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Matrix Completion in MIMO Radar

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.

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.

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.


  1. NSF Grant CNS-1239188 (pi: Dr. Athina Petropulu)
  2. ONR Grant N00014-12-1-0036 (pi: Dr. Athina Petropulu)

Selected Publications:

  1. 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.
  2. 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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