Intelligent information fusion method of distributed multi-sensor

Abstract

The invention provides an intelligent information fusion method of a distributed multi-sensor. The intelligent information fusion method includes the following steps: (1) directly collecting signals from a distributed ultrasonic wave receiver, sending the signals to a control center, filtering processing the signals through distributed Kalman filtering, (2) after distributed signal filtering processing, aligning time, space and a related track, unifying sample frequency, namely each measure system is provided with current measured data of each sampling instant, and unifying a space and time coordinate system, (3) judging errors through a track correlation method with the deviation between a future point and an observing point as error judgment criteria, and (4) matching each relative track into a novel track through a fusion method of optimal fusion estimation. By means of the intelligent information fusion method of a distributed multi-sensor, the optimal fusion of numbers of estimated values is achieved through a minimum variance principle, and high-precision indoor positioning of supersonic waves is achieved effectively.

Description

technical field [0001] The invention is a distributed multi-sensor intelligent information fusion method, which belongs to the transformation technology of the distributed multi-sensor intelligent information fusion method. Background technique [0002] At present, multi-sensor data fusion is a current research hotspot, and scholars focus on problems in specific application fields (according to the type of problem). Scholars have proposed general functional models of multi-sensor information fusion systems from different perspectives: JDL model, waterfall model, intelligent model, Boyd model, Omnibus model, etc. However, the JDL model does not specify the information flow in the entire system; the new information after the waterfall model decision cannot be effectively used in other links; the intelligent cycle model does not consider the management requirements of the knowledge base and system data; the Boyd model and the intelligent cycle are respectively passed The "acti...

AI Technical Summary

Problems solved by technology

Although many problems have been solved, many new challenging problems arise with the development of multi-sensor data fusion technology and technology, such as data collaboration, data sharing, data fusion management, sensor uncertainty, data traffic, noise filtering , decision prediction techniques, dynamic system models, etc.

The main source of these new challenges is the low measurement accuracy of sensors and the interference of information sources by the external environment.

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