<title>Improved acquisition capabilities of tactical IR seekers modeled with the infrared sensor performance analysis model</title>

Abstract

The Infrared Sensor Performance Analysis Model (ISPAM) is a statistical tool used to evaluate detection and acquisition performances of IR sensors and seekers. ISPAM has become increasingly important in providing performance estimates for developmental infrared seekers. While models with varying degrees of freedom offer higher fidelity, the ISPAM model offers quick-look performances with relative ease particularly important in the early design phase of programs. Recent modifications to the model have been necessary to improve the fidelity in areas such as complex background clutter, signal processing techniques, and target discrimination. The model now more accurately represents the performance of state-of-the-art tactical IR sensors and seekers. In support of these modifications, the effectiveness of signal processing for target discrimination in a variety of clutter backgrounds was recently evaluated. An algorithm testbed utilizing a generic tracker and various spatial and temporal processing techniques was used in a Monte Carlo fashion to determine acquisition ranges based on each technique. Results of one of these spatial processes, an anti-median filter, were compared to field test data generated using this same processing technique by a current developmental seeker and tracker. The acquisition ranges from this field test were compared with that of the ISPAM model. This paper will address the general methodology of ISPAM's performance prediction, and the effectiveness of signal processing on target acquisition and tracking determined from the algorithm testbed.