Dual Channel Matched Filtering and Space-Time Adaptive Processing
Abstract
We propose a dual channel matched filtering system that addresses two key challenges in the practical implementation of a single channel matched filtering system: secondary data support and computational cost. We demonstrated that the dual channel system requires half the secondary data to achieve nearly the same signal-to-interference plus noise ratio (SINR) as an equivalent single channel system. The key to the dual channel system is the block diagonalization of the interference plus noise correlation matrix with a fixed transformation. We investigated the application of this dual channel concept to the problem of space-time adaptive processing (STAP), referring to the system as Block STAP. We provide evidence that the family of STAP correlation matrices cannot be simultaneously block diagonalized with a fixed transformation, and thus, the Block STAP processor is suboptimal. We propose a transformation selection criterion for minimizing the loss in SINR performance of the suboptimal Block STAP processor. Finally, we introduce the SINR metric and a new eigen-based, reduced-rank direct form STAP processor based on the SINR metric. The SINR metric is used to identify the eigenvectors of the correlation matrix that have the greatest impact on SINR performance of a direct form processor.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1999
- Accession Number
- ADA364396
Entities
People
- Scott D. Berger
Organizations
- Air Force Institute of Technology