Adaptive detection using low rank approximation to a data matrix

Kirsteins, Ivars; Tufts, D.W.

doi:10.1109/7.250406

Cited by 214 publications

(33 citation statements)

References 22 publications

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“…A vast portion of the research effort has been devoted to the airborne STAP. Most of them are concerned about how to reduce the number of the secondary data, how to enhance the capability of detecting the slowly moving target, the computational complexity and the sample limitation for estimating the clutter covariance matrix, and so on; such as reduced-dimension (RD-STAP) [2], [3], reduced-rank (RR) [4], time varying spacetime auto regressive filtering (TV-STAR) [5], and the extend factor approach (EFA) [6].…”

Section: Introductionmentioning

confidence: 99%

High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

Cao¹,

Almslmany²,

Wang³

2015

RADIOENGINEERING

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Section: Introductionmentioning

confidence: 99%

High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

Cao¹,

Almslmany²,

Wang³

2015

RADIOENGINEERING

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“…It is based on the structure of the optimum interference canceller and requires a minimum number of assumptions about the interference characteristics. Intuitive arguments of how low-rank structure is natural in many sensor applications have been discussed in [7]. Performance analysis has shown that its performance is close to that of the clairvoyant processor that utilizes complete knowledge of the linear algebraic structure in the data [6,7].…”

Section: Difficulties In Auulving Freauencv Domain Methodsmentioning

confidence: 99%

Suppressing reverberation by multipath separation for improved buried object detection

Kirsteins

Fay²,

Kelly³

MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295)

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This paper addresses the problem of using a vertical aperture to suppress the interference caused to SAS by surface bounce path reverberation components decorrelated by the rough sea surface. Using at-sea gathered SACLANTCEN vertical array acoustic data, we characterize the reverberation vertical properties and investigate the separation of the direct and surface bounce path reverberation and target echo components. We propose two implementations of the PCI method of interference cancellation and demonstrate with actual data that they are effective in separating the reverberation in the vertical domain. I. BACKGROUNDThe detection of objects buried in the seabed by sonar has scores of applications, including mine hunting, cable and pipeline surveying, and archaeological research. This is a challenging problem. The physics of sound penetration into the seabed is a complicated phenomena that is governed by the frequency and the angle of the impinging acoustic field relative to the bottom interface. For grazing angles above the critical angle, Snell's theory predicts that sound will refract into sediment albeit with attenuation [l]. Since sediment attenuation [2] increases as a function of frequency, present day high frequency mine hunting sonars operating at hundreds of lcHz are ineffectual for detecting buried mines. However, the situation is better at low frequencies, e.g., in the 2-16 lrHz frequency band. Recently, investigators at SACLANTCEN 113 and elsewhere have found that there is substantial low frequency sound penetration into the sediment at angles above the critical angle and also at subcritical angles. At above critical angles, a SACLANTCEN study [l] found that buried mines were easily detectable in the 2-16 kHz frequency band, even down to a 50 cm burial depth.

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“…A measure of the power arriving from a direction θ is given by the function to be minimized in (1). If the exact MVDR beamformer w from equation (2) is used, then the expression for S xx in (1) can be simplified to S xx = 1/s H w. We show that this simplification is also valid when w is substituted by a low rank solution, w (r) using the CG algorithm.…”

Section: Computation Of the Power Spectrummentioning

confidence: 97%

“…where the Lagrange multiplier serves to satisfy the unity gain constraint in (1). In Steering-Independent CG, the CG algorithm is used to solve Rw = s; the solution obtained at step r of CG is denoted w (r) .…”

Section: Steering-independent Beamformingmentioning

confidence: 99%

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On low rank MVDR beamforming using the conjugate gradient algorithm

Santos

Zoltowski

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

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In array applications an important task is adaptive beamforming. The Minimum Variance Distortionless Response (MVDR) beamformer can only be computed if the true spatial correlation matrix is available. In practice, the correlation matrix has to be estimated from the arriving signals, and in some cases there are only a small number of samples (snapshots) available. When the number of snapshots is small, the MVDR beamformer is no longer optimal, and a low rank MVDR solution can provide a higher SINR. In this work we will analyze two methods of finding low rank solutions: Steering Independent Conjugate Gradient (SI-CG) and Steering Dependent Conjugate Gradient (SD-CG). We will also propose a simplified expression to compute the arriving power from any given direction.

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Adaptive detection using low rank approximation to a data matrix

Cited by 214 publications

References 22 publications

High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

Suppressing reverberation by multipath separation for improved buried object detection

On low rank MVDR beamforming using the conjugate gradient algorithm

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