Adaptive spatio-temporal CFAR and multiple-hypothesis tracking system

摘要

This paper describes a self organising spatio-temporal radar CFAR system that uses multipleintelligent software agents to detect and adapt the processing to features in the environment.By combining both temporal and spatial data gathering sufficient samples can be collected toallow both the first and second order moments of the clutter distribution to be approximatedfor each cell. By gathering higher order statistics to a useful accuracy, more stablethresholds may be produced.