Improved IIR tracking by fusion of centroid estimation processing with IMM filter

Imaging Infrared seeker(IIR) is a passive system which works on the reflections from the ambience and tries to deduce intelligible information regarding the targets of interest. Passive systems have complex processing schemes because of the unavailability of active reference signals to synchronize the processing. All the information has to be derived from the raw data obtained using thermal gradients. Manual intervention in these systems is inevitable to provide the initial conditions for the processing to start, unlike active systems where the system automatically configures or maps the surrounding by transmitting a signal. Centroid tracking and image correlation based tracking have been used for IIR tracking extensively in literature. Centroid tracking is highly sensitive to background data and initial tracking window size selected whereas correlation tracking requires a reference template for matching the target parameters which is usually not available up front. Both the techniques have high track loss rate if the background is cluttered. In this work we have proposed a novel infrared tracking technique for IIR seekers by fusing centroid processing with Interacting Multiple Model(IMM) filtering to reduce track loss and improve tracking efficiency.