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Title
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Sparse multidimensional exponential analysis with an application to radar imaging
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Author
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Abstract
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| We present a d-dimensional exponential analysis algorithm that offers a range of advantages compared to other methods. The technique does not suffer the curse of dimensionality and only needs O((d + 1)n) samples for the analysis of an n-sparse expression. It does not require a prior estimate of the sparsity n of the d-variate exponential sum. The method can work with sub-Nyquist sampled data and offers a validation step, which is very useful in low SNR conditions. A favorable computation cost results from the fact that d independent smaller systems are solved instead of one large system incorporating all measurements simultaneously. So the method easily lends itself to a parallel execution. Our motivation to develop the technique comes from 2-D and 3-D radar imaging and is therefore illustrated on such examples. |
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Language
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English
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Source (journal)
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SIAM journal on scientific computing. - Philadelphia, Pa
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Publication
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Philadelphia, Pa
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2020
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ISSN
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1064-8275
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DOI
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10.1137/19M1278004
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Volume/pages
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42
:3
(2020)
, p. B675-B695
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ISI
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000551255700024
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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