The ARPA/NAVY Mountaintop Program: adaptive signal processing for airborne early warning radar

Titi, G.W.; Marshall, D. F.

doi:10.1109/icassp.1996.543572

Cited by 76 publications

(27 citation statements)

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“…The COMET technique will now be used to estimate the parameters in the array covariance model (77). The primary purpose is to estimate to gain insight into the propagation conditions that may be expected in mobile communications; see also [19].…”

Section: Channel Estimationmentioning

confidence: 99%

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Covariance Matching Estimation Techniques for Array Signal Processing Applications

Ottersten

Stoica

Roy

1998

Digital Signal Processing

366

265

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Section: Channel Estimationmentioning

confidence: 99%

“…These data were collected under the ARPA/NAVY Mountaintop Program and the reader is referred to [77] for more details concerning the experiment.…”

Section: A Radar Experimentsmentioning

confidence: 99%

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Ottersten

Stoica

Roy

1998

Digital Signal Processing

366

265

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“…STAP consists in simultaneously processing spatial and temporal data. The basic theory of STAP is by now well developed [13,19,20,21]. An advanced airborne radar uses a© -element uniform linear array with interelement spacing A taken equal to halfwavelength.…”

Section: The Stap Contextmentioning

confidence: 99%

Application of the Global Matched Filter to Stap Data an Efficient Algorithmic Approach

Maria

Fuchs

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings

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The Global Matched Filter (GMF) is a mean to solve simultaneously detection and estimation problems. It has been applied mainly in source localization and delay estimation problems where the amount of data to be handled is reasonably small. This is not the case in the Space Time Adaptive Processing (STAP) context where the amount of data is extremely large and constitutes probably the major challenge. We present a very efficient algorithm that allows to apply the GMF to problems having several thousands unknowns. This allows its application to the STAP data. We detail both the algorithm and the implementation of the GMF to the STAP data. Since the GMF is a high resolution technique it outperforms the algorithms that are traditionally used in this context.

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“…이때 다양한 NHD 에 따른 성능 변화를 살펴보기 위하여 inner product(IP) 그리고 generalized inner product(GIP)뿐만 아 니라, 다수의 이상치(outlier)에 강한 PS [7] 표현되는 각 셀의 신호는 목표물, 개의 클러터, 잡음 신호의 합으로 나타낼 수 있다 [9] . [10], [11] . SαS 분포의 특 성함수는 다음과 같이 정의된다.…”

Section: 본 논문에서는 중위수를 이용한 간섭 공분산 행 렬의 예측 방법의 성능을 평가하기 위하여 다양한unclassified

Performance Analysis of Projection Statistics through Method of Clutter Covariance Matrix Estimation for STAP

Kang¹,

Kim²,

Jeong³

2011

The Journal of Korean Institute of Electromagnetic Engineering

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We analyze the performance of various techniques to overcome degradation of performance of STAP caused by nonhomogeneous clutter. The performance of NHD that used to eliminate outliers from nonhomogeneous clutter is improved by using the projection statistics(PS) that is robust to multiple outliers. The method of clutter covariance matrix estimation using a median value and the conventional method are also investigated and then compared. From the simulation results of STAP, the method of clutter covariance matrix estimation using a median value shows better performance than the conventional method for the calculation of the SINR loss, and MSMI for the single target and the multiple targets regardless of the NHD methods.

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The ARPA/NAVY Mountaintop Program: adaptive signal processing for airborne early warning radar

Cited by 76 publications

References 0 publications

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Covariance Matching Estimation Techniques for Array Signal Processing Applications

Application of the Global Matched Filter to Stap Data an Efficient Algorithmic Approach

Performance Analysis of Projection Statistics through Method of Clutter Covariance Matrix Estimation for STAP

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