Measurement method on the basis of multi-sensor date fusion

Abstract

The present invention discloses a measurement method on the basis of multi-sensor date fusion. The method provided by the invention comprises the following steps: when a sensor is used for measuring a parameter, the rejection of careless errors of acquired original data according to the Grubbs criterion is performed to minimize the influence on the fusion precision caused by the careless errors; local fusion of measurement data of the same observation object through adoption of the same sensor at different times through a batch estimation method is carried out to obtain local estimated values of relevant parameters of the observation object, and the measurement error of the sensor at this time is obtained through calculation; and weighting coefficients of different sensors are determined through measurement errors of the sensors obtained through the batch estimation, and weighted fusion of the obtained local estimated value of each sensor is performed to obtain final global estimated values of the parameters. The measurement method on the basis of multi-sensor date fusion is applicable to the practical engineering application, and weighting coefficients of data fusion are determined according to prior knowledge.

Description

technical field [0001] The invention belongs to the technical field of information processing, in particular to a measurement method based on multi-sensor data fusion. Background technique [0002] With the development of science and technology, the performance of sensors has been greatly improved, and various multi-sensor systems facing complex backgrounds have emerged in large numbers. Single-sensor signal processing or low-level multi-sensor data processing is a low-level imitation of the information processing process of the human brain, while multi-sensor information fusion is to maximize the acquisition of detected targets by effectively utilizing multi-sensor resources. and environmental information. [0003] Multi-sensor data fusion is a relatively precise definition, which can be summarized as: making full use of multi-sensor data resources in different time and space, analyzing, evaluating and correcting multi-sensor observation data obtained in time series under ...

AI Technical Summary

Problems solved by technology

[0004] With the continuous development of technology, in order to meet the needs of different measurement systems, people have done many researches on data fusion algorithms. Now commonly used algorithms include weighted average, Kalman filter, multi-Bayesian estimation, neural network, and fuzzy estimation. However, most of these algorithms are aimed at research and estimation under ideal conditions, and there are many different environmental factors to be considered in practical applications. The existing technology cannot meet the requirements of sensor measurement accuracy in practical engineering applications.

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