Mixed interactive multi-model filtering method

Abstract

The invention discloses a mixed interactive multi-model filtering method. The method comprises the following steps: firstly, building a system model and an observation model of an application object,building a total model set according to a change condition of noise statistic characteristics of external information, and describing current noise characteristics by adopting the adjacent three models; storing a robust filter real-time noise variance matrix in a historical sequence by adopting a sliding window, and adaptively selecting a proper model according to the smoothed noise statistic characteristics; setting an initial probability of each model and a mixed initial state and a covariance matrix of each filter, and according to the system model and the observation model, performing state estimation and covariance matrix updating processes, and performing model updating by adopting a Bayesian hypothesis testing method; and performing an output interactive process according to a weight, and outputting a final filtering result. By taking an inertia / Doppler combined navigation system as an example, the interference of noise sudden change type errors and outliers existing in Dopplerspeed measurement information can be effectively relieved.

Description

technical field [0001] The invention is a hybrid interactive multi-model filtering method, belongs to multi-sensor information fusion technology, and is especially suitable for the field of underwater INS / DVL (inertial navigation / Doppler) combined navigation. Background technique [0002] With the development of science and technology, relying on the information provided by a single sensor can no longer meet the needs of control, and the information fusion technology of multi-sensor systems for complex application backgrounds has emerged as the times require, and has penetrated into every corner of the modern information society. more and more prominent. Multi-sensor information fusion technology is the use of computer technology to automatically analyze and synthesize information and data from multiple sensors or sources under certain criteria to complete the required decision-making and estimation. Since the data obtained by each scattered sensor will inevitably be restri...

AI Technical Summary

Problems solved by technology

A single observation variance matrix cannot be adapted to the integration system for long voyages

When navigating in uncharted waters, it is difficult to get an empirical value for the variance matrix of the measurement noise

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