relate the influence of noise on both basic methods. Linearity, relative hardware simplicity, and track capture range are also discussed. It is our conclusion that the Amplitude or Tri-Bit method offers the greatest hardware simplicity, but is limited by noise and non-linearity at high track densities. The time dependent or Chevron method requires two data channels, but offers a relatively higher noise immunity, better linearity, and higher data capacity.     

Real-time digital control of optical interferometers by the mechanical-modulation technique

We discuss the application of digital systems to the automatic control of dual-wave optical interferometers. We show that, if the mechanical-modulation technique is used for error-signal extraction, digital techniques can be used both for error-signal extraction and for control-signal generation. Therefore, apart from two front/end amplifiers that are necessary to match the dynamics of the detectors and actuators to the dynamics of the analog-to-digital converters and digital-to-analog converters, no other analog devices are required. In particular, the mechanical-modulation technique requires the synchronous demodulation of the photodiode output signal. Hence we need to implement a digital lock-in amplifier whose algorithm is described here. Finally, we describe one of the possible applications of this digital control procedure, such as the control of a classic Mach-Zehnder interferometer in air.     

Fringe pattern demodulation with a two-dimensional digital phase-locked loop algorithm

A novel technique called a two-dimensional digital phase-locked loop (DPLL) for fringe pattern demodulation is presented. This algorithm is more suitable for demodulation of fringe patterns with varying phase in two directions than the existing DPLL techniques that assume that the phase of the fringe patterns varies only in one direction. The two-dimensional DPLL technique assumes that the phase of a fringe pattern is continuous in both directions and takes advantage of the phase continuity; consequently, the algorithm has better noise performance than the existing DPLL schemes. The two-dimensional DPLL algorithm is also suitable for demodulation of fringe patterns with low sampling rates, and it outperforms the Fourier fringe analysis technique in this aspect.     

Complex-wave retrieval from a single off-axis hologram

We present a new digital two-step reconstruction method for off-axis holograms recorded on a CCD camera. First, we retrieve the complex object wave in the acquisition plane from the hologram's samples. In a second step, if required, we propagate the wave front by using a digital Fresnel transform to achieve proper focus. This algorithm is sufficiently general to be applied to sophisticated optical setups that include a microscope objective. We characterize and evaluate the algorithm by using simulated data sets and demonstrate its applicability to real-world experimental conditions by reconstructing optically acquired holograms.     

MEDUSA-32: A low noise, low power silicon strip detector front-end electronics, for space applications

In this report we describe a mixed analog-digital integrated circuit (IC) designed as the front-end electronics for silicon strip-detectors for space applications. In space power consumption, compactness and robustness become critical constraints for a pre-amplifier design. The IC is a prototype with 32 complete channels, and it is intended for a large area particle tracker of a new generation of gamma ray telescopes. Each channel contains a charge sensitive amplifier, a pulse shaper, a discriminator and two digital buffers. The reference trip point of the discriminator is adjustable. This chip also has a custom PMOSFET transistor per channel, included in order to provide the high dynamic resistance needed to reverse-bias the strip diode.

The digital part of the chip is used to store and serially shift out the state of the channels. There is also a storage buffer that allows the disabling of non-functioning channels if it is required by the data acquisition system.

An input capacitance of 30 pF introduced at the input of the front-end produces less than 1000 electrons of RMS equivalent noise charge (ENC), for a total power dissipation of only 60 μW per channel.

The chip was made using Orbit's 1.2 μm double poly, double metal n-well low noise CMOS process. The dimensions of the IC are 2400 μm × 8840 μm.     

Data-Aided Timing Recovery for Recording Channels With Data-Dependent Noise

In high-density data storage systems, noise becomes highly correlated and data dependent as a result of media noise, channel nonlinearities, and front-end filters. In such environments, conventional timing recovery schemes will exhibit large residual timing jitter and, especially, data-dependent timing jitter. This paper presents a new data-aided timing recovery algorithm for data storage systems with data-dependent noise. We derive a maximum-likelihood timing recovery scheme based on a data-dependent Gauss-Markov model of the noise. The timing recovery algorithm incorporates data-dependent noise prediction parameters in the form of linear prediction filters and prediction error variances. Moreover, because noise can be nonstationary in practice, we propose an adaptive algorithm to estimate and track the noise prediction parameters. Simulation results, for an idealized optical storage channel incorporating a simple model of media noise, illustrate the merits of our algorithm     

A framework for optimising the radiographic technique in digital X-ray imaging

The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possible by rapid digital image acquisition. However, this transition has taken place largely without optimising the radiographic technique used to acquire the images. This paper proposes a framework for optimising the acquisition of digital X-ray images. The proposed approach is based on the signal and noise characteristics of the digital images and the applied exposure. Signal is defined, based on the clinical task involved in an imaging application, as the difference between the detector signal with and without a target present against a representative background. Noise is determined from the noise properties of uniformly acquired images of the background, taking into consideration the absorption properties of the detector. Incident exposure is estimated or otherwise measured free in air, and converted to dose. The main figure of merit (FOM) for optimisation is defined as the signal-difference-to-noise ratio (SdNR) squared per unit exposure or (more preferably) dose. This paper highlights three specific technique optimisation studies that used this approach to optimise the radiographic technique for digital chest and breast applications. In the first study, which was focused on chest radiography with a CsI flat-panel detector, a range of kV(p) (50-150) and filtration (Z = 13-82) were examined in terms of their associated FOM as well as soft tissue to bone contrast, a factor of importance in digital chest radiography. The results indicated that additive Cu filtration can improve image quality. A second study in digital mammography using a selenium direct flat-panel detector indicated improved SdNR per unit exposure with the use of a tungsten target and a rhodium filter than conventional molybdenum target/molybdenum filter techniques. Finally, a third study focusing on cone-beam computed tomography of the breast using a CsI flat-panel detector indicated that high Z filtration of a tungsten target X-ray beam can notably improve the signal and noise characteristics of the image. The general findings highlight the fact that the techniques that are conventionally assumed to be optimum may need to be revisited for digital radiography.     

Signal processing for cryogenic micro-calorimetry

We describe electronics and signal processing techniques used to acquire data with our micro-calorimeters. The system includes front end electronics with cold FETs, an amplitude-independent trigger, pulse digitization and storage, and digital signal processing in software. We discuss some ideas for processing signals from devices which exhibit a variation in pulse shape.     

基于QR码的自适应抗打印扫描水印算法

目的提出一种基于QR码的自适应抗打印扫描盲水印算法。方法首先对载体QR码进行三级小波变换,并对低频部分进行4×4分块Schur分解,然后利用子块酉矩阵的系数差值的稳定性,将二值水印信息自适应嵌入到载体QR码中,最后对含水印QR码打印扫描并提取出水印信息。同时,算法实现了盲提取。结果算法能较好抵抗打印扫描攻击,并对高斯噪声、椒盐噪声、斑纹噪声、泊松噪声、JPEG压缩等攻击具有较强的鲁棒性。结论算法具有较强的抗打印扫描性能,可以广泛应用于数字产品的版权保护。     

基于最大相关熵准则的水下生物脉冲噪声消除方法

近海生物噪声表现为脉冲噪声,这一类噪声显著降低了水声通信系统的性能。结合水声信道的稀疏特性,提出一种基于最大相关熵准则的级联滤波器算法,该算法实现了脉冲噪声的消除及稀疏信道估计。第一级自适应滤波器完成对噪声的消除工作,第二级滤波器对去噪后的信号进行稀疏信道估计。该方法的优势在于无需知道信号和噪声的相关信息。仿真结果表明,提出的方法比单一的滤波器结构和传统信道估计算法性能更加优越。     

Enhancing time-stamp counter phase modulation measurements

This paper demonstrates that digital signal processing techniques can enhance the quality of phase modulation measurements produced by a time-stamp (phase digitizing) frequency counter. A typical time-stamp counter utilizes a digital divider to reduce signal frequency to the desired sample rate. Unfortunately, division also reduces phase modulation to the point where useful information may be obscured by counter measurement uncertainty (jitter). An analogy between an analog-to-digital converter (ADC) and a time-stamp counter predicts that the counter induced modulation can be modeled as random noise which is white in phase. The noise magnitude is directly related to the instrument's resolution specification. Fourier analysis, subject to some restrictions, can compute the power spectra of phase or frequency modulation, revealing even low level responses. A number of techniques can be used to reduce the amount of counter induced noise that appears on time domain plots of phase and frequency modulation. Experimental data, generated by a prototype counter, illustrates the type of results that can be expected from Fourier analysis and various noise reduction techniques     

Optimisation of dose per image in digital imaging

Three current digital radiography modalities are briefly described: digital fluorography, storage phosphor radiography and amorphous selenium radiography. For all of these modalities, the dose used to form an image can be varied considerably. Threshold contrast detail techniques were used to investigate the consequence of changing dose per image at the image receptor. At low doses, contrast resolution is limited by X ray quantum noise while system noise limits contrast resolution at high dose per image values.     

基于维纳滤波的红外焦平面非均匀性校正算法

针对焦平面阵列上各探测单元光电响应的非均匀性,本文使用了维纳滤波技术来实现红外焦平面阵列非均匀校正.该方法首先根据实际情况确定一个输出延迟,然后采用维纳滤波并借助前后帧信息对当前帧进行多次估计,最后取其均值作为此帧的最终校正结果.文中使用了真实红外图像对算法性能进行验证,由于能够充分利用过去和将来的场景信息,因而本算法可以有效地去除原图像上的固定图案噪声.     

Development of a Digital Signal Readout System for Large TES Arrays

We are developing a digital signal readout system for arrays of high-resolution gamma and fast-neutron detectors based on superconducting transition edge sensors (TESs). The readout system allows for real time data acquisition and analysis at count rates exceeding 100 Hz for pulses with several ∼ms decay times with minimal loss of energy resolution compared to optimum filtering. This digital signal processing system had originally been developed for gamma-ray analysis with HPGe detectors, and we have modified the hardware and firmware to accommodate the slower TES signals. Parameters of the filtering algorithm have been optimized to maximize either resolution or throughput. Here we present a summary of the digital signal processing hardware and discuss its initial performance.      

Underwater digital holography for studies of marine plankton

Conventional and digital holographies are proving to be increasingly important for studies of marine zooplankton and other underwater biological applications. This paper reports on the use of a subsea digital holographic camera (eHoloCam) for the analysis and identification of marine organisms and other subsea particles. Unlike recording on a photographic film, a digital hologram (e-hologram) is recorded on an electronic sensor and reconstructed numerically in a computer by simulating the propagation of the optical field in space. By comparison with other imaging techniques, an e-hologram has several advantages such as three-dimensional spatial reconstruction, non-intrusive and non-destructive interrogation of the recording sampling volume and the ability to record holographic videos. The basis of much work in optics lies in Maxwell's electromagnetic theory and holography is no exception: we report here on two of the numerical reconstruction algorithms we have used to reconstruct holograms obtained using eHoloCam and how their starting point lies in Maxwell's equations. Derivation of the angular spectrum algorithm for plane waves is provided as an exact method for the in-line numerical reconstruction of digital holograms. The Fresnel numerical reconstruction algorithm is derived from the angular spectrum method. In-line holograms are numerically processed before and after reconstruction to remove periodic noise from captured images and to increase image contrast. The ability of the Fresnel integration reconstruction algorithm to extend the reconstructed volume beyond the recording sensor dimensions is also shown with a 50% extension of the reconstruction area. Finally, we present some images obtained from recent deployments of eHoloCam in the North Sea and Faeroes Channel.