This work deals with evaluation of hardware implementations of image processingalgorithms for real time applications, using SRAM based Field Programmable Gate Arrays. We discuss a generic architectural model adapted ...
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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, analy...
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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.
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 unifor...
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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.
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),...
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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.
The proceedings include 28 papers, 27 of them are indexed separately. Topics covered include advanced techniques of real-time signalprocessing in various fields, such as space information systems, radar data processi...
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The proceedings include 28 papers, 27 of them are indexed separately. Topics covered include advanced techniques of real-time signalprocessing in various fields, such as space information systems, radar data processing, missile guidance underwater acoustic imaging, wideband integrated optics. Also hardware architectures and algorithms for real-time signalprocessing are considered. Several presentations are devoted to digital approaches and analog implementations of real-time signalprocessing.
A number of adaptive condition number estimators have been proposed in the past to dynamically estimate the sensitivity of the coefficient matrix of a linear systems of equations. Applications of these techniques ofte...
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ISBN:
(纸本)0819416207
A number of adaptive condition number estimators have been proposed in the past to dynamically estimate the sensitivity of the coefficient matrix of a linear systems of equations. Applications of these techniques often arise in the context of signalprocessing, where the information matrix is being updated with rank-one modifications. Various schemes, such as ACE, ALE and ICE, were proposed to cope with this problem. In this paper, we will briefly review the past work, and show how the small-sample condition estimator can be used in an adaptive manner.
Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through ...
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Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through the application of signalprocessing principles in the design, deployment and operation of sensor networks. After a discussion of general issues arising in this context, this talk will describe several recent developments in this area. These include the effects of receiver choice on energy efficiency, collaborative beam-forming, sensor scheduling, and distributed learning. Some of the work described in this talk can be found in Refs. 1-8.
This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time...
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ISBN:
(纸本)0819416207
This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time of non-contact type inspection problems including industrial and medical applications. A single processor can not deliver sufficient processing power required for the use of applications hence, a MIMD system is designed and constructed to enable fast processing of electro-optic images. The Texas Instruments TMS320C40 digital signal processor is used due to its high speed floating point CPU and the support for the parallel processing environment. A custom designed VISION bus is provided to transfer images between processors. The system is being applied for solder joint inspection of high technology printed circuit boards.
It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high band...
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It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high bandwidth sensors. Reconfigurable computing, based on field programmable gate arrays, offers ten to one hundred times the performance of traditional microprocessors for certain algorithms. This paper discusses the architecture of the computer and the source of performance gains, as well as an example application. The calculation of multiple matched filters applied to multispectral imagery, showing a performance advantage of forty-five over Pentium II (450 MHz), is presented as an exemplar of algorithms appropriate for this technology.
A two-sided (or complete) orthogonal decomposition of an m × n matrix A is a product of an orthogonal matrix, a triangular matrix, and another orthogonal matrix. Two examples are the URV and ULV decompositions. I...
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ISBN:
(纸本)0819416207
A two-sided (or complete) orthogonal decomposition of an m × n matrix A is a product of an orthogonal matrix, a triangular matrix, and another orthogonal matrix. Two examples are the URV and ULV decompositions. In this paper we present and analyze URV and ULV algorithms that are efficient whenever the numerical rank k of the matrix is much less than min(m,n). We also prove that good estimates of the singular vectors, needed in the algorithms, lead to good approximations of the singular subspaces of A.
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