Outlier elimination method and device

Abstract

An embodiment of the invention provides an outlier elimination method and device. The method includes: acquiring target residual errors forming a residual error mean value of zero from a constructed Kalman filter residual error model in preset time; when the target residual errors accord with Gaussian distribution, acquiring a covariance matrix of the Kalman filter residual error model by the Kalman filter residual error model; taking a range formed by a first target value and a second target value as a target residual error range; taking the residual errors outside the target residual error range as outliers, and eliminating the outliers from the target residual error range. By adoption of the outlier elimination method, the problem of low reliability in fusion positioning can be solved.

Description

technical field [0001] The invention relates to the technical field of fusion positioning, in particular to a method and device for eliminating outliers. Background technique [0002] Traditional multi-source fusion positioning is based on information fusion technology, which fuses homogeneous or heterogeneous navigation information from different navigation sources according to existing corresponding fusion algorithms, such as robust Kalman filter algorithm, variance adaptive compensation method, Taking the variance adaptive compensation method as an example, in the Kalman filtering process, the covariance matrix of the model error is adaptively generated by using the observation information, so that the observation residual and the covariance matrix maintain a good consistency filtering, based on windowing The approximation method uses the previous step residual sequence to estimate the covariance matrix of the observation vector and the covariance matrix of the state erro...

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Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a method and d

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