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On using a priori k...
On using a priori knowledge in space-time adaptive processing
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- Stoica, Peter, 1949- (författare)
- Uppsala universitet,Avdelningen för systemteknik,Reglerteknik
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Li, Jian (författare)
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Zhu, Xumin (författare)
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Guerci, J (författare)
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(creator_code:org_t)
- 2008
- 2008
- Engelska.
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Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 56:6, s. 2598-2602
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In space-time adaptive processing (STAP), the clutter covariance matrix is routinely estimated from secondary "target-free" data. Because this type of data is, more often than not, rather scarce, the so-obtained estimates of the clutter covariance matrix are typically rather poor. In knowledge-aided (KA) STAP, an a priori guess of the clutter covariance matrix (e.g., derived from knowledge of the terrain probed by the radar) is available. In this note, we describe a computationally simple and fully automatic method for combining this prior guess with secondary data to obtain a theoretically optimal (in the mean-squared error sense) estimate of the clutter covariance matrix. The authors apply the proposed method to the KASSPER data set to illustrate the type of achievable performance.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- convex combination
- general linear combination
- knowledge-aided
- space-time adaptive processing
- Information technology
- Informationsteknik
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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