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An Adaptive Cooperative Navigation Filtering Method

A collaborative navigation and self-adaptive technology, applied in the direction of navigation computing tools, etc., can solve the problems of limiting the scope of application of AUV, not taking into account, etc., and achieve the effect of increasing the number of models, good modularity, and good post-correction

Active Publication Date: 2019-10-18
HARBIN ENG UNIV
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AI Technical Summary

Problems solved by technology

Due to the particularity of the underwater environment and acoustic-based positioning, the measurement noise covariance matrix required in the collaborative navigation filtering process is time-varying. Possible changes that limit the applicability of AUVs

Method used

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  • An Adaptive Cooperative Navigation Filtering Method
  • An Adaptive Cooperative Navigation Filtering Method
  • An Adaptive Cooperative Navigation Filtering Method

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Experimental program
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Embodiment

[0043] The specific operation is as follows:

[0044] Combine below figure 1 And embodiment, content of the present invention is described in further detail.

[0045] Step 1: Enter the interactive process

[0046] Such as figure 1 As shown, the interactive multi-model algorithm is a cyclic algorithm, and the state estimation is completed through four processes of input interaction process, model filtering, model probability update and output interaction process.

[0047] In the input interaction process, the mixed state is obtained through the predicted model probability for the first time, and the calculated model probability is replaced by the calculated model probability in the next cycle.

[0048] Cooperative navigation is estimated from the AUV interactive hybrid state and the covariance is:

[0049]

[0050]

[0051] In the formula is the state estimation of the jth filter at time k-1; P j (k-1) is Corresponding covariance matrix; P 0i (k-1) is the state ...

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Abstract

The invention relates to the field of collaborative navigation algorithms, in particular to a self-adaptive collaborative navigation and filtering method used under unknown measurement noise. The method includes the steps of interaction process input, model filtering, model probability update and interaction output. Compared with a traditional collaborative navigation and filtering method, under the condition of unknown noise environments, the method can effectively reduce the problem of precision reduction caused by overlarge noise preset deviation. The method has a very good modular characteristic, people can increase the number of models and can also freely select filters with various characteristics, and accordingly the method has very good later correction performance.

Description

technical field [0001] The invention relates to the field of collaborative navigation algorithms, in particular to an adaptive cooperative navigation filtering method for unknown measurement noise. Background technique [0002] Autonomous underwater vehicles (AUVs) have a wide range of applications in both civilian and military applications. As the exploration of the ocean deepens, the mission of AUVs becomes more and more complex and diverse. If only a single AUV is used to achieve these functions, not only will the cost increase a lot, but the reliability will also increase. However, the collaborative system composed of multiple underwater AUVs has the characteristics of spatial distribution, functional distribution, and redundancy. However, regardless of single AUV or multi-AUV system and what tasks it performs, the quality of the navigation system directly affects the performance of the system. As a new navigation and positioning method, cooperative navigation and posi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20
Inventor 徐博卢少然白金磊王星姜涛但剑晖
Owner HARBIN ENG UNIV
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