Singular value decomposition-based method for solving a deterministic adaptive problem

Sheeyun Park, Tapan K. Sarkar, Yingbo Hua

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


A computational scheme based on the singular value decomposition (SVD) for a deterministic, data domain approach to the adaptive processing problem is presented. In the direct data domain approach, a single snapshot is considered for an assumed direction of arrival with unknown amplitude. This unknown signal strength is estimated on a snapshot by snapshot basis. The new SVD based method is compared with the QZ method for determining the generalized eigenvalues of a system. Their performance in estimating the strength of signals of interest in the presence of main beam jammers, clutter, and thermal noise is considered. Limited examples have been presented to illustrate the two methods.

Original languageEnglish (US)
Pages (from-to)57-63
Number of pages7
JournalDigital Signal Processing: A Review Journal
Issue number1
StatePublished - Jan 1999

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing
  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics


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