An interactive multi-model combined navigation method

An interactive multi-model and integrated navigation technology, applied in the field of information fusion and interactive multi-model integrated navigation, can solve the problems of filter divergence, algorithm efficiency reduction, estimation noise error delay, etc.

Active Publication Date: 2021-05-11
SOUTHEAST UNIV
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Problems solved by technology

The interactive multi-model algorithm adopts the method of establishing a model set to cover the current model to eliminate model errors, but the filtering calculation of multiple models leads to a decrease in algorithm efficiency
Adaptive filtering improves filtering accuracy by estimating the noise model, but there are problems of filtering divergence and estimated noise error delay

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  • An interactive multi-model combined navigation method
  • An interactive multi-model combined navigation method
  • An interactive multi-model combined navigation method

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[0069] The technical solutions provided by the present invention will be described in detail below in conjunction with specific examples. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0070] An interactive multi-model combined navigation method provided by the present invention, the realization principle is as follows figure 1 As shown, the process mainly includes the following steps:

[0071] Step S1, establish the state equation according to the error model of the integrated navigation system:

[0072]

[0073] Z=HX+V

[0074] Among them, X is the state vector, F is the system matrix, W is the system noise vector, Z is the measurement vector, H is the measurement matrix, and V is the measurement noise vector.

[0075] Step S2, according to the joint measurement noise variance matrix R output by the previous state estimation k Create th...

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Abstract

The invention discloses an interactive multi-model integrated navigation method. Firstly, the state equation is established according to the error model of the integrated navigation system; Calculate the estimated initial state and estimated error variance matrix of each model state and estimated error variance matrix of the estimated output; then perform Sage-Husa adaptive filtering on the three established models and use Bayesian hypothesis testing method to update the model ; Finally, the output interaction process is performed according to the weight, and the final filtering result is output. The invention can estimate the measurement noise variance matrix in real time and effectively improve the positioning accuracy and efficiency of combined navigation.

Description

Technical field: [0001] The invention relates to an interactive multi-model combined navigation method, which belongs to the information fusion technology and is especially suitable for the combined navigation field. Background technique: [0002] As a kind of optimal control, Kalman filter technology is widely used in the field of integrated navigation. However, in the application process, the system model is required to be accurate, and the model error will reduce the filtering accuracy. In this context, interactive multi-model algorithms and adaptive filtering came into being. The interactive multi-model algorithm adopts the method of building a model set to cover the current model to eliminate model errors, but the filtering calculation of multiple models leads to a decrease in algorithm efficiency. Adaptive filtering improves filtering accuracy by estimating the noise model, but there are problems of filtering divergence and estimated noise error delay. In view of th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20G01C21/00G06F17/18
CPCG01C21/005G01C21/20G06F17/18
Inventor 徐晓苏侯岚华姚逸卿王迪潘绍华吴贤安仲帅
Owner SOUTHEAST UNIV
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