Non-Gaussian Noise Models and Coherent Detection of Radar Targets
Abstract
The problem of detecting radar targets against a background of coherent, correlated non-Gaussian clutter is studied with a two-step procedure. In the first step, the structure of the multidimensional probability density function (PDF) describing the statistical properties of the clutter is derived. The starting point for this derivation is the basic scattering problem, and the statistics are determined from an extension of the Central Limit Theorem that is formulated and proved herein. Some basic mathematical properties of the resulting distributions are studied, and the problem of fitting data to such distributions is also discussed. The end product of the first step is a multidimensional PDF, which is then used in step 2 in the derivation of both the optimal and a suboptimal detection structure for detecting radar targets in this type of clutter. Performance results for the new detection processor are also given. Detectors, Radar, Non-Gaussian noise, Clutter.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 05, 1992
- Accession Number
- ADA258049
Entities
People
- Karl R. Gerlach
- Kevin J. Sangston
Organizations
- United States Naval Research Laboratory