New infrared counter-countermeasure technique using an iterative self-organizing data analysis algorithm for the rosette scanning infrared seeker

Conventional infrared counter-countermeasure (IRCCM) techniques against fla res in the rosette scanning infrared seeker (RSIS) are based on the image-p rocessing algorithms such as the clustering and moment techniques. We analy ze the conventional IRCCM techniques and find that they can handle only a l imited number of clusters and may falsely recognize multiple targets as sin gle ones. To overcome these limitations, we propose a new IRCCM technique u sing an iterative self-organizing data analysis algorithm. The proposed IRC CM classifies image clusters and calculates their centroids regardless of t heir numbers, since the ISODATA technique can handle an arbitrary number of clusters. The nonlinearity of the rosette pattern causes the calculated ce ntroid of the target cluster to lean toward the middle of the pattern, i.e. , the optical axis. For a precise determination of the cluster centroid, we also propose a new calculation method based on a weight function. We simul ate the RSIS to evaluate the tracking performance in various situations. Th e simulation results prove that the proposed algorithm is very effective fo r IRCCM against flares. (C) 2000 Society of Photo-Optical Instrumentation E ngineers. [S0091-3286(00)00609-7].