A distributed multi-sensor intelligent information fusion method

Abstract

The invention is a distributed multi-sensor intelligent information fusion method. It includes the following steps: 1) directly collect signals from distributed ultrasonic receivers to the control center, and use distributed Kalman filter for filtering processing; 2) after distributed signal filtering processing, time and space alignment and track correlation, make Unify the sampling frequency, each measurement system has the current measurement data at each sampling time, and unify the space and time coordinate system; 3) Through the trajectory correlation method, the deviation between the prediction point and the observation point is used as the error evaluation standard; 4) The fusion method of optimal fusion estimation is used to fit all relevant tracks into a new track. The invention discloses a distributed multi-sensor intelligent information fusion method that realizes optimal fusion of N estimated values ​​according to the minimum variance principle, and effectively realizes high-precision indoor positioning of ultrasonic waves.

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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