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Time-frequency analysis using peak-value sampling of spatial-temporal image data from streak camera

Time-frequency analysis using peak-value sampling of spatial...

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conference on advanced signal processing algorithms, architectures, and implementations XIV

作者： Sun, KX Marlett, K Bechtel Nevada Livermore Operat Livermore CA 94551 USA

ISBN: (纸本)0819454974

A streak camera is a recording instrument in which spatial image is swept in time. creating a spatial-temporal image on a charge-coupled device (CCD). Traditional analysis for captured image data has been using uniform and as sampling points, in which a block of CCD pixel readouts are summed to give one reading. Equivalently simple area moving averages are applied concurrently while sampling, and high frequency content is reduced. To solve this problem. we use peak-value sampling procedure, based on the view from photoelectron statistics. After background correction. maximum values in spatial dimensions are selected to obtain time series data. A DSP filter is then applied and optimized for this time series. A Welch algorithm fast Fourier transform is applied to obtain power spectra. Segmented cumulative spectra is then calculated for global statistics and related to time domain fluctuations. Self similarity at different sweeping time-scales is used to recognize CCD pattern noise. Sinusoidal pattern noise is automatically corrected by peak-value sampling. Computational results show that time-frequency analysis using peak-value sampling algorithm and similar variants is far more effective in discovering high frequency oscillatory noise than traditional uniform binned sampling. We have applied this algorithm to analyze data produced by a 4096x4096 CCD streak camera illuminated with a macro pulse laser. High frequency oscillations in 6similar to10 GHz region were found in laser spectra. Spatial-temporal oscillations of this range are difficult to diagnose with conventional optoelectronic detectors on a per-shot basis. This work has led to improvement of laser design.

关键词： streak camera laser maximum value sampling image processing high frequency spectral analysis

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Estimating the frequency interval of a regularly spaced multi-component harmonic line signal in coloured noise

Estimating the frequency interval of a regularly spaced mult...

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conference on advanced signal processing - algorithms, architectures, and implementations viI

作者： Frazer, GJ Anderson, SJ Defence Science and Technology Organisation (Australia)

ISBN: (纸本)0819425842

The radar returns from some classes of time-varying point targets can be represented by the discrete-time signal plus noise model: x(t) = s(t) + [nu(t) + eta(t)] = (P-1)Sigma(i=0) A(i)e(j2 pi fi/fst) + nu(t) + eta(t), t is an element of 0,...,.N - 1, f(i) = kf(I) + f(o) where the received signal x(t) corresponds to the radar return from the target of interest from one azimuth-range cell. The signal has an unknown number of components, P, unknown complex amplitudes A(i) and frequencies f(i). The frequency parameters f(o) and f(I) are unknown, although constrained such that f(o) < fI/2 and parameter k is an element of {-u,...,-2,-1,0,1,2,...,upsilon) is constrained such that the component frequencies f(i) are bound by [-fs/2,fs/2). The noise term nu(t), is typically coloured, and represents clutter, interference and various noise sources. It is unknown, except that Sigma(t)\nu(t)\(2) < infinity;in general, nu(t) is not well modelled as an auto-regressive process of known order. The additional noise term eta(t) represents time-invariant point targets in the same azimuth-range cell. An important characteristic of the target is the unknown parameter, f(I), representing the frequency interval between harmonic lines. It is desired to determine an estimate of f(I) from N samples of x(t). We propose an algorithm to estimate f(I) based on Thomson's harmonic line F-Test, which is part of the multi-window spectrum estimation method and demonstrate the proposed estimator applied to target echo time series collected using an experimental HF skywave radar.

关键词： HF radar multiple-window methods harmonic line detection frequency interval estimation

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Separating Cognitive Processes with Principal Components Analysis of EEG Time-Frequency Distributions

Separating Cognitive Processes with Principal Components Ana...

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conference on advanced signal processing algorithms, architectures, and Implementantions XviII

作者： Bernat, Edward M. Nelson, Lindsay D. Holroyd, Clay B. Gehring, William J. Patrick, Christopher J. Univ Minnesota Dept Psychol Minneapolis MN 55455 USA Univ Victoria Dept Psychol Victoria BC Canada Univ Michigan Dept Psychol Ann Arbor MI 48109 USA

ISBN: (纸本)9780819472946

Measurement of EEG event-related potential (ERP) data has been most commonly undertaken in the time-domain, which can be complicated to interpret when separable activity overlaps in time. When the overlapping activity has distinct frequency characteristics, however, time-frequency (TF) signal processing techniques can be useful. The current report utilized ERP data from a cognitive task producing typical feedback-related negativity (FRN) and P300 ERP components which overlap in time. TF transforms were computed using the binomial reduced interference distribution (RID), and the resulting TF activity was then characterized using principal components analysis (PCA). Consistent with previous work, results indicate that the FRN was more related to theta activity (3-7 Hz) and P300 more to delta activity (below 3 Hz). At the same time, both time-domain measures were shown to be mixtures of TF theta and delta activity, highlighting the difficulties with overlapping activity. The TF theta and delta measures, on the other hand, were largely independent from each other, but also independently indexed the feedback stimulus parameters investigated. Results support the view that TF decomposition can greatly improve separation of overlapping EEG/ERP activity relevant to cognitive models of performance monitoring.

关键词： Time-frequency analysis Principal component analysis Electroencephalography signal processing Brain Electrodes Psychology signal attenuation Time metrology Transform theory

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Tuning Time-Frequency methods for the detection of metered HF speech

Tuning Time-Frequency methods for the detection of metered H...

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conference on advanced signal processing algorithms, architectures and implementations XII

作者： Nelson, DJ Smith, LH US Dept Def Ft George G Meade MD 20755 USA

ISBN: (纸本)0819445584

Speech is metered if the stresses occur at a nearly regular rate. Metered speech is common in poetry, and it can occur naturally in speech, if the speaker is spelling a word or reciting words or numbers from a list. In radio communications, the CQ request, call sign and other codes are frequently metered. In tactical communications and air traffic control, location, heading and identification codes may be metered. Moreover metering may be expected to survive even in HF communications, which are corrupted by noise, interference and mistuning. For this environment, speech recognition and conventional machine-based methods are not effective. We describe Time-Frequency methods which have been adapted successfully to the problem of mitigation of HF signal conditions and detection of metered speech. These methods are based on modeled time and frequency correlation properties of nearly harmonic functions. We derive these properties and demonstrate a performance gain over conventional correlation and spectral methods. Finally, in addressing the problem of HF single sideband (SSB) communications, the problems of carrier mistuning, interfering signals, such as manual Morse, and fast automatic gain control (AGC) must be addressed. We demonstrate simple methods which may be used to blindly mitigate mistuning and narrowband interference, and effectively invert the fast automatic gain function.

关键词： signal to noise ratio signal processing signal detection Optical filters Time-frequency analysis Interference (communication) Automatic control Electronic filtering Receivers RF communications

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NEW MATHEMATICAL TOOLS IN DIRECTION FINDING AND SPECTRAL ANALYSIS.

NEW MATHEMATICAL TOOLS IN DIRECTION FINDING AND SPECTRAL ANA...

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Real Time signal processing vi.

作者： Schmidt, Ralph O. ESL Inc Sunnyvale CA USA ESL Inc Sunnyvale CA USA

ISBN: (纸本)0892524669

Linear Algebra (i. e. , the algebra of vector spaces) provides widely used mathematical tools and concepts which are today considered for implementation in special computer architectures. It seems that so many signal processing problems can be expressed and, more importantly, implemented efficiently as a sequence of vector and matrix operations, that a signal processing system with a capability for high speed linear algebra is necessary if the more advanced signal processing algorithms are to be implemented to operate in real time. This paper supports the notion that linear algebra is a sound basis for important signal processing system implementations and suggests that multilinear algebra (i. e. , the algebra of vector, bivector, trivector, etc. spaces) offers an even broader set of signal processing tools. Examples and ideas from direction finding and time series analysis are discussed.

关键词： signal processing

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Active perception in a sensor fusion model

Active perception in a sensor fusion model

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conference on Sensor Fusion - architectures, algorithms, and Applications vi

作者： Biel, L Wide, P Univ Orebro Ctr Appl Autonomous Sensor Syst Orebro Sweden

ISBN: (纸本)0819444812

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

关键词： Sensors Sensor fusion Data fusion Fuzzy systems Carbon monoxide Oxygen Systems modeling Environmental sensing Control systems signal processing

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GPU Implementation of Fully Constrained Linear Spectral Unmixing for Remotely Sensed Hyperspectral Data Exploitation

GPU Implementation of Fully Constrained Linear Spectral Unmi...

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conference on Satellite Data Compression, Communications, and processing vi

作者： Sanchez, Sergio Martin, Gabriel Plaza, Antonio Chang, Chein-, I Univ Extremadura Dept Technol Comp & Commun Hyperspectral Comp Lab Avda Univ S-N Caceres 10071 Spain Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Remote Sensing Signal & Image Proc Lab Baltimore MD 1000 USA

ISBN: (纸本)9780819483065

Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. The spectral signatures collected in natural environments are invariably a mixture of the pure signatures of the various materials found within the spatial extent of the ground instantaneous field view of the imaging instrument. Spectral unmixing aims at inferring such pure spectral signatures, called endmembers, and the material fractions, called fractional abundances, at each pixel of the scene. A standard technique for spectral mixture analysis is linear spectral unmixing, which assumes that the collected spectra at the spectrometer can be expressed in the form of a linear combination of endmembers weighted by their corresponding abundances, expected to obey two constraints, i.e. all abundances should be non-negative, and the sum of abundances for a given pixel should be unity. Several techniques have been developed in the literature for unconstrained, partially constrained and fully constrained linear spectral unmixing, which can be computationally expensive (in particular, for complex high-dimensional scenes with a high number of endmembers). In this paper, we develop new parallel implementations of unconstrained, partially constrained and fully constrained linear spectral unmixing algorithms. The implementations have been developed in programmable graphics processing units (GPUs), an exciting development in the field of commodity computing that fits very well the requirements of on-board data processing scenarios, in which low-weight and low-power integrated components are mandatory to reduce mission payload. Our experiments, conducted with a hyperspectral scene collected over the World Trade Center area in New York City, indicate that the proposed implementations provide relevant speedups over the corresponding serial versions in latest-generation Tesla C1060 GPU architectures.

关键词： Hyperspectral imaging spectral unmixing parallel computing graphics processing units (GPUs)

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Adaptive array beamforming with fixed-point arithmetic matrix inversion using Givens rotations

Adaptive array beamforming with fixed-point arithmetic matri...

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conference on advanced signal processing algorithms, architectures, and implementations XI

作者： Rabinkin, DV Song, W Vai, MM Nguyen, H MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819441880

Adaptive array systems require the periodic solution of the well-known w = (R) over tilde (-1)v equation in order to compute optimum adaptive array weights. The covariance matrix (R) over tilde is estimated by forming a product of noise sample matrices X : (R) over tilde = (XX)-X-H. The operations-count cost of performing the required matrix inversion in real time can be prohibitively high for a high bandwidth system with a large number of sensors. Specialized hardware may be required to execute the requisite computations in real time. The choice of algorithm to perform these computations must be considered in conjunction with the hardware technology used to implement the computation engine. A systolic architecture implementation of the Givens rotation method for matrix inversion was selected to perform adaptive weight computation. The bit-level systolic approach enables a simple ASIC design and a very low power implementation. The bit-level systolic architecture must be implemented with fixed-point arithmetic to simplify the propagation of data through the computation cells. The Givens rotation approach has a highly parallel implementation and is ideally suited for a systolic implementation. Additionally, the adaptive weights are computed directly from the sample matrix X in the voltage domain, thus reducing the required dynamic range needed in carrying out the computations. An analysis was performed to determine the required fixed-point precision needed to compute the weights for an adaptive array system operating in the presence of interference. Based on the analysis results. it was determined that the precision of a floating-point computation can be well approximated with a 13-bit to 19-bit word length fixed point computation for typical system jammer-to-noise levels. This property has produced an order-of-magnitude reduction in required hardware complexity. A synthesis-based ASIC design process was used to generate preliminary layouts. These layouts were used t

关键词： Very large scale integration Chemical elements Computing systems Sensors Statistical analysis Computer architecture Matrices Radar Electroluminescence signal processing

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Superresolution imaging: a survey of current techniques

Superresolution imaging: a survey of current techniques

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conference on advanced signal processing algorithms, architectures, and Implementantions XviII

作者： Cristobal, G. Gil, E. Sroubek, F. Flusser, J. Miravet, C. Rodriguez, F. B. CSIC Inst Opt Serrano 121 E-28006 Madrid Spain ASCR Inst Informat Theory & Automat Prague Czech Republic Univ Autonoma Madrid Escuela Politecn Super Madrid Spain

ISBN: (纸本)9780819472946

Imaging plays a key role in many diverse areas of application, such as astronomy, remote sensing, microscopy, and tomography. Owing to imperfections of measuring devices (e.g., optical degradations, limited size of sensors) and instability of the observed scene (e.g., object motion, media turbulence), acquired images can be indistinct, noisy, and may, exhibit insufficient spatial and temporal resolution. In particular, several external effects blur images. Techniques for recovering the original image include blind deconvolution (to remove blur) and superresolution (SR). The stability of these methods depends on having more than one image of the same frame. Differences between images are necessary to provide new information, but they can be almost unperceivable. State-of-the-art SR techniques achieve remarkable results in resolution enhancement by estimating the subpixel shifts between images, but they lack any apparatus for calculating the blurs. In this paper, after introducing a review of current SR, techniques we describe two recently developed SR methods by the authors. First, we introduce a variational method that minimizes a regularized energy function with respect to the high resolution image and blurs. In this way we establish a unifying way to simultaneously estimate the blurs and the high resolution image. By estimating blurs we automatically estimate shifts with subpixel accuracy, which is inherent for good SR performance. Second, an innovative learning-based algorithm using a neural architecture for SR is described. Comparative experiments on real data illustrate the robustness and utilization of both methods.

关键词： superresolution deconvolution energy minimization probabilistic neural network sequence processing

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Hardware/software trade-offs for advanced 3G channel coding

Hardware/software trade-offs for advanced 3G channel coding

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Design, Automation and Test in Europe conference and Exhibition

作者： H. Michel A. Worm M. Munch N. Wehn Institute of Microelectronic System Design University of Kaiserslautern Kaiserslautern Germany ASIC Design Laboratories Zaventem Belgium

ISBN: (纸本)0769514715

Third generation's wireless communications systems comprise advanced signal processing algorithms that increase the computational requirements more than ten-fold over 2G's systems. Numerous existing and emerging standards require flexible implementations ("software radio"). Thus efficient implementations of the performance-critical parts as Turbo decoding on programmable architectures are of great interest. Besides high-performance DSPs, application-customized RISC cores offer the required performance while still maintaining the aspired flexibility. This paper presents for the first time Turbo decoder implementations on customized RISC cores and compares the results with implementations on state-of-the-art VLIW DSPs. The results of our studies show that the Log-MAP performance is about 50% higher that on an ST120, a current VLIW architecture.

关键词： Hardware Channel coding Decoding Digital signal processing Reduced instruction set computing VLIW signal generators Wireless communication signal processing algorithms Software standards

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