All-Weather Sense and Avoid (SAA) Radar Clutter Modeling and Control

Abstract

The background of this thesis is related to the enhancement and optimization of the Pulsed-Doppler Radar sensor for the need of Detect and Avoid (DAA), or Sense and Avoid (SAA), for both weather and air-traffic (collision aircraft) detection and monitoring. Such radars are used in both manned and unmanned aircraft for the situation awareness of pilot navigation operations. The particular focus of this study is to develop a simulation model that is based on MATLAB's phased array toolbox and use that simulation model to predict the performance of an end-to-end radar signal processing chain for all-weather, multi-mission DAA. To achieve this goal, we developed an airborne system model based on MATLAB toolboxes, NASA’s airborne radar flight test data, and NEXRAD radar data. The measured data from airborne and ground-based radars are used as the “truth field” for the weather. During the modeling and verification process, we primarily investigated the impact of ground or surface clutters on the radar outputs and results, which include the testing of the constant-gamma model using actual measured radar data and improved system and sensor modeling based on the clutter geometry. Evaluation of various moving target indication (MTI) techniques were tested with the simulation model.