Quantitative Measurement Information Fusion Analysis And Method

Recent advances in distributed signal processing, sensing technology, micro elec-tro mechanical systems, wireless communications have enabled the development of the sensor networks. State measurement information with high fusion accuracy a sensor network, while each node in the network has limited energy supply and communication bandwidth.Therefore, the information fusion estimation problem based on the quan-tized information and under the limited bandwidth for high fusion accuracy in a sensor network.This paper is concerned with the information fusion estimation problem based on the state measurement information for a dynamic stochastic system in a sensor network.Firstly, proposed energy model and the quantization strategy of energy. In this paper, we ignore the energy consumption of observing between sensor nodes and the fusion center. The energy consumption of sending information from sensor nodes to the fusion center is considered. We adopt the quantization strategy in [11].Then, we consider the energy consumption and bandwidth and the error of the fusion center. Base on the energy model and the quantization strategy, we give two fusion strategies and their optimization models. Approximate solutions for two opti-mal bandwidth scheduling problems are given, where the tradeoff between the fusion accuracy or the bandwidth constraint and the energy consumption is considered.The filtering methods based on information fusion estimation in linear systems was presented for the filtering problem in linear dynamic system. One step predic-tive information and state measurement information are used to obtain the optimal fusion estimate of the system and the uniformity between the standard Kalman filter-ing was proved. Furthermore, a solution to the selection of initial filtering values was investigated.