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检索条件"任意字段=Advanced Signal Processing Algorithms, Architectures, and Implementations XVII"

共 419 条记录，以下是281-290 订阅

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3D Object Matching on the GPU Using Spin-Image Surface Matching

3D Object Matching on the GPU Using Spin-Image Surface Match...

引用

Conference on advanced signal processing algorithms, architectures, and Implementantions xviiI

作者： Davis, Nolan Braunreiter, Dennis Tebcherani, Cezario Tanida, Masatoshi Sci Applicat Int Corp San Diego CA 92121 USA

ISBN: (纸本)9780819472946

Spin-image surface matching is a technique for locating objects in a scene by processing three-dimensional surface information from sources such as light detection and ranging (LIDAR), structured light photography, and tomography. It is attractive for parallel processing on graphics processing units (GPUs) because the two main computational steps matching pairs of spin-images by correlation, and matching pairs of points between model and scene - are explicitly parallel. By implementing these parallel computations on the GPU, as well as recasting serial portions of the algorithm into a parallel form and structuring the algorithm to limit data exchanges between host and GPU, this project achieved an overall speedup of 20 times or more compared to conventional serial processing. A demonstration application has been developed that allows users to select among a set of models and scenes and then applies the spin-image surface matching algorithm to match the selected models to the scene. It also has several user interface controls for changing parameters. One new parameter is a geometric consistency ratio (GCR) that quantifies the matching performance and provides a measure for discarding low-quality matches. By toggling between GPU- and host-based processing, the application demonstrates the speedup achieved with parallelization on the GPU.

关键词： spin image surface matching object matching image correlation geometric consistency GPU graphical processing unit parallel processing speedup

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EFFECT OF RESAMPLING ON THE MUSIC ALGORITHM WHEN APPLIED TO INVERSE SYNTHETIC APERTURE RADAR

EFFECT OF RESAMPLING ON THE MUSIC ALGORITHM WHEN APPLIED TO ...

引用

CONF ON advanced signal processing algorithms, architectures, AND implementations 2

作者： NASH, G Defence Science and Technology Organization and Univ. of South Australia (Australia)

ISBN: (纸本)0819406945

Inverse synthetic aperture radar (ISAR) is a radar imaging method by which the rotation of a target is utilized to produce a two dimensional image. To achieve high resolution in both range and cross range, a series of stepped frequency waveforms are transmitted. These sample the target's radar response in frequency and time. Frequency transforms to time, which is proportional to range, and time transforms to doppler frequency, which is proportional to cross range. Therefore a two dimensional Fourier transform can be applied to the two dimensional data set to produce a radar image. However this is an approximation as the data is in a polar format, which only approximates a rectangular grid. Therefore resampling (interpolation) is required to change the grid from a polar to a rectangular format. The resampling in this case is straightforward. In an attempt to obtain higher resolution images, the Fourier transform has been replaced by the multiple signal classification (MUSIC) algorithm. The justification for this is that the targets of interest are manmade and so have sharp edges and corners. Therefore they consist of a number of corner reflectors with a background of continuous reflectors. The corner reflectors by their nature will generally give much stronger reflections, so one can with a certain degree of accuracy, approximate the ship as a collection of corner reflectors. Over the small change in aspect angle for which ISAR imaging is performed, corner reflectors can be approximated as point scatterers. This leads to the data being modeled as a collection of complex exponentials with added white Gaussian noise. The noise being due to thermal noise in the radar system. This type of data set is ideal for the two dimensional MUSIC algorithm. There are two major difficulties in applying the MUSIC algorithm to ISAR imaging. First, the MUSIC estimator is more sensitive to the sampling grid being polar than the Fourier transform is. Second, the resampling is less effect

关键词： Fourier transforms Radar Reflectors Computer simulations Interference (communication) Data modeling Detection and tracking algorithms Image resolution signal processing Transform theory

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On-line arithmetic for recurrence problems

On-line arithmetic for recurrence problems

引用

advanced signal processing algorithms, architectures, and implementations II

作者： Ercegovac, Milos D. Univ. of California/Los Angeles Los Angeles CA USA

An arithmetic-level approach to increasing computation rate in solving recurrence problems is discussed. The approach, based on on-line arithmetic principles, is discussed in problems such as root finding and recursiv... 详细信息

ISBN: (纸本)0819406945

关键词： signal processing

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New algorithms for on-line computation of elementary functions

New algorithms for on-line computation of elementary functio...

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advanced signal processing algorithms, architectures, and implementations II

作者： Kla, Sylvanus Mazenc, Christophe Merrheim, Xavier Muller, Jean-Michel M. Ecole Normale Superieure de Lyon Lyon Cedex 07 France

ISBN: (纸本)0819406945

We present here some algorithms for on-line computation of elementary functions. These algorithms use shift-and-add as elementary step and need signed digit representations of numbers. Then, we give some theoretical results about on-line computation of functions. For instance, we show that a finite automaton (in practice a bounded size and memory operator) can compute in on-line only piecewise affine functions.

关键词： signal processing

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Architecture of a complex arithmetic processor for communication signal processing

Architecture of a complex arithmetic processor for communica...

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advanced signal processing: algorithms, architectures, and implementations V

作者： Gilfeather, Susan L. Gehman Jr., John B. Harrison, Calvin Motorola Government and Systems Technology Group Scottsdale AZ USA

ISBN: (纸本)0819416207

The Complex Arithmetic Processor (CAP) is a high performance, single chip Digital signal Processor optimized for communication signal processing operations. The CAP VLSI provides the communication system building block necessary to meet the increased signal processing requirements of complex modulation types, voice and image compression while maintaining the requirement for small, low power implementations. The chip is intended for high speed, low power digital communication system applications such as hand held spread spectrum communications systems. The CAP architecture has been developed specifically for the complex arithmetic functions required in communication signal processing. The CAP is a software programmable, highly integrated parallel array of processors containing the arithmetic resources, memories, address generation, bit manipulation and logic functions necessary to support the sophisticated processing required in advanced communication equipment. The CAP executes a 1024 point complex Fast Fourier Transform in 131 microseconds.

关键词： Digital integrated circuits

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Resolution advantages of quadratic signal processing

Resolution advantages of quadratic signal processing

引用

advanced signal processing algorithms, architectures, and implementations II

作者： Atlas, Les E. Fang, Jing Loughlin, Patrick Music, Wayne Univ. of Washington Seattle WA USA

ISBN: (纸本)0819406945

In this paper, we show how quadratic time-frequency representations are a generalization of the spectrogram and we review our results for time-frequency analysis and display of chirps and speech. We then show comparative performance on phase-shifted keyed communication signals. The concept of quadratic filtering is then introduced and linked to Teager's energy detector and the resolution advantages over linear filtering are demonstrated.

关键词： signal processing

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Filtering chaotic time series

Filtering chaotic time series

引用

advanced signal processing: algorithms, architectures, and implementations V

作者： Davies, Michael E. Univ. Coll. London London UK

We consider the relationship between modelling dynamics with a nonlinear function approximation and the application of a noise reduction algorithm. Filtering the data with such an algorithm is then shown to provide a ... 详细信息

ISBN: (纸本)0819416207

关键词： signal filtering and prediction

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Acoustic sensor networks for woodpecker localization

Acoustic sensor networks for woodpecker localization

引用

advanced signal processing algorithms, architectures, and implementations XV

作者： Wang, H. Chen, C.E. Ali, A. Asgari, S. Hudson, R.E. Yao, K. Estrin, D. Taylor, C. UCLA Computer Science Department UCLA Electrical Engineering Department UCLA Ecology and Evolutionary Biology Department

Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations.1,2 Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method3 to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.

关键词： signal processing

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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...

引用

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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