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This paper presents a fusion process developed for the future armoured vehicle system (FAVS) technical demonstration (TD) project. One of the project objectives was to develop, optimize and demonstrate a multi-sensor suite mounted on an army vehicle to detect and identify targets while the platform was moving. The sensors consisted of a cooled infrared camera, millimetre-wave radar and a defensive...
The question tackled here is the time allocation of radars in a multitarget environment. At a given time radars can only observe a limited part of the space; it is therefore necessary to move their axis with respect to time, in order to be able to explore the overall space facing them. Such sensors are used to detect, to locate and to identify targets which are in their surrounding aerial space. In...
We seek to establish a quality metric for sensor fused video based on the performance of a multisensor system that actively tracks multiple surface targets over an extended field of regard Such a system must, in real-time, fuse multisensor/spectral imagery, detect targets reliably, track the targets for extended time periods as they move, stop, approach, cross, hide/emerge, over an extended field...
We describe data fusion technology relevant to two applications of potential benefit to the Canadian army. The first application is a local situational awareness system (LSAS) while the second is a versatile surveillance platform. The LSAS improves an armored vehicle crew's ability to recognize and locate threats and hazards without leaving the relative safety of their vehicle. It is designed primarily...
In this paper we present a comparison of three AFE tools used in the context of ship and vehicle detection based on high resolution data. The three tools (Genie Pro - Los Alamos National Laboratory, Feature Analyst - Visual Learning Systems and eCognition - Definiens AG) were chosen because they were defined as promising and were to be analyzed by NGA in the framework of the STAR program. The comparison...
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