Use of Spectral Anomaly Signature Feature to Improve ROC Performance

摘要

Track features help reduce the number of false associations during tracking. It is expected that the spectral signature vector from a target would tend to be consistent over short periods of time. Therefore, the spectral signature vector direction is a potential track feature candidate. The target's spectral signature and covariance are measured from the data at the output of the spatial-spectral match filter. The spectral vector feature is not independent from the local signal to clutter plus noise ratio (S(C+N)R), at the output of the anomaly detector which is often also used as a track feature. A correction term is introduced in this paper to account for the correlation between these two features. Results from field data collections using a multi-spectral Infra-Red Search and Track System (IRST) are summarized with ROC curves showing the performance improvements achieved by using the unit spectral vector as a feature for both moving and stationary targets.