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NRL FLEX radar signal-processing architecture: an update

NRL FLEX radar signal-processing architecture: an update

引用

advanced signal processing algorithms, architectures, and implementations III

作者： Alter, James J. Evins, James B. Popick, Glen L. Scott, Russell A. Letellier, J.P. Naval Research Lab. Washington DC USA

ISBN: (纸本)081940943X

The NRL FLEX processor architecture is designed for real-time radar signal processing and was described at last year's conference in the context of its original application, the Point Defense Demonstration Radar project at NRL. This paper describes the current status of the processor and the application of the same architecture to a new problem which requires a different board configuration to satisfy a different set of latency and data flow requirements.

关键词： Radar systems

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An algorithm for weighted least squares positive time-frequency distributions

An algorithm for weighted least squares positive time-freque...

引用

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

作者： Pitton, JW MathSoft Seattle WA 98109 1700 Westlake Ave N United States

ISBN: (纸本)0819425842

An algorithm for computing positive time-frequency distributions (TFDs) for nonstationary signals is presented. This work extends the earlier work of the author and his colleagues in computing positive TFDs [11, 15]. A general approach to the problem of computing these signal-dependent distributions is derived. The method is based on an evolutionary spectrum formulation of positive TFDs. Following earlier work [15], a relationship is derived between positive TFDs and the ambiguity function of the observed signal. In particular, it is shown that the TFD is approximately equal to the two-dimensional Fourier transform of the ambiguity function. A method for computing the positive TFD is then presented based on minimizing the squared error in this approximation subject to the TFD being positive and satisfying the time and frequency marginals. The squared error may be weighted non-uniformly, resulting in a constrained weighted least-squares optimization problem. A solution to this optimization problem based on an alternating projections framework is presented, and an example is provided. The resulting TFD provides excellent time-frequency resolution while maintaining positivity and satisfying the marginals.

关键词： signal processing time-frequency analysis time-varying signals optimization alternating projections

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Time-frequency analysis for the study of phase synchrony in the brain

Time-frequency analysis for the study of phase synchrony in ...

引用

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

作者： Aviyente, Selin Evans, Westley Michigan State Univ E Lansing MI 48824 USA

ISBN: (纸本)9780819472946

The quantification of synchrony is important for the study of large-scale interactions in the brain. Current synchrony measures depend on the energy of the signals rather than the phase, and cannot be reliably used as measures of neural synchrony. Moreover, the current methods are insufficient since they are limited to pairs of signals. These approaches cannot quantify the synchrony across a group of electrodes and over time-varying frequency regions. In this paper, we propose two new measures for quantifying the synchrony between both pairs and groups of electrodes using time-frequency analysis. The proposed measures are applied to electroencephalogram (EEG) data to quantify neural synchrony.

关键词： Phase measurement Time-frequency analysis Brain Electrodes Electroencephalography Mode locking Wavelets Iterated function systems signal analyzers Wavelet transforms

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Wavelet windowed time-frequency distribution decompositions

Wavelet windowed time-frequency distribution decompositions

引用

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

作者： Williams, WJ Sang, TH ONeill, JC Zalubas, EJ Univ. of Michigan (United States)

ISBN: (纸本)0819425842

This paper outlines means of combining and reconciling concepts associated with Cohen's class of distributions and with the wavelet transform. Both have their assets and their liabilities. Previous work has shown that one can decompose any time-frequency distribution (TFD) in Cohen's class into a weighted sum of spectrogram. A set of orthogonal analysis windows which also have the scaling property in common with wavelets is proposed. Successful application of this theory offers very fast computation of TFDs, since very few analysis windows may be needed and fast algorithms can be used. In addition, the decomposition idea offers the possibility of shaping the analysis such that good local and global properties as well as a number of desirable TFD properties are retained. Finally, one may view the result in terms of conventional Cohen's class concepts or, alternatively, in terms of wavelet concepts and potentially combine powerful insights and concepts from both points of view. Preliminary results applied to radar backscatter are provided. Performance curves for several wavelet types are also provided.

关键词： time-frequency wavelets signal decomposition radar fast algorithms

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Very low-noise (switching free) CNN-based adder

Very low-noise (switching free) CNN-based adder

引用

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

作者： Sadeghi-Emamchaie, S Jullien, GA Miller, WC Univ Windsor VLSI Res Grp Windsor ON N9B 3P4 Canada

ISBN: (纸本)0819432938

This paper presents novel methods of designing analog Cellular Nonlinear (Neural) Networks (CNNs) to implement very low-noise binary addition. In these techniques the continuous characteristic of the current that charges (discharges) the load capacitor leads to a virtually switching free addition process that significantly reduces the switching noise. This switching mechanism also leads to higher slew of output voltage during the transitions which in turn reduces the cross talk. Simulation results demonstrate a three orders of magnitude reduction in the noise generated by this structure compared to that generated by a digital adder running at the same speed. This very good noise performance of these new adder structures makes them suitable choices for low to moderate speed high precision mixed signal applications.

关键词： Cellular Nonlinear Networks switching noise mixed-signal IC analog design low-noise digital adder

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Fast blind signal separation for multi-user interference rejection in smart antenna arrays

Fast blind signal separation for multi-user interference rej...

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

作者： Sarajedini, A Chau, PM Univ. of California/San Diego (United States)

ISBN: (纸本)0819425842

Spread spectrum modulation techniques such as frequency-hopped code division multiple access (FH-CDMA) are an efficient way to allow multi-user transmission over a limited bandwidth. Recently, there has been a push to increase user capacity over the same bandwidth. In particular, smart antenna arrays have been studied for their capacity gain potential. In this regard, we propose the use of blind signal separation for recovery of signals received through an antenna array. To implement this technique requires the antenna array vectors to be stationary which does not hold in FH-CDMA, so we also propose a new method for frequency compensation. We present the theoretical details of the frequency compensation and compare its performance to no frequency compensation. We then present the blind signal separation algorithm applied to a complex antenna array matrix and complex signals with noise and show in simulation that the blind signal separation works.

关键词： blind signal separation frequency compensation frequency-hopped CDMA spread spectrum

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Computing the signal subspaces of a sparse and/or structured matrix

Computing the signal subspaces of a sparse and/or structured...

引用

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

作者： Fierro, RD California State Univ./San Marcos (United States)

ISBN: (纸本)0819425842

Many techniques involve the computation of singular subspaces associated with an extreme cluster of singular values of an m x n data matrix A. Frequently A is sparse and/or structured, which usually means matrix-vector multiplications involving A and its transpose can be done with much less than O(mn) flops, and A and its transpose can be stored in static data structures with much less than O(mn) storage locations. Standard complete orthogonal decompositions may be unattractive due to the computational and dynamic storage overhead associated with the initial preprocessing of the data. We describe an efficient Matlab implementation of the low-rank ULV algorithm for extracting reliable and accurate approximations to the singular subspaces associated with the cluster of large singular values without altering the matrix. The user can choose any principal singular vector estimator to underwrite the algorithm, may call a specialized routine to compute matrix-vector products involving A and its transpose, and can choose the desired level of accuracy of a residual. The main computational savings stems from preserving A and avoiding the explicit formation of unwanted information.

关键词： singular value decomposition singular subspaces signal subspaces ULV decomposition fast algorithms Householder transformations

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GPU implementations for Fast Factorizations of STAP Covariance Matrices

GPU Implementations for Fast Factorizations of STAP Covarian...

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

作者： Roeder, Michael Davis, Nolan Furtek, Jeremy Braunreiter, Dennis Healy, Dennis Sci Applicat Int Corp 10260 Campus Point Dr San Diego CA 92121 USA DARPA Microsyst Technol Off Arlington VA 22203 USA

ISBN: (纸本)9780819472946

One of the main goals of the STAP-BOY program has been the implementation of a, space-time adaptive processing (STAP) algorithm on graphics processing units (GPUs) with the goal of reducing the processing time. Within the context of GPU implementation, we have further developed algorithms that exploit data redundancy inherent in particular STAP applications. Integration of these algorithms with GPU architecture is of primary importance for fast algorithmic processing times. STAP algorithms involve solving a linear system in which the transformation matrix is a covariance matrix. A standard method involves estimating a covariance matrix from a data matrix, computing its Cholesky factors by one of several methods. and then solving the system by substitution. Some STAP applications have redundancy in successive data matrices from which the covariance matrices are formed. For STAP applications in which a data matrix is updated with the addition of a new data row at the bottom and the elimination of the oldest data in the top of the matrix, a sequence of data matrices have multiple rows in common. Two methods have been developed for exploiting this type of data redundancy when computing Cholesky factors. These two methods are referred to as 1) Fast QR factorizations of successive data matrices 2) Fast Cholesky factorizations of successive covariance matrices. We have developed GPU implementations of these two methods. We show that these two algorithms exhibit reduced computational complexity when compared to benchmark algorithms that do not exploit data, redundancy. More importantly, we show that when these algorithmic improvements are optimized for the GPU architecture, the processing times of a GPU implementation of these matrix factorization algorithms may be greatly improved.

关键词： Covariance cholesky QR factorization GPGPU Space Time Adaptive processing (STAP) block update CUDA thread parallelism block parallelism

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Efficient implementation of a projection-based wave front sensor

Efficient implementation of a projection-based wave front se...

引用

conference on advanced signal processing algorithms, architectures and implementations XII

作者： Holder, J Cain, S Mantica, P Indiana Univ Purdue Univ ITT Aerosp Commun Div Ft Wayne IN 46805 USA

ISBN: (纸本)0819445584

In this paper, a new wave front sensor design that utilizes the benefits of image projections is described and analyzed. The projection-based wave front sensor is similar to a Shack-Hartman type wave front sensor, but uses a correlation algorithm as opposed to a centroiding algorithm to estimate optical tilt. This allows the projection-based wave front sensor to estimate optical tilt parameters while guiding off of point sources and extended objects at very low signal to noise ratios. The implementation of the projection-based wave front sensor is described in detail showings important signal processing steps on and off of the focal plane array of the sensor. In this paper the design is tested in simulation for speed and accuracy by processing simulated astro-nomical data. These simulations demonstrate the accuracy of the projection-based wave front sensor and its superior performance to that of the traditional Shack-Hartman wave front sensor. Timing analysis is presented which shows how the collection and processing of image projections is computationally efficient and lends itself to a wave front sensor design that can produce adaptive optical control signals at speeds of up to 500 hz.

关键词： Wavefront sensors Charge-coupled devices signal to noise ratio Image sensors Sensors Adaptive optics signal processing Detection and tracking algorithms Image processing Astronomy

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Time frequency guided design of quadratic filters

Time frequency guided design of quadratic filters

引用

conference on advanced signal processing algorithms, architectures and implementations XII

作者： Williams, WJ Quantum Signal LLC Ann Arbor MI USA

ISBN: (纸本)0819445584

Time-frequency distributions (TFDs) of Cohen's class often dramatically reveal complex structures that are not evident in the raw signal. Standard linear filters are often not able to separate the underlying signal from background clutter and noise. The essense of the signal can often be extracted from the TFD by evaluating strategic slices through the TFD for a series of frequencies. However, TFDs are often computationally intense compared to other methods. This paper demonstrates that quadratic filters may be designed to capture the same information as is available in the specific slices through the TFD at a considerably lower computational cost. The outputs of these filters can be combined to provide a robust impulse-like response to the chosen signal. This is particularly useful when the exact time series representation of the signal is unknown, due to variations and background clutter and noise. It is also noted that Teager's method is closely related to TFDs and are an example of a quadratic filter. Results using an ideal matched filter and the TFD motivated quadratic filter are compared to give insight into their relative responses.

关键词： time-frequency Teager speech quadratic filter reduced interference distributions

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