Overview of digital signal processing algorithms, part II - Part 10 in a series of tutorials in instrumentation and measurement

Digital signal processing (DSP) is the process of taking a signal and performing an algorithm on it to analyze, modify, or better identify that signal. To take advantage of DSP advances, one must have at least a basic understanding of DSP theory along with an understanding of the hardware architecture designed to support these new advances. There are several programming techniques that maximize the efficiency of the DSP hardware, as well as a few fundamental concepts used to implement DSP software. This tutorial will touch on the fundamental concepts of DSP theory and algorithms and also provide an overview of the implementation and optimization of DSP software.     

Compressive sensing and sparse decomposition in precision machining process monitoring: From theory to applications

Precision machining has been claimed to be the backbone to modern industry. It has been widely applied to the key parts’ production in the aerospace, medical and automotive industries. One of the main problems related to precision machining productivity and safety is the machining condition. By utilizing the acquired information from sensory measurements to direct the further actions, the signal processing bridges the gap between human instruction and full automation. Traditional signal acquisition and processing methods are mainly based on Shannon’s Sampling theory, Fourier methods or wavelet analysis. While these techniques meet challenges in precision machining environment, such as machining at high speed, low signal to noise ratio, and high sampling rate. These factors limit their applications especially the online monitoring implementation. The newly developed compressive sensing theory and sparse decomposition techniques provide a possible solution to these problems, while limited studies have been investigated. This paper serves as an introduction to the theory and shows the theory’s potentials in machining condition monitoring by reviewing related literatures and demonstrating case studies from real experiments.     

星上多载波解调技术研究

新一代具有星上处理的卫星将急剧降低地球站的复杂度,星上多载波解调(MCD)技术就是在星上分离出各个信道然后再独立解调。研究了星上多路信号即FDMA/QPSK信号的多载波技术,这是一种重要的星上处理技术,它包括频分多路信号的FFT分路算法、频偏估计、多路QPSK信号的全数字化解调算法和解调算法中的位定时恢复方法等。对主要的关键技术进行了计算机仿真。     

超宽带载波包络调制及其频谱相关解调

针对超宽带载波包络调制的频谱特性,提出新颖的正交梳状频谱相关解调方法,将超宽带脉冲信号的处理从时域扩展到了频域。阐述了该解调方式的基本原理和设计思路,推导了正交梳状频谱的载波选择原则。对系统性能的分析和仿真证明了频域相关解调的方法有着和时域解调相同的误码率性能。该方法接收机结构简单、成本低,可由全数字电路实现,便于采用其它数字信号处理技术进一步提高系统性能。     

Computer-aided modeling, analysis, and design of communicationnetworks

Computer-aided design, analysis, and simulation techniques for communication networks are surveyed. The focus is on analytic and simulation techniques that are either amendable to, or require, implementation on a computer. Issues relating to the implementation of these techniques on a computer as well as their embodiment in software tools are addressed. Past and present work in these areas is surveyed, the application of these techniques to network performance modeling and analysis is discussed, and promising directions for future research are indicated     

Implementation of adaptive and synthetic-aperture processingschemes in integrated active-passive sonar systems

Progress in the implementation of state-of-the-art signal processing schemes in sonar systems is limited mainly by the moderate advance made in sonar computing architectures and the lack of operational evaluation of the advanced processing schemes. Until recently, matrix-based processing techniques, such as adaptive and synthetic-aperture processing, could not be efficiently implemented in the current type of sonar systems, even though it is widely believed that they have advantages that can address the requirements associated with the difficult operational problems that next-generation sonars will have to solve. Interestingly, adaptive and synthetic-aperture techniques may be viewed by other disciplines as conventional schemes. For the sonar technology discipline, however, they are considered as advanced schemes because of the very limited progress that has been made in their implementation in sonar systems. This paper is intended to address issues of implementation of advanced processing schemes in sonar systems and also to serve as a brief overview to the principles and applications of advanced sonar signal processing. The main development reported in this paper deals with the definition of a generic beam-forming structure that allows the implementation of nonconventional signal-processing techniques in integrated active-passive sonar systems. These schemes are adaptive and synthetic-aperture beam formers that have been shown experimentally to provide improvements in array gain for signals embedded in partially correlated noise fields. Using target tracking and localization results as performance criteria, the impact and merits of these techniques are contrasted with those obtained using the conventional beam former     

Advanced digital receiver principles and technologies for PCS

The synergy between digital radio communications and VLSI signal processing is revolutionizing the design of wireless terminals. Driving this synergy are certain fundamental paradigms in modern communication theory, digital signal processing, and VLSI design. The authors discuss the modern centers-of-gravity model, which they believe is emerging as the basis for the successful design and implementation of advanced digital communication systems. Central to this model are design principles that enable engineers to systematically derive digital receiver structures and explore algorithm and architecture trade-offs using sophisticated tools. Digital signal processing technology is critical in the implementation of these digital receiver structures efficiently. Finally, CAD tools for digital communications system design and design space exploration are shown to be of crucial importance in the efficient execution of these designs     

信号检测、处理及实现系列课程建设探讨

信号检测、处理及实现系列课程包括电气测量技术、传感器与检测技术、自动化仪表、信号分析与处理和DSP原理及应用.我们对教学内容进行了整合.使课程之间互相衔接和前后呼应.在教学中注重新技术和新方法的介绍,使学生了解最新的科技发展.较好地处理课程中的难点,以便提高教学效果.加强实验和实践环节,培养学生的动手能力.积极编写教材和辅助教材,为学生提供丰富的学习资料.     

A Unified Conjugate Gradient Based Approach for Optimal Complex Block FIR Filtering

This paper proposes a unified block based approach to generate two complex filtering algorithms. The proposed unified approach calculates the complex conjugate gradients as the orthogonal update directions for the adaptive filter coefficients at each iteration. Along each update direction, the time-varying convergence factors tailored for the adaptive filter coefficients are updated based on the complex Taylor series expansion. The general formulation leads to two classes of adaptive algorithms: the Complex Block Conjugate Least Mean Square algorithm with Individual adaptation of parameters, CBCI-LMS, and the Complex Block Conjugate Least Mean Square algorithm, CBC-LMS. The formulation shows that the CBCI-LMS algorithm achieves faster adaptation than the CBC-LMS technique at the expense of an increase in the number of computations per iteration. The performances of these two proposed algorithms are evaluated and compared to existing techniques. In addition, the implementation aspects are examined under a wide range of adaptive conditions. These two generated algorithms are then applied to channel equalization and adaptive array beamforming. Based on the obtained results, the proposed algorithms demonstrate excellent convergence characteristics, in terms of the adaptation speed and accuracy.     

Active noise control: a tutorial review

Active noise control (ANC) is achieved by introducing a cancelling “antinoise” wave through an appropriate array of secondary sources. These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme. ANC has application to a wide variety of problems in manufacturing, industrial operations, and consumer products. The emphasis of this paper is on the practical aspects of ANC systems in terms of adaptive signal processing and digital signal processing (DSP) implementation for real-world applications. In this paper, the basic adaptive algorithm for ANC is developed and analyzed based on single-channel broad-band feedforward control. This algorithm is then modified for narrow-band feedforward and adaptive feedback control. In turn, these single-channel ANC algorithms are expanded to multiple-channel cases. Various online secondary-path modeling techniques and special adaptive algorithms, such as lattice, frequency-domain, subband, and recursive-least-squares, are also introduced. Applications of these techniques to actual problems are highlighted by several examples     

Supervised Hyperspectral Image Classification Based on Spectral Unmixing and Geometrical Features

Data hiding systems have emerged as a solution against the piracy problem, particularly those based on quantization have been widely used for its simplicity and high performance. Several data hiding applications, such as broadcasting monitoring and live performance watermarking, require a real-time multi-channel behavior. While Digital Signal Processors (DSP) have been used for implementing these schemes achieving real-time performance for audio signal processing, custom hardware architectures offer the possibility of fully exploiting the inherent parallelism of this type of algorithms for more demanding applications. This paper presents an efficient hardware implementation of a Rational Dither Modulation (RDM) algorithm-based data hiding system in the Modulated Complex Lapped Transform (MCLT) domain. In general terms, the proposed hardware architecture is conformed by an MCLT processor, an Inverse MCLT processor, a Coordinate Rotation Digital Computer (CORDIC) and an RDM-QIM processor. Results of implementing the proposed hardware architecture on a Field Programmable Gate Array (FPGA) are presented and discussed.     

The past, present, and future of image and multidimensional signalprocessing

The field of image and multidimensional signal processing began as a field of strong theoretical framework based on mathematics, statistics, and physics. Later, with advances in computing, memory, and image-sensing technology, techniques developed for image enhancement, still and moving image compression, image understanding gave this field a solid base of practical applications. Furthermore, the exploding growth of the Internet and the ubiquity of images and video, the field of image and multidimensional signal processing is becoming more and more exciting. Topics covered in the article include: multidimensional signal-processing theory, image acquisition, image transforms, image modeling, image enhancement and restoration, image and video analysis, processing, coding, hardware and software implementation issues, and computed imaging     

Direct demodulation of a 10.6µm FM signal with an NH2D stark cell

A new technique for direct demodulation of a 10.6-μm FM signal using a Stark absorption cell is described. A Stark tunable absorption line in NH2D is used to track the time-varying frequency of the incoming FM laser signal using a closed servo loop. The demodulated FM signal is proportional to the feedback voltage applied to the Stark cell. Demodulation at frequencies up to 5 kHz has been demonstrated, the rate being limited only by the bandwidth of the available servo electronics.     

Relationships between digital signal processing and control and estimation theory

The purpose of this paper is to explore several current research directions in the fields of digital signal processing and modern control and estimation theory. We examine topics such as stability theory, linear prediction, and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing, in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the two disciplines.     

Edge-connected, crossed-electrode array for two-dimensionalprojection and beamforming

A novel geometry for planar structures which allows simpler implementation and construction while trading off higher signal processing costs and possible reduced performance is introduced. A geometry for array construction which uses two sets of orthogonal striped electrodes is discussed. The basic operation principles of the geometry are given. While obtaining N² intersecting points in a two-dimensional structure, only 2N control points are required. Thus, N² active elements are controlled with 2N degrees of freedom, which simplifies both implementation and data handling. This gain in simplicity is traded off against reduced performance when used as a projector and increased signal processing when used in beamforming if the process is carried out in a two-step process. The limitations of the crossed-electrode geometry and discussed, and a theory for operation as a projector and a receiver is presented     

FBG光纤传感器的同步探测技术

光纤光栅传感解调系统的波长校准技术是人们关注的焦点,通常是将固定波长的FBG固定在恒温箱中,以此作为光纤光栅传感解调系统的参考元件．此方法占用了宽带光源的某个波长范围,从而制约了解调系统的波长扫描范围．构建的光纤光栅传感解调系统,将FP滤波器的驱动锯齿信号转变为方波信号,以此作为同步处理所需参考信号,省去了这个固定波长的FBG传感器,充分地利用了宽带光源的波长范围,并使得解调技术简单,同时提高了外接FBG传感器的数量．     

基于FPGA的OS-CFAR设计与实现

有序统计恒虚警率处理(OS-CFAR)是现代雷达信号处理的一种重要方法。本文首先简要介绍了OS-CFAR的算法模型,其次通过对数据流的分析,依据OS-CFAR算法的特点,提出一种基于FPGA的实现方案,并详细阐述了用FPGA实现OS-CFAR的两个关键技巧,最后给出了实现结果。     

基于相位敏感光时域反射计的音频激励信号解调与复现

解调复现外部振动信号在实际工程监测应用中具有广阔的应用前景。基于相位敏感光时域反射计(Φ-OTDR)的DAS可以探测分布式单模光纤的振动信号,其集传感和光纤于一体且还原原始信号时无需参考信号,适用于工程应用。本文设计演示了一种基于 Φ-OTDR的直接监测的简易且低成本的音频振动信号的解调与复现系统。在实验装置中使用聚苯乙烯板作为声音在空气中传输的增敏材料。将正弦干扰声音、人声及音乐三种激励源通过扬声器对待测光纤播放,证明本系统能在10 km的传输距离中复现频率丰富的外部振动信号,且具有4 m的空间分辨率,该系统适用于长距离监测下的外部振动的解调复现。     

Similarity methods in signal processing

A signal may contain information that is preserved by certain transformations of the signal. For example, the information phase-modulated signal is not altered by amplitude scaling of the signal. Many processing techniques have been developed to exploit such similarities. In the past, these algorithms have been developed in isolation without regard to common principles of invariance that tie them together. Similarity methods are presented as a unified method of designing processing algorithms invariant to specified transformations. These methods are based upon groups of continuous transformations known as local Lie groups and lead to a quasilinear partial differential equation. Solution of this partial differential equation specifies the form the signal processing operations must take. This form can then be applied using engineering judgment for algorithmic implementation. The paper presents an extended tutorial on Lie groups and similarity methods and quasilinear differential equations drawn from the mathematical literature. This is followed by several examples of signal processing interest that demonstrate that the similarity techniques may be applicable in certain kinds of signal processing problems     

FSK Coherent Demodulation Using Second- Harmonic Injection Locked Oscillator

We present an alternative coherent demodulation of frequency shift keying (FSK) signals based on the use of a super harmonic injection locked oscillator (ILO). Demodulation consists of multiplying the incoming FSK signal by the output of the ILO using an up-conversion mixer. The product includes a second harmonic signal that locks the oscillator, closing a non-linear feedback loop, and synchronizes its output with the incoming FSK signal. In addition to the second harmonic, the product also includes a base band signal that reproduces the original modulation. We built and tested a hybrid prototype of the demodulation system for the frequency range from 250 to 300 MHz. The circuit consists of a second-harmonic differential output ILO with varactor diodes as tuning elements and a four quadrant analog multiplier. Our results demonstrate the reliability and robustness of the demodulator system.