Wave-oriented data processing for frequency- and time-domain scattering by nonuniform truncated arrays

Understanding observable-based observables (OBP) phenomenology should make it possible to link observables, extracted from measured or computed data, to the wave mechanisms from which they originated, aiding in data inversion: we have referred to such a scenario as wave-oriented data processing. Thus, in wave-oriented data processing, one first parameterizes the forward problem in terms of a concise set of observables (forward problem), and then signal-processing algorithms are developed to extract these observables from data (inverse problem). To close the loop, we must show that the data processing algorithms extract wave phenomenology which is consistent with the forward OBP. The authors describe the forward and inverse phases of this strategy in greater detail. A general strategy is then implemented for a very specific scattering problem: frequency-domain (FD) and time domain (TD) scattering from periodic and weakly aperiodic arrays. That scattering problem is described and the results of their previous forward modeling are summarized. The remainder of the article emphasizes inverse, wave-oriented data processing. Processing options for phase-space processing are summarized,and the results for FD and TD scattering are presented.<>     

Wave-oriented processing of scattered field data from aplane-wave-excited finite array of filaments on an infinite dielectricslab

In a companion paper, we presented the formulation and solution for time-harmonic plane wave fields scattered by truncated periodic and aperiodic arrays of infinitely long filaments on an infinite dielectric slab. The solution was constructed so as to highlight the coupled phenomenologies associated with slab loading of the Floquet mode beams characteristic of the truncated arrays and with the slab-guided leaky modes excited by these arrays. Asymptotic reduction of the solution yielded a parameterization of the scattered fields and a numerically accurate algorithm, based on physically observable ray- and mode-field constituents. This study is concerned with the inverse procedure of extracting from the scattered field data the phenomenological footprints of the scattering mechanisms found by forward problem asymptotics; this information is relevant to target classification and identification. The data processing tools involve Gaussian windowed transforms and superresolution algorithms that yield projections onto appropriate subdomains of the (space)-(spectral wave number) phase space. A variety of examples demonstrate physically and quantitatively the interplay of Floquet-mode and leaky-mode phenomena, and how these are affected by changes in the problem parameters. Of special interest is the performance of superresolution algorithms for “cleaning up” the diffuse Gaussian windowed phase space distributions, in the absence and presence of system noise     

N阶色散媒质的FDTD法与数字信号处理技术

提出了一种新的N阶色散媒质的时域分析方法,并将其表征为一组无限冲击响应滤波器,将色散媒质在FDTD中的表述问题转化为数字滤波器(IIR)的设计问题.改进FDTD能分析处理与频率有关的电磁场问题.为验证此方法的有效性和可靠性,用此方法计算了高斯平面波脉冲入射N阶色散媒质的情况,计算结果与解析值非常吻合.     

基于组件的雷达信号及数据处理仿真方法

不同体制雷达系统的信号及数据处理在共性功能模拟和特性功能刻画之间存在矛盾问题。基于组件化设计思想,将雷达信号处理及数据处理仿真划分为天线模拟、目标回波功率计算、脉冲压缩、参数测量、航迹起始、跟踪滤波、调度策略等28个组件。通过参数选择实现不同体制雷达特性功能模拟组件的设置,并对共性功能组件复用,实现了相控阵、机扫、无源探测等多种雷达体制的功能级仿真。对各组件进行功能测试,验证了组件化设计方法的可行性。     

Listen to your data [signal processing applications]

This paper gives emphasis on the importance of testing the performance of signal processing algorithms with real data and learning from the data. The discussion is made primarily within the context of a patient monitoring research. The author suggests six steps on how to test with and learn from real data. These steps are: (1) minimize measurement uncertainty so your physiological phenomenon is consistently observable, (2) understand your data, (3) acquire a significant number of appropriate training and testing sets, (4) construct high-performance validation criteria, (5) design algorithms that can generalize in the clinical environment, and (6) test and learn from your data. Results show that this process is also applicable to other fields as well.     

Multichannel signal processing for data communications in thepresence of crosstalk

Transceiver designs for multiple coupled channels typically treat the crosstalk between adjacent twisted pairs as random noise uncorrelated with the transmitted signal. The authors propose a transmitter/receiver pair that compensates for crosstalk by treating an entire bundle of twisted pairs as a single multi-input/multi-output channel with a (slowly varying) matrix transfer function. The proposed transceiver uses multichannel adaptive FIR filters to cancel near- and far-end crosstalk, and to pre- and postprocess the input/output of the channel. Linear pre- and postprocessors that minimize mean squared error between the received and transmitted signal in the presence of both near- and far-end crosstalk are derived. The performance of an adaptive near-end crosstalk canceller using the stochastic gradient (least-mean-square) transversal algorithm is illustrated by numerical simulation. Plots of mean squared error versus time and eye diagrams are presented, assuming a standard transmission line model for the channel. A signal design algorithm that maps a vector input bit stream to a stream of channel symbol vectors is also presented and illustrated explicitly for s simple model of two coupled channels     

高速数字信号处理采集数据的存贮

本文针对高速数字信号处理技术中存在的数据接口问题,分析了几种数据存贮结构,在此基础上给出了一种性能/价格比较优的总线隔离的数据存贮器直接存贮数据接口结构。     

SDH信号中DCME数据的检测处理技术

SDH信号中的虚容器VC-12是承载DCME数据的主要部分,文章通过分析简化其中各层数据的帧格式提出了一套可行的设计方案,用于初步实现SDH信号中DCME数据从前期检测到后期处理的流程,从而达到数据分析的目的.     

Knowledge-based radar signal and data processing: a tutorial review

Radar systems are an important component in military operations. In response to increasingly severe threats from military targets with reduced radar cross sections (RCSs), slow-moving and low-flying aircraft hidden in foliage, and in environments with large numbers of targets, knowledge-based (KB) signal and data processing techniques offer the promise of significantly improved performance of all radar systems. Radars under KB control can be deployed to utilize valuable resources such as airspace or runways more effectively and to aid human operators in carrying out their missions. As battlefield scenarios become more complex with increasing numbers of sensors and weapon systems, the challenge will be to use already available information effectively to enhance radar performance, including positioning, waveform selection, and modes of operation. KB processing fills this need and helps meet the challenge.     

Jitter model and signal processing techniques for high-densityoptical data storage

The author discusses a jitter model and signal processing techniques for data recovery in pulse width modulation (PWM) optical recording. A high-speed counter clock is used to convert time marks to amplitude marks, and signal processing techniques are used to minimize jitter according to the jitter model. The jitter model considered takes into account jitter from both the write and read processes, and the signal processing techniques include: velocity and intersymbol interference equalization; differential interleaving detection (DID); additive interleaving detection (AID); differential interleaving modulation (DIM); and additive interleaving modulation (AIM). These techniques are found to be effective in reducing the mark error rate (MER). Various modulation codes can be used in addition to the signal processing techniques to achieve better modulation efficiency     

Randomized data selection in detection with applications to distributed signal processing

Performing robust detection with resource limitations such as low-power requirements or limited communication bandwidth is becoming increasingly important in contexts involving distributed signal processing. One way to address these constraints consists of reducing the amount of data used by the detection algorithms. Intelligent data selection in detection can be highly dependent on a priori information about the signal and noise. In this paper, we explore detection strategies based on randomized data selection and analyze the resulting algorithms' performance. Randomized data selection is a viable approach in the absence of reliable and detailed a priori information, and it provides a reasonable lower bound on signal processing performance as more a priori information is incorporated. The randomized selection procedure has the added benefits of simple implementation in a distributed environment and limited communication overhead. As an example of detection algorithms based upon randomized selection, we analyze a binary hypothesis testing problem, and determine several useful properties of detectors derived from the likelihood ratio test. Additionally, we suggest an adaptive detector that accounts for fluctuations in the selected data subset. The advantages and disadvantages of this approach in distributed sensor networks applications are also discussed.     

Aperture-domain signal processing

An elementary reconsideration of first principles in aperture-domain processing of wave phenomena for reception (and, by reciprocity, for transmission) can yield revealing, and in some cases novel, insights into what can or cannot be achieved. The subjects covered here include direction-selective reception, superdirectivity, direction finding, focused near-field reception, circular arrays and circular modes in such arrays, and the new concepts of arrays composed of `random symmetrical pairs', and of real gain in omnidirectional receiving antennas. The ideas are basic to all wave directional analysis and imagining applications, be they electromagnetic or acoustic, in radar or sonar, communications, navigation, surveillance or medical imaging     

Baseband signal processing

The baseband signal processing of the ALTAIR wireless in-building network (WIN) is described. The discussion covers the 19-GHz oscillator, burst processing, packet detection, symbol clock synchronization and gain and offset correction. The algorithms described are carried out in a single ASIC composed of 60000 active gates. The implemented procedures allow for parallel processing, which significantly reduces the computation time and therefore leads to preserving high bandwidth efficiency. The learning processes that acquire information about packet parameters and the adjustment operations in the receivers are executed in 3 μs     

Quantum signal processing

In this article we present a signal processing framework that we refer to as quantum signal processing (QSP) (Eldar 2001) that is aimed at developing new or modifying existing signal processing algorithms by borrowing from the principles of quantum mechanics and some of its interesting axioms and constraints. However, in contrast to such fields as quantum computing and quantum information theory, it does not inherently depend on the physics associated with quantum mechanics. Consequently, in developing the QSP framework we are free to impose quantum mechanical constraints that we find useful and to avoid those that are not. This framework provides a unifying conceptual structure for a variety of traditional processing techniques and a precise mathematical setting for developing generalizations and extensions of algorithms, leading to a potentially useful paradigm for signal processing with applications in areas including frame theory, quantization and sampling methods, detection, parameter estimation, covariance shaping, and multiuser wireless communication systems. We present a general overview of the key elements in quantum physics that provide the basis for the QSP framework and an indication of the key results that have so far been developed within this framework. In the remainder of the article, we elaborate on the various elements in this figure.     

Electrical signal processing

This text presents a new approach to the processing of complicated signals. The method proposed provides the possibility of decomposing a complicated fluctuating signal into a deterministic part and a stochastic part. A procedure for finding a differential equation related to the deterministic part is presented