Performance analysis for an interferometric space-based GMTI radar system

Sedwick, Raymond J.; Hacker, Troy L.; Marais, Karen

doi:10.1109/radar.2000.851917

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…From the left part of Fig. 1, we can see that the value of the angle must be less than 0.16 in order to make approximation error less than 4 10 − . In this case, the upper limit of max k is 4B .…”

Section: Theoretical Limitation Of the New Methodsmentioning

confidence: 99%

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A new method of cluster optimization design for scanned pattern interferometric radar

Zhu

Dian-nong

2007

SPIE Proceedings

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To deal with the contravention between the reversibility of the point spread function of scanned pattern interferometric radar and the improvement of the azimuth resolution of the radar system, the paper presents a new method of cluster optimization design. The method bases on the variability of the maximum spatial frequency number of the theoretical formula of the array factor. By selecting an appropriate maximum spatial frequency number, we get a new aperture array. The array designed by this method not only can get the desirable azimuth resolution but also can guarantee the reversibility of the point spread function. Simulations validate the correctness of the method. At last, we also discuss the applicability of the method.

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Section: Theoretical Limitation Of the New Methodsmentioning

confidence: 99%

“…Compared with air-borne GMTI, space-borne GMTI has a good many advantages, but it encounters many theoretical and technologic challenges [4] .To tackle these challenges, scientists have presented different kinds of schemes. Scanned Pattern Interferometric Radar (SPIR) was firstly presented by Karen marais and Raymond Sedwick in the 2001.…”

Section: Introductionmentioning

confidence: 99%

A new method of cluster optimization design for scanned pattern interferometric radar

Zhu

Dian-nong

2007

SPIE Proceedings

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“…Space-time adaptive processing (STAP) [1,2] has been widely used in airborne early warning (AEW) radar since the 1970s and it is a key technology for clutter suppression. After nearly 40 years of development, the application of the STAP method has also expanded to many aeras, such as spaceborne battlefield surveillance radar [3,4] and radar imaging [5,6]. Detecting a weak and slow-moving target that is submerged by ground clutter is a challenging problem, and the STAP method plays an important role in suppressing strong clutter.…”

Section: Introductionmentioning

confidence: 99%

A Fast IAA–Based SR–STAP Method for Airborne Radar

Zhang,

Wang,

Liu

et al. 2024

Remote Sensing

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Space−time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for traditional STAP methods. Sparse recovery−based STAP (SR−STAP) methods have received widespread attention in the past few years. The accurate estimation of the clutter plus noise covariance matrix can be achieved using only a few training samples. The iterative adaptive approach (IAA) can quickly and accurately estimate the power spectrum, but applying this method directly to the STAP method cannot produce good performance. In this paper, a fast IAA−based SR−STAP method is proposed. Based on the weighted problem, the IAA spectrum is used as a weighted term to obtain a good approximation. In order to obtain an analytical solution, we use the weighted norm to approximate the weighted norm without loss of performance. Compared with the IAA−STAP method, the proposed method is more robust to errors. Moreover, the proposed method has a fast computational speed. The effectiveness of the proposed method is demonstrated by simulations.

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“…The cluster of satellites forms a large (∼100m), sparse, multielement, time varying phased array with narrow beamwidth and concomitant grating or random sidelobes that introduce significant ground clutter into the received signal. Previous work described approaches to distributed space-based radar employing satellites in a single orbital plane [3,6,7,8,11,17]. In our previous work [9,10,12,13,14,15], the satellites were assumed to be in multiple, nearly circular, low Earth orbits with a common orbital plane and thus form a sparse, periodic, two dimensional transmit-receive array with limited along track dimension operating at one of a carefully selected set of PRFs.…”

Section: Introductionmentioning

confidence: 99%

Transmit beamforming and waveforms for random, sparse array radar

Schindler

Steyskal

2004

2004 International Waveform Diversity &Amp; Design Conference

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We address the design of radar waveforms, transmit and receive beamforming, and signal processing in moving, sparse array antennas with randomly positioned elements. We are motivated by a concept for less expensive space based radar consisting of a formation of small, autonomous, identical satellites in nearly the same low earth orbits. The satellites operate collaboratively as a coherent, large aperture radar to detect and locate slowly moving targets near the earth surface. Limited fuel mandates that the satellites navigate only to avoid collision within array aperture limits and not necessarily to maintain any ideal array antenna configuration.

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Performance analysis for an interferometric space-based GMTI radar system

Cited by 6 publications

References 3 publications

A new method of cluster optimization design for scanned pattern interferometric radar

A new method of cluster optimization design for scanned pattern interferometric radar

A Fast IAA–Based SR–STAP Method for Airborne Radar

Transmit beamforming and waveforms for random, sparse array radar

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