We have developed useful results on the application of low rank Matrix Completion (MC) in a colocated Multiple Input Multiple Output (MIMO) Radar setting, employed as a means for effectively reducing the volume of data required for target detection and estimation.
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We studied the applicability of MC on the type of data matrices appearing in colocated MIMO radar. In particular, for the classical case of a uniform linear array, we showed for the first time that the coherence of the data matrix is asymptotically optimal with respect to the number of antennas. As a result, the data matrix is provably recoverable via MC using a subset of its entries of minimal cardinality.
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These results were subsequently generalized to the case of an arbitrary 2-dimensional array, providing more general but yet easy to use sufficient conditions, ensuring low matrix coherence.
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Support:
- NSF Grant CNS-1239188 (pi: Dr. Athina Petropulu)
- ONR Grant N00014-12-1-0036 (pi: Dr. Athina Petropulu)
Selected Publications:
- D. S. Kalogerias and A. P. Petropulu, “Matrix Completion in Colocated MIMO Radar: Recoverability, Bounds & Theoretical Guarantees,” IEEE Transactions on Signal Processing, vol. 62, no. 2, pp. 309 – 321, January 2014.
- D. S. Kalogerias and A. P. Petropulu, “MC-MIMO Radar: Recoverability and Performance Bounds,” 1st IEEE Global Conference on Signal and Information Processing (GlobalSIP 2013), Austin, TX, USA, December 2013.
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