Multiple-sensor cueing using a heuristic search
暂无分享,去创建一个
Modern military surveillance systems typically include a number of different, independently adjustable sensors distributed throughout an environment to be monitored. These sensors should be configured so that their integrated outputs provide the optimal combination of probability of target detection and probability of false alarm. While it is desirable to optimize this measure of system performance, it is also desirable to minimize the enemy's ability to detect these sensors. These are conflicting goals. Each sensor can typically monitor only a small part of the environment and can sample only a small number of target discriminants. Because there are only a limited number of sensors available, sensor placement and configuration are critical to system performance. A system may use passive sensors to cue active sensors, or use low-resolution sensors to cue high-resolution sensors. All available information (properties of the sensors, properties of the environment being monitored, and known target locations and properties) should be used to determine an optimal sensor configuration. We call this the sensor cueing problem. This paper describes an algorithm that uses a heuristic search to efficiently solve the sensor cueing problem. The algorithm assumes that sensor locations are fixed in advance, but that other attributes (pointing direction, field of view, focus, etc.) may be adjusted to maximize system performance. Expected system performance is based on how well the group of sensors covers regions of the environment known to contain targets, as well as regions of the environment where targets are expected to appear. The algorithm's performance and possible extensions are described.
[1] Jesfis Peral,et al. Heuristics -- intelligent search strategies for computer problem solving , 1984 .
[2] Nils J. Nilsson,et al. Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Ren C. Luo,et al. Multisensor integration and fusion in intelligent systems , 1989, IEEE Trans. Syst. Man Cybern..