On the modeling of the sensor fusion process for concealed weapons detection

Abstract

Summary form only given. Multisensor information fusion is one of the key technologies required to make significant advances in information processing and utilization in a distributed information environment. The data fusion process model proposed by the US Joint Directors of Laboratories (JDL) is accepted widely for military applications. There have been other models such as a three level model proposed by the Defense Evaluation and Research Agency (DERA) of the United Kingdom. There is an ongoing research and development program in the area of concealed weapons detection sponsored by Air Force Research Laboratory (AFRL) and National Institute of Justice (NIJ). The main objectives of this program are twofold: development of efficient sensors and signal processing technologies for the detection of civilian applications. Data collected by different sensors needs to be combined intelligently to enhance detection performance for concealed weapons. Toward this goal we have developed several novel image/signal processing algorithms. These include algorithms for image registration, image enhancement, image fusion, denoising, and object extraction. While great strides in the CWD program have been made, its relationship with the data fusion process models has not been investigated. The goal of this presentation is to examine this relationship.