Enhanced Radar Detection Based on a Weather-Aware Constant False Alarm Rate Algorithm

Abstract

The multifunction phased array radar (MPAR) program was created by organizations including the Federal Aviation Administration (FAA) and the National Oceanic and Atmospheric Administration (NOAA) in an attempt to reduce overall cost by combining the missions of multiple agencies. Required capabilities for this project include detection of both civilian point targets and weather. One benefit of a combined radar for both agencies is the potential to improve detection within a storm. In detection for a point target, the presence of weather is considered clutter. The presence of strong weather clutter limits the abilities of traditional detection algorithms to detect weaker targets, and causes an increase in false alarms. The weather-aware constant false alarm rate (Wx-CFAR) algorithm is proposed as a mitigation path for detection in weather clutter. This algorithm combines the use of traditional constant false alarm rate (CFAR) techniques with additional variables calculated from weather. It uses a decision tree in order to determine if there is clear air or weather clutter. This algorithm is aimed at improving detection within a storm, and lowering the number of false alarms due to increased clutter. The algorithm was demonstrated on single polarization data which was collected using Horus with light precipitation and multiple aircraft present throughout. The results show a decrease in false alarms while maintaining an improved number of detections. The algorithm presented limitations when a point target had a similar radial velocity to the surrounding clutter and when a point target was located along a clutter edge.