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Abstract: Session SAM-2 |
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SAM-2.1
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An Adaptive-Gain Alpha-Beta Tracker Combined with Three-Dimentional Circular Prediction Using Estimation of the Plane State
Tetsuya Kawase,
Hideshi Tsurunosono,
Naoki Ehara,
Iwao Sasase (Keio University)
In tracking systems using phased array antenna, the adaptive-gain alpha-beta tracker
combined with circular prediction has been proposed for maneuvering targets.
However, tracking quality of the circular prediction filter degrades for highly maneuvering targets
that continue to change the turning plane, since the circular prediction is calculated
on the assumption that a target flies on the same plane of previous three measured positions.
In this paper, we extend the circular prediction to three-dimentional space and
propose the adaptive-gain alpha-beta tracker combined with three-dimentional circular prediction
using estimation of the plane state to improve tracking quality.
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SAM-2.2
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Matched Window Processing for Mitigating Over-The-Horizon Radar Spread Doppler Clutter
Kerem Harmanci,
Jeffrey L Krolik (Duke University)
Ionospheric motion causes spreading of surface clutter
in Doppler space which fundamentally limits the
detection performance of skywave HF over-the-horizon
radars. This paper presents a technique which reduces
the effect of so-called ``coincident'' spread Doppler
clutter, i.e. that which results from surface
scattering from within the same range resolution
cell as the target. The method exploits the spatial
correlation of the ionospheric aberration along the
geomagnetic field aligned irregularities to obtain a
cross-relation between clutter in neighboring range
bins. This cross relation is exploited to estimate
the Doppler spreading sequence common to neighboring
range bins by a technique adapted from blind
multichannel system identification. A Chebyshev
Doppler window is then designed which is matched
to the estimated ionospheric aberration. Simulation
and real data results presented here indicate the
proposed method provides as much as 10 dB improvement
in sidelobe level using a 3 second coherent
integration time radar waveform.
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SAM-2.3
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Non-Conventional Application of Robust Matched-Field Localization: Small Aperture Array and Mid-Frequency Signals
Brian F Harrison (Naval Undersea Warfare Center)
Conventional applications of matched-field processing (MFP)
use large aperture vertical arrays and low frequency signals. It
is well known that MFP's sensitivity to environmental
mismatch is proportional to frequency. Thus, real-world
application of MFP to mid-frequency signals, e.g.,
800 - 3000 Hz, is generally regarded a very difficult
problem. Using small aperture vertical arrays can also
compromise the performance of MFP. However, small aperture
arrays are more practical for real-world scenarios. In
this paper, we propose the broadband L-infinity-norm
estimator for robust broadband matched-field localization
of mid-frequency signals received on extremely small
aperture vertical arrays. Results using a simulated
Gulf of Mexico environment for broadband signals
(1000 - 3000 Hz) received on a 3-meter vertical array
demonstrate the significant performance gains in using
the L-infinity-norm estimator over the asymptotically-optimal
maximum a posteriori estimator in the presence of finite
environmental sampling.
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SAM-2.4
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Bayesian estimation of non-minimum phase wavelets applied to marine reflection seismic data
Olivier Rosec,
Jean-Marc Boucher (ENST de Bretagne, SC department, BP 832, 29285 Brest Cedex France)
In this paper, the problem of wavelet estimation for marine seismology is investigated with a bayesian approach applied to a Bernoulli-Gaussian model.
We specify proper prior distributions for all unknown quantities including the seismic wavelet, the parameters of the reflectivity sequence and noise.
To solve this estimation problem, an algorithm close to a stochastic version of the EM algorithm is used.
The random variables are generated iteratively by a simple Monte-Carlo method namely the Gibbs sampler.
But the direct application of this procedure often leads to a local minimum of the likelihood function resulting in a shifted and distorted wavelet.
We propose a general method to obtain the true solution which systematycally uses different shifted wavelets to reinitialize the algorithm.
Then we rerun the procedure on each initialization and retain the wavelet which minimizes the noise variance.
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SAM-2.5
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Jitter Identification Techniques for a Regular Event-Based Process
Stephen D Elton (Defence Science and Technology Organisation)
Two system identification techniques are proposed for discriminating
between the type of timing jitter that perturbs the arrival time
sequence recorded for an event-based process. A univariate point
process is used to characterise the observed signal activity. The
first jitter identification method requires a visual inspection of an
estimate of the expectation density computed for the point
process. The second method involves a statistical hypothesis test for
a renewal process.
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SAM-2.6
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A New Estimation Technique For Near-Shore Bathymetric Measuments
Radhakrishnan S Pillai (Zetron, Inc. Advanced Development),
Hyun S Oh (Department of Electrical Engineering, Polytechnic University)
A new technique for depth estimation in airborne laser bathymetry is
proposed. The technique involves the transmission of a nonlinear
frequency-modulated signal,
the detection of the signal reflected by the ocean,
and its processing using an appropriate matched filter. On the basis of this
technique, a receiver can be constructed that offers improved resolution
between the signals reflected by the surface and bottom of the ocean which
translates into improved accuracy of depth measurement.
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SAM-2.7
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Fast Range and Doppler estimation for narrowband active sonar
Saul R Dooley,
Asoke K Nandi (University of Strathclyde)
In this paper, we present a computationally simple
algorithm suitable for fast, high resolution
estimation of time delays and doppler shifts
(which are necessary for target localization and
tracking) between narrowband signals in an active
sonar system. The algorithm uses a modulated Lagrange
interpolation filter and an LMS-type algorithm. The
problem of delay and doppler estimation is reduced to
a linear regression problem. Convergence and
performance analysis of the method is studied both
analytically and through simulation. It is demonstrated
that the method provides estimates close to the
Cramer-Rao Lower Bound.
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SAM-2.8
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Time Delay Estimation in Unknown Spatially Uncorrelated Gaussian Noises Using Higher-Order Statistics
Yong Wu (Depart. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, USA),
A. Rahim Leyman (School of EEE, Nanyang Technological University , Singapore)
Bispectrum methods have been proposed for non-Gaussian
signal Time Delay Estimation(TDE) problem.
When the signal is non-Gaussian and additive noises
are spatially uncorrelated Gaussian, the bispectrum
methods are outperformed by Generalized Cross-Correlation(GCC)
methods. This problem is addressed in this paper and
new methods are proposed to improve the TDE performance.
The new methods exploit the Higher-Order Statistics
characteristics of the signals and formulate weighting
functions to improve the time delay estimation. Computer
simulation results show that the new methods outperform
both the GCC and the bispectrum methods.
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SAM-2.9
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Joint Estimation of DOA and Time-Delay in Underwater Localization
Qunfei Zhang,
Jianguo Huang (Northwestern Poly. Univ., P.R.China)
Joint estimation of direction of arrival (DOA) and time delay plays a great role in source localization, which attracts many researchers not only in the areas of radar, sonar, geological exploration but also in wireless communication. [1][2][3][4] M. Wax applies approximate MLE with iteration algorithm [1], which convert a 2-D search into two or three 1-D search. A.J.van der Veen use 2-D ESPRIT to conduct joint estimation [2]. Both of them show good performance at a cost of large computation. And both of them require deconvolution in frequency domain to transfer time-delay into phase. The deconvolution leads to two problems. One is blowing up noise, the other is leading to spurious peak if the emitted signal is non-minimum phase. In this paper, a simple method using 1-D ESPRIT is presented to complete joint estimation of DOA and time-delay, which requires no deconvolution. It is suitable for active underwater localization where non-minimum phase signal is frequently employed. The method can estimate parameters of three reflectors with big difference between amplitudes as large as 12dB. The statistical performance of new estimators and the probability of correct pairing are given by computer simulations. It shows that better performance of the new method can be achieved for multiple source localization even in low SNR.
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