Home HomeJean Jacques Fuchs, IRISA (France)
A transmitted and known signal is observed at the receiver through more than one path in additive noise. The problem is to estimate the number of paths and for each of them the associated attenuation and delay. It is a frequent problem in sonar, radar and geophysics. We propose an algorithm that is easy to implement, that has a reasonable computational load and seems to be able to solve the problem under more severe conditions (lower SNR) than previous methods.
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Robert B. MacLeod, NUWC (U.S.A.)
Richard J. Vaccaro, University of Rhode Island (U.S.A.)
In this paper we are concerned with signal processing of acoustic signals resulting from active transmissions by high frequency sonar systems. These signals consist of structured interference related to propagation effects in the media, reflections from targets, and measurement noise. The methods herein model these signals as replicas of the transmitted signal, scaled in amplitude and time, and delayed. Furthermore, we are interested in signals with `simple' time frequency profiles, such as linear frequency modulated (LFM) or hyperbolic frequency modulated (HFM) signals. These signals have the underlying property that the principle ridge of the autoambiguity function crosses the mid point of the time-frequency plane in a smooth manner, with a simple relationship between time delay and time scaling (frequency shifting). This paper describes a method for estimating the delay and time scale of signal components using fast maximum likelihood, while preserving the high resolution property of related time delay estimation techniques.
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Amir W. Habboosh, NUWCDIVNPT (U.S.A.)
Richard J. Vaccaro, University of Rhode Island (U.S.A.)
Steven M. Kay, University of Rhode Island (U.S.A.)
This paper considers a method for estimating time delays, amplitudes, and Doppler scales of a multipath signal. The method is an extension of work previously reported by Manickam and Vaccaro which dealt solely with time delays and amplitudes, and extended by Habboosh and Vaccaro to include Doppler scale. In this paper, an algorithm is presented for determining the size of the indicator set to reduce ill-conditioning of the signal subspace matrix. Simulation results are shown and comparisons to the Cramer-Rao lower bound provided; these results show that significant reduction in estimate variances can be achieved using the deconvolution approach with a properly selected indicator set.
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Shi Quan Wu, The Chinese University of Hong Kong (Hong Kong)
Hing Cheung So, City University of Hong Kong (Hong Kong)
Pak Chung Ching, The Chinese University of Hong Kong (Hong Kong)
In this paper, wavelet denoising is applied in time delay estimation between signals received at two spatially separated sensors in the presence of noise. Prior to cross correlation, each of the sensor outputs is denoised according to a novel thresholding rule in order to increase the input signal-to-noise ratio. Unlike conventional generalized cross correlators (GCCs), it does not require spectral estimation of the source signal and the corrupting noises which may introduce large delay variance. It is proved that the delay estimate provided by the proposed method is globally convergent to the true value with a high probability. Computer simulations illustrate that the technique outperforms other GCCs for different SNRs when the sampling rate is sufficiently high.
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Charles W. Therrien, NPS, Monterey (U.S.A.)
K.L. Frack, NPS, Monterey (U.S.A.)
N. Ruiz Fontes, NPS, Monterey (U.S.A.)
A noise removal algorithm based on short-time Wiener filtering is described. An analysis of the performance of the filter in terms of processing gain, mean square error, and signal distortion is presented. A generalized form of the filter is also discussed and results of applying the algorithm to some typical underwater acoustic data are presented.
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Donald W. Tufts, University of Rhode Island (U.S.A.)
Edward C. Real, Sanders, A Lockheed Martin Company (U.S.A.)
James W. Cooley, University of Rhode Island (U.S.A.)
A new fast and accurate algorithm for tracking singular values, singular vectors and the dimension of the signal subspace through an overlapping sequence of data matrices is presented. The accuracy of the algorithm approaches that of the Prony-Lanczos method with speed and accuracy superior to both the PAST and PASTd algorithms for moderate to large size problems. The algorithm is described for the special case of changes to two columns of the matrix prior to each update of principal singular vectors and values. Comparisons of speed and accuracy are made with the algorithms named above.
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Brian E. Freburger, University of Rhode Island (U.S.A.)
Donald W. Tufts, University of Rhode Island (U.S.A.)
Tom A. Palka, University of Rhode Island (U.S.A.)
An efficient scheme for implementing a search of a likelihood function of known form at moderate to high SNR is constructed. Often, the original function to be searched is ill behaved with many local extreme points. By projecting the signal onto a subspace of replica waveforms we first find the maximum of a related function that is more well behaved, and then follow with a local search on the original function. The approach builds on a previous method of estimation of time delay of a narrowband signal, and it can be used to improve the efficiency of Fast Maximum Likelihood estimation.
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Nirmal Keshava, Carnegie Mellon University (U.S.A.)
José M.F. Moura, Carnegie Mellon University (U.S.A.)
POL-SAR data acquired from the two 1994 flights of the SIR-C/X-SAR platform has illustrated the variability of measurements due to seasonal, spectral, and angular changes. Consequently, statistical techniques for terrain classification make robust, unsupervised classification problematic. We present an algorithm for classifying terrain that accounts for variability in terrain signatures by deriving a single representative process for each terrain from a family of stochastic scattering models. A best-basis search through a wavelet packet tree, using the Bhattacharyya coefficient as a cost measure, determines the optimal unitary basis of eigenvectors for the representative process and offers a scale-based interpretation of the scattering phenomena. The associated eigenvalues and means are determined through iterative algorithms. The technique is illustrated with a simple example.
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Michael Papazoglou, Duke University Dept. of ECE (U.S.A.)
Jeffrey L. Krolik, Duke University Dept. of ECE (U.S.A.)
The refraction of over-the-horizon skywave radar signals by the ionosphere facilitates wide-area surveillance. While current systems measure target ground range, azimuth, and velocity they do not estimate target altitude, which is important for classification purposes. In this paper, a method akin to matched-field processing in underwater acoustics is proposed for target height-finding. The approach exploits the delay-Doppler differences between direct and surface-reflected multipath returns from the target. In particular, the coherent sum of these multipath returns can be matched in the complex delay-Doppler space for a single dwell to estimate target altitude, ground range, and radial velocity. In this paper, a maximum likelihood estimate (MLE) of these target coordinates is developed without requiring knowledge of the target backscatter reflection coefficients. The performance of the MLE is evaluated through simulation for an uncertain quasi-parabolic ionosphere and compared to the Cramer-Rao lower bound (CRLB).
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Geoff Roberts, SPRC, Queensland University of Technology (Australia)
Abdelhak M. Zoubir, SPRC, Queensland University of Technology (Australia)
Boualem Boashash, SPRC, Queensland University of Technology (Australia)
We present a non-stationary signal classification algorithm based on a time-frequency representation and a multiple hypothesis test. The time-frequency representation is used to construct a time-dependent quadratic discriminant function. At selected points in time we evaluate the discriminant function and form a set of statistics which are used to test the multiple hypotheses. The multiple hypotheses are treated simultaneously using the sequentially rejective Bonferroni test to control the probability of incorrect classification of one class. We show results for classifying three classes of humpback whale calls. The results demonstrate that this time-frequency method performs favourable when compared with a frequency domain method which assumes stationarity.
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Jianguo Huang, NPU, Shaanxi (China)
Jianping Zhao, NPU, Shaanxi (China)
Yiqing Xie, NPU, Shaanxi (China)
An easy and efficient method to classify the underwater sources for passive sonar by extracting poles of AR model as the feature of source emitted noise is proposed . Our research demonstrates that poles of AR model can represent the intrinsic spectral characteristic of sources, and the simple statistical classifiers can be used to have excellent recognition performance due to the good cluster property and robustness of poles corresponding to different sources. It is more important that poles of low order AR model can represent the basic feature of source, thus the computation burden will be reduced significantly. Real data are processed and classification results show the efficiency even for short data records.
ic970567.pdf TOPHongya Ge, New Jersey Institute of Technology (U.S.A.)
Presented in this work are analytical expressions of the performance measure on the LMMSE estimate-based multiuser detector, including error probability expression and its computationally and notationally efficient approximations, signal to interference-plus-noise ratio, and asymptotic efficiency. Also included in this work are adaptive implementation schemes of the LMMSE detector and the equivalent relation between them under appropriate assumptions. Simulations are included to show the tightness of approximate results over a wide range of near-far ratio and various combinations of SNRs of interfering multiple-access users.
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Mark Johnson, WHOI (U.S.A.)
Lee E. Freitag, WHOI (U.S.A.)
Milica Stojanovic, NEU (U.S.A.)
The performance of coherent acoustic communication systems involving moving platforms (e.g., underwater vehicles and ships) is adversely effected by Doppler shift resulting from relative motion of the transmitter and receiver. This paper presents a series of innovations which, together, dramatically improve the response to Doppler shift of a widely-used adaptive receiver algorithm. The innovations include a frequency-shift estimator, time-scale interpolator and robust phase-locked loop (PLL). These techniques reduce the computational load of the coherent equalizer and provide accurate Doppler tracking. Results from at-sea testing are presented to illustrate the performance of the combined algorithm.
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Bayan S. Sharif, University of Newcastle (U.K.)
Jeff Neasham, University of Newcastle (U.K.)
David Thompson, University of Newcastle (U.K.)
Oliver R. Hinton, University of Newcastle (U.K.)
Alan E. Adams, University of Newcastle (U.K.)
This paper presents the development and performance of blind algorithms for a spatial diversity scheme to enable reliable data telemetry over a long range underwater acoustic channel. A number of Bussgang based stochastic gradient algorithms were tested for this multipath channel with additive white and coloured shipping noise. Both simulation and real experimental tests have shown that a significant improvement is obtained by utilising the spatial diversity of the long range channel and the ability of the combiner to perform joint equalisation and carrier phase tracking.
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