Two-Dimensional Processing for Radar Systems
Abstract
The model-based multichannel detection formulation is presented in the context of a two-dimensional (2-D) representation for space-time processes in general, and airborne surveillance phased array radar systems in particular. For the phased array space-time adaptive processing (STAP) problem, such a formulation requires 2-D parametric models for the channel output process under each one of two mutually exclusive hypotheses. Results presented herein demonstrate the applicability of 2-D model identification algorithms and methods to the phased array STAP problem. Specifically, it is demonstrated that 2-D model identification algorithms provide representative models for airborne surveillance phased array simulated data. Furthermore, the identified models can be used to design hypothesis filters for use in the innovations-based detection methodology resulting from the binary hypothesis testing formulation for moving target detection pioneered by Metford and Haykin (1985) and extended by Michels (1991) to the complex-valued multichannel case. This is a novel feature of the work reported herein.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1997
- Accession Number
- ADB232680
Entities
People
- Dennis W. Davis
- Jaime R. Roman
Organizations
- Rome Laboratory