This paper describes an efficient implementation of auxiliary constraints for a concurrent block least squares adaptive sidelobe canceller when a single array of sensors is used to form one or more main beams. The app...
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ISBN:
(纸本)0819406945
This paper describes an efficient implementation of auxiliary constraints for a concurrent block least squares adaptive sidelobe canceller when a single array of sensors is used to form one or more main beams. The approach is to compute QR decomposition of the auxiliary data matrix and then send this information to main beam processors, where the constraints are applied using a blocking matrix and the individual residuals are computed. The blocking matrix can be chosen with special structure which is used to derive a new fast algorithm and architecture for constrained main beam processing that reduces the operation count from order n3 to order n2, where n is the number of auxiliary sensors.
This paper describes a cascade decomposition of the generalized sidelobe canceller (GSC) implementation for linearly constrained minimum variance beamformers. The GSC is initially separated into an adaptive interferen...
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ISBN:
(纸本)0819406945
This paper describes a cascade decomposition of the generalized sidelobe canceller (GSC) implementation for linearly constrained minimum variance beamformers. The GSC is initially separated into an adaptive interference cancellation module followed by a non-adaptive beamformer. We prove that the adaptive interference cancellation module can be decomposed into a cascade of first (or higher) order adaptive interference cancellation modules, where the order corresponds to the number of adaptive degrees of freedom represented in the module. This distributes the computational burden associated with determining the adaptive weights over several lower order problems and facilitates simultaneous implementation of beamformers with differing numbers of adaptive degrees of freedom.
We compare the performance of three parallel supercomputers executing a bispectrum estimation code used to remove distortions from astronomical data. We discuss the issues in parallelizing the code on an 8-processor s...
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ISBN:
(纸本)0819406945
We compare the performance of three parallel supercomputers executing a bispectrum estimation code used to remove distortions from astronomical data. We discuss the issues in parallelizing the code on an 8-processor shared-memory CRAY Y-MP and a 1024-processor distributed-memory nCUBE machine. Results show that elapsed times on the nCUBE machine are comparable to those on the CRAY Y-MP. Execution of the nCUBE was more than 40 times faster than that of a single processor CRAY-2 resulting in more than 50 times better cost performance. Cost performance on the nCUBE is more than 25 times better than an 8- processor CRAY Y-MP.
A new approach to the problem of detecting the number of signals in unknown colored noise environments is presented. Based on an assumption that the noise is correlated only over a limited spatial range, the principle...
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ISBN:
(纸本)0819406945
A new approach to the problem of detecting the number of signals in unknown colored noise environments is presented. Based on an assumption that the noise is correlated only over a limited spatial range, the principle of canonical correlation analysis is applied to the outputs of two spatially-separated arrays. The number of signals is determined by testing the significance of the sample canonical correlation coefficients. The new method is shown to work well in both white and unknown colored noise situations and does not require any subjective threshold setting. Instead, a set of threshold values are generated according to a specified or desired false alarm rate. Simulation results are included to illustrate the comparative performance of the proposed canonical correlation technique (CCT), versus the well-known AIC and MDL criteria, in colored noise. It is found that the performance of the AIC and MDL criteria degrade very rapidly as the degree of color in the noise increases. On the other hand, the performance of the CCT method is relatively insensitive with respect to variations in degree of color.
A new preconditioner is proposed for the solution of an N × N Toeplitz system TNx = b, where TN can be symmetric indefinite or nonsymmetric, by preconditioned iterative methods. The preconditioner FN is obtained ...
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ISBN:
(纸本)0819406945
A new preconditioner is proposed for the solution of an N × N Toeplitz system TNx = b, where TN can be symmetric indefinite or nonsymmetric, by preconditioned iterative methods. The preconditioner FN is obtained based on factorizing the generating function T(z) into the product of two terms corresponding, respectively, to minimum-phase causal and anticausal systems and therefore called the minimum-phase LU (MPLU) factorization preconditioner. Due to the minimum-phase property, F N-1 is bounded. For rational Toeplitz TN with generating function T(z) = A(z-1)/B(z-1) + C(z)/D(z), where A(z), B(z), C(z), and D(z) are polynomials of orders p1, q1, p2, and q2, we show that the eigenvalues of FN-1TN are repeated exactly at 1 except at most α F outliers, where αF depends on p1, q1, p2, q2, and the number approximately ega of the roots of T(z) = A(z-1)D(z) + B(z-1)C(z) outside the unit circle. A preconditioner KN in circulant form generalized from the symmetric case is also presented for comparison.
A general solution for the problem of time-frequency signal representation of nonlinear FM signals is provided, based on a generalization of the Wigner-Ville distribution. The Wigner-Ville distribution (WVD) is a seco...
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ISBN:
(纸本)0819406945
A general solution for the problem of time-frequency signal representation of nonlinear FM signals is provided, based on a generalization of the Wigner-Ville distribution. The Wigner-Ville distribution (WVD) is a second order time-frequency representation. That is, it is able to give ideal energy concentration for quadratic phase signals and its ensemble average is a second order time-varying spectrum. The same holds for Cohen's class of time-frequency distributions, which are smoothed versions of the WVD. The WVD may be extended so as to achieve ideal energy concentration for higher order phase laws, and such that the expectation is a time-varying higher order spectrum. The usefulness of these generalized Wigner-Ville distributions (GWVD) is twofold. Firstly, because they achieve ideal energy concentration for polynomial phase signals, they may be used for optimal instantaneous frequency estimation. Second, they are useful for discriminating between nonstationary processes of differing higher order moments. In the same way that the WVD is generalized, we generalize Cohen's class of TFDs by defining a class of generalized time-frequency distributions (GTFDs) obtained by a two dimensional smoothing of the GWVD. Another results derived from this approach is a method based on higher order spectra which allows the separation of cross-terms and auto- terms in the WVD.
The kernel in Cohen's generalized time-frequency representation (GTFR) requires is chosen in accordance to certain desired performance attributes. Properties of the kernel are typically expressed as constraints. W...
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The kernel in Cohen's generalized time-frequency representation (GTFR) requires is chosen in accordance to certain desired performance attributes. Properties of the kernel are typically expressed as constraints. We establish that many commonly used constraints are convex in the sense that all allowable kernels satisfying a given constraint form a convex set. Thus, for a given set of constraints, the kernel can be designed by alternately projecting among these sets. If there exists a nonempty intersection among the constraint sets, then the theory of projection onto convex sets (POCS) guarantees convergence to a point in the intersection. If the constraints can be partitioned into two sets, each with a nonempty intersection, the POCS guarantees convergence to a kernel that satisfies the inconsistent constraints with minimum mean square error.
The proceedings contain 31 papers. The topics discussed include: numerical linear algebra on the CEDAR multiprocessor;a novel MVDR beamforming algorithm;adaptive beamforming using real arithmetic;systolic kalman filte...
The proceedings contain 31 papers. The topics discussed include: numerical linear algebra on the CEDAR multiprocessor;a novel MVDR beamforming algorithm;adaptive beamforming using real arithmetic;systolic kalman filtering based on QR decomposition;systolic architecture for extended kalman filtering;triangular systolic arrays and related fault tolerance;robust spectral estimation;robust spectral estimation;signal eigenvector method for general array signalprocessing;a signal subspace method for interference cancellation;and linear system description using Wigner distribution functions.
An advancedsignalprocessing laboratory has been assembled at Martin Marietta in Baltimore, Maryland, based on the SAXPY MATRIX 1 supercomputer. This parallel processor has a 1 Gflop peak computational capacity. It w...
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The key to meeting the extremely high throughput requirements of future military signal and image processing systems is parallelism in algorithms and hardware. This paper will describe the implementation of a core set...
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