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Bandlimits and coherent modulation filtering of non-stationary signals

Bandlimits and coherent modulation filtering of non-stationa...

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

作者： Clark, Pascal Atlas, Les Univ Washington Dept Elect Engn Seattle WA 98195 USA

ISBN: (纸本)9780819472946

Modulation filtering is a technique for filtering slowly-varying envelopes of frequency subbands of a non-stationary signal, ideally without affecting the signal's phase and fine-structure. Coherent modulation filtering is a potentially more effective subtype of such techniques where subband envelopes are determined through demodulation of the subband signal with a coherently detected subband carrier. In this paper we propose a coherent modulation filtering technique based on detecting the instantaneous frequency of a subband from its time-frequency representation. We show that coherent modulation filtering imposes a new bandlimiting constraint on the modulation product plus the ability to recover arbitrarily chosen envelopes and carriers from their modulation product. We show that a carrier estimate based on the time-varying spectral center-of-gravity satisfies the bandlimiting condition as well as Loughlin's previously derived bandlimiting constraint on the instantaneous frequency of carrier. These bandwidth constraints lead to effective and distortion-free modulation filters, offering new approaches for potential signal modification. The spectral center-of-gravity does not satisfy the condition on arbitrary recovery, however, which somewhat limits the flexibility of coherent modulation filtering. Demonstrations are provided with speech signals.

关键词： modulation time-frequency analysis time-varying filters bandwidth speech processing

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Optimizing time-frequency distributions for automatic classification

Optimizing time-frequency distributions for automatic classi...

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

作者： Atlas, L Droppo, J McLaughlin, J Univ. of Washington (United States) MIT Lincoln Lab. (United States)

ISBN: (纸本)0819425842

An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable more accurate classification. We refer to these kernels, which are optimized to discriminate among several classes of signals, as signal class dependent kernels, or simply class dependent kernels. The genesis of the class dependent kernel is to be found in the area of operator theory, which we use to establish a direct link between a discrete-time, discrete-frequency TFR and its corresponding discrete signal. We see that many similarities, but also some important differences, exist between the results of the continuous-time operator approach and our discrete one. The differences between the continuous representations and discrete ones may not be the simple sampling relationship which has often been assumed. From this work, we obtain a very concise, matrix-based expression for a discrete-time/discrete-frequency TFR which is simply the product of the kernel with another matrix. This simple expression opens up the possibility to optimize the kernel in a number of ways. We focus, of course, on optimizations most suitable for classification, and ultimately wind up with the class dependent kernel. When applied to simulated sonar transient signals, we find that our approach does a good job of discriminating within very similar classes of transients and is especially sensitive to differences in time variation across classes.

关键词： Time-frequency analysis Matrices Fourier transforms Convolution Detection theory Distance measurement signal generators signal processing Silicon Stochastic processes

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New one-hot RNS structures for high-speed signal processing

New one-hot RNS structures for high-speed signal processing

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conference on advanced signal processing algorithms, architectures and implementations xiI

作者： Conway, R Conway, T Nelson, J Univ Limerick ECE Dept Limerick Ireland

ISBN: (纸本)0819445584

New efficient structures using the one-hot residue number system (OHRNS) are presented. Normally the RNS uses a binary representation for the residues, though recently there has been renewed interest in the OHRNS, which uses a simple, but novel representation for the residues. The basic component of the OHRNS is the barrel shifter, making the OHRNS suitable for very high speed applications. The first of the new structures presented reduces the power dissipation in OHRNS adder trees. A modification to the normal barrel shifter is proposed, which reduces the power dissipated by as much as 30%. This improvement is obtained through the use of the modified barrel shifter and the appropriate connection of active-low and active-high stages. This overall power reduction offers the possibility of using the OHRNS in place of a typical full adder based tree in high speed DSP applications. A new storage register for one-hot representations is detailed, which overcomes the problem of having to use a large number of registers. A new architecture is presented for fast OHRNS sign detection. Sign detection is complex and slow to perform in the RNS. A mixed radix conversion (MRC) is typically used for sign detection in the OHRNS. The new sign detection architecture is based on a new property of the Chinese Remainder Theorem (CRT) and is significantly faster than the MRC approach for large moduli sets. Simulation results using SPICE are detailed for the new structures.

关键词： RNS one-hot sign detection

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

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

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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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Innovative implementation and simulation of signal processing algorithms for the ASTP & DITP programs.

Innovative implementation and simulation of signal processin...

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conference on signal and Data processing of Small Targets

作者： DeChaine, MD Kinashi, Y Nichols Res Corp Arlington VA 22202 USA

ISBN: (纸本)0819428221

An innovative approach is being used to implement and simulate the infrared (IR) and laser radar signal processing algorithms for the advanced Sensor Technology Program (ASTP) and the Discrimination Interceptor Technology Program (DITP). Although the algorithms will run on four different computer architectures, they will use the same source code for all implementations. The initial development and testing will occur in Mathcad on a Windows 95/NT personal computer, then move to simulation on a Silicon Graphics (SGI) workstation, then to scaled real-time simulation on a parallel high performance computer (HPC), and finally to the actual flight processor, the miniaturized parallel Wafer Scale signal Processor (WSSP) with a MIMD (multiple-instruction and multiple data) architecture. This flexibility is accomplished with code wrappers that implement interchangeable interface layers for the code modules, one wrapper for Mathcad matrices, one for C++ objects on the workstation, one for message passing with static routing on the HPC, and one for dynamically routed message passing on the WSSP. With this approach, developers can move modules back and forth from the workstation simulation environment to the implementation hardware. This will eliminate the need to maintain different versions of the same algorithm. The signal processing algorithms will be modified to work in a massively parallel architecture, with a message passing interface, which is simulated on the Silicon Graphics workstation, emulated on the HPC, and implemented on the WSSP. This approach will allow for pipeline processing as well as multiple, concurrently running instances of modules. In addition, innovative algorithms will fuse active laser radar detections and passive multicolor IR sensor measurements to improve target state estimation.

关键词： signal processing algorithms parallel processing simulation infrared sensors laser radar ballistic missile defense

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Energy-Efficient Synthetic-Aperture Radar processing on a Manycore Architecture

Energy-Efficient Synthetic-Aperture Radar Processing on a Ma...

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42nd Annual International conference on Parallel processing (ICPP)

作者： Zain-ul-Abdin Ahlander, Anders Svensson, Bertil Halmstad Univ Ctr Res Embedded Syst CERES Halmstad Sweden Saab AB Gothenburg Sweden

ISBN: (纸本)9780769551173

The next generation radar systems have high performance demands on the signal processing chain. Examples include the advanced image creating sensor systems in which complex calculations are to be performed on huge sets of data in real time. Manycore architectures are gaining attention as a means to overcome the computational requirements of the complex radar signal processing by exploiting massive parallelism inherent in the algorithms in an energy efficient manner. In this paper, we evaluate a manycore architecture, namely a 16-core Epiphany processor, by implementing two significantly large case studies, viz. an autofocus criterion calculation and the fast factorized back-projection algorithm, both key components in modern synthetic aperture radar systems. The implementation results from the two case studies are compared on the basis of achieved performance and programmability. One of the Epiphany implementations demonstrates the usefulness of the architecture for the streaming based algorithm (the autofocus criterion calculation) by achieving a speedup of 8.9x over a sequential implementation on a state-of-the-art general-purpose processor of a later silicon technology generation and operating at a 2.7x higher clock speed. On the other case study, a highly memory-intensive algorithm (fast factorized backprojection), the Epiphany architecture shows a speedup of 4.25x. For embedded signal processing, low power dissipation is equally important as computational performance. In our case studies, the Epiphany implementations of the two algorithms are, respectively, 78x and 38x more energy efficient.

关键词： Manycore architecture Parallel programming Radar signal processing

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Proceedings of the 35th Asilomar conference on signals, Systems & Computers

Proceedings of the 35th Asilomar Conference on Signals, Syst...

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35th Asilomar conference on signals, Systems and Computers

This Volume 2 of 2 of the conference proceedings contains 160 papers. Topics discussed include wireless communication and signal processing, algorithms for MIMO links, modulation and detection techniques, signal detection and classification, adaptive communications and arrays, image segmentation and frequency domain processing, multiple user/multiple access techniques, digital signal processing architectures, hyperspectral processing and multisignals or data fusion, computer arithmetic implementations and FPGA designs, radar and sonar processing, equalization and synchronization techniques, higher order statistical signal processing for communications, adaptive signal processing in communication, speech coding and processing, wireless systems, special arithmetic techniques, biomedical imaging and advanced modulation and channel estimation.

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...

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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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