| Heterogeneous multisensor systems have been widely used in a variety of military and civilian applications. While the majority of research in multisensor systems is dedicated to military applications, other applications include robot navigation, autonomous vehicles and paramilitary operations. In general, single sensor systems only provide partial information on the state of the environment while multisensor systems rely on data fusion techniques to combine related data from multiple similar and/or dissimilar sensors. The goal of a multisensor system is to provide a synergistic effect that enhances the quality and availability of information about the state of the world over that which would be acquired solely from one sensor.; Sensor management can be described as a system or process that provides automatic or semiautomatic control of a suite of sensors or measurement devices. Previous approaches to sensor management all appear to suffer from the mixing of sensor physical requirements with information needs. The result has been ad hoc point solutions that treat the problem as a single optimization task with a performance measure as a weighted sum of diverse, noncommensurate measures. This dissertation presents a new mathematical representation of the multisensor system to capture the sensor management process. Based on this representation, an original hierarchical sensor management model is developed that partitions the system into its constituent processes. These include the sensors themselves, the targets, the Fusion Space, and the Information Space. The Information Space is further partitioned into the Mission Manager, the Information Instantiator, and the Sensor Scheduler.; Additionally, this dissertation describes a new approach which uses partially ordered sets to construct a goal-lattice that converts qualitative mission goals to quantitative values for different sensor actions. This approach superimposes value apportionment on the lattice in order to provide a mathematically quantitative and traceable measure of importance (weights) that a sensor manager can use to optimize trade-offs among competing management functions to meet the mission goals. Another advantage is that these weights can vary as a function of time or phase of a mission thus providing a mathematically based methodology to modify the preferences in real-time based on changes in information produced by data fusion, a human operator, or both. |
