Radar and Sonar Signal Processing

An Adaptive-Gain Alpha-Beta Tracker Combined with Three-Dimensional Circular Prediction Using Estimation of the Plane State

Authors:

Tetsuya Kawase,
Hideshi Tsurunosono,
Naoki Ehara,
Iwao Sasase,

Page (NA) Paper number 1427

Abstract:

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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Matched Window Processing for Mitigating Over-The-Horizon Radar Spread Doppler Clutter

Authors:

Kerem Harmanci, Duke University (U.K.)
Jeffrey L Krolik, Duke University (U.K.)

Page (NA) Paper number 2375

Abstract:

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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Non-Conventional Application of Robust Matched-Field Localization: Small Aperture Array and Mid-Frequency Signals

Authors:

Brian F Harrison,

Page (NA) Paper number 1316

Abstract:

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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Bayesian Estimation Of Non-Minimum Phase Wavelets Applied To Marine Reflection Seismic Data

Authors:

Olivier Rosec, ENST de Bretagne, SC department, BP 832, 29285 Brest Cedex France (France)
Jean-Marc Boucher, ENST de Bretagne, SC department, BP 832, 29285 Brest Cedex France (France)

Page (NA) Paper number 1867

Abstract:

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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Jitter Identification Techniques for a Regular Event-Based Process

Authors:

Stephen D Elton,

Page (NA) Paper number 1358

Abstract:

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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A New Estimation Technique For Near-Shore Bathymetric Measurements

Authors:

S. Radhakrishnan Pillai,
Hyun Seok Oh,

Page (NA) Paper number 1722

Abstract:

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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Fast Range and Doppler Estimation For Narrowband Active Sonar

Authors:

Saul R Dooley,
Asoke K Nandi,

Page (NA) Paper number 1136

Abstract:

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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Time Delay Estimation in Unknown Spatially Uncorrelated Gaussian Noises Using Higher-Order Statistics

Authors:

Yong Wu, Depart. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, USA (USA)
A. Rahim Leyman, School of EEE, Nanyang Technological University , Singapore (Singapore)

Page (NA) Paper number 1012

Abstract:

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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Joint Estimation of DOA and Time-Delay in Underwater Localization

Authors:

Qunfei Zhang, Northwestern Poly. Univ., P.R.China (China)
Jianguo Huang, Northwestern Poly. Univ., P.R.China (China)

Page (NA) Paper number 2356

Abstract:

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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