Performance evaluation of a remote-sensing chemical identification algorithm

The remote detection and identification of gaseous chemical plumes is an important problem with many military and commercial applications. In this paper, we consider the performance of a chemical identification system that consists of a detector bank and a model averaging algorithm. Using standard detection metrics and an identification metric, we compare the two algorithms and show that cascading the two algorithms can lead to superior performance.