Information filter for decentralized data fusion and sensor management

摘要

Previous work in data fusion has seen the development of a range of architectures for multisensor data fusion systems, from fully centralized through distributed to fully decentralized. This paper presents some results obtained from an implementation of a multitarget tracking system built around a fully decentralized Kalman filter (DKF). Explicit use is made of the information available locally to a sensor to control its pointing and target detection. The tracking system integrates an essentially range- only sensor with a bearing-only sensor, and the performance of the system is described in terms of both its ability to produce good tracks and its requirement for communications bandwidth. The sensors run asynchronously from each other, and also exhibit asynchronous first detection. Of particular importance in the way the individual sensors can use the information in the global picture to make decisions about which targets to observe. In the demonstration system, simple sensor management is achieved by fixating on the nearest (interesting) target. First we give some background and describe the decentralized data fusion test bed. Then we consider the realization of the decentralized information filter in terms of the ultrasonic and IR sensors used in our demonstration system. Finally, we draw some conclusions about system performance, and indicate some possible future work.