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Gravity matching method based on self-adaptive robust untracked Kalman filtering

An unscented Kalman, self-adaptive robust technology, applied in the fields of navigation, guidance and control, can solve the problems of filter divergence and filter effect decline, and achieve the goal of improving robustness, reducing reliability and improving real-time performance Effect

Inactive Publication Date: 2018-08-24
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, due to the complex underwater environment and the existence of various interferences, the UKF algorithm has exposed certain shortcomings, that is, when the system process noise is highly uncertain and the observation noise is polluted, the filtering effect will decrease or even the filtering will diverge.

Method used

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  • Gravity matching method based on self-adaptive robust untracked Kalman filtering
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  • Gravity matching method based on self-adaptive robust untracked Kalman filtering

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Embodiment Construction

[0032] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0033] The invention provides a gravity matching method based on the adaptive robust unscented Kalman filter (ARUKF), which enhances the robustness of the system by introducing an adaptive factor and a robust Huber function, so that the system has no noise in the system process In the case of strong certainty and pollution of observation noise, high matching accuracy can still be obtained. The system block diagram is as follows: figure 1 shown.

[0034] The specific flow chart is as figure 2 shown, including the following steps:

[0035] Step 1, using the single-point matching algorithm based on recursive filtering, according to the characteristics of the gravity-assisted inertial navigation system, the inertial navigation error model is used as the state model of the filter, taking is the system state, where and δλ denote the latitude and longitude...

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Abstract

The invention discloses a gravity matching method based on robust self-adaptive untracked Kalman filtering. The method comprises the following process of building a system state equation and observation equation of a gravity assistance inertial navigation system filter on the basis of a single-point matching algorithm of the recurrence filtering; performing subtraction on the gravity abnormal reference value extracted from the current moment gravity abnormal pattern and the gravity abnormal practical measuring value to obtain the gravity abnormal difference value; on the basis of the improvedARUKF algorithm, performing filtering on the gravity abnormal difference by using the system state equation and the observation equation of the gravity assistance inertial navigation system filter soas to obtain the position and the variance of a submersible vehicle at the next moment; calculating the submersible vehicle position at each filtering sampling moment in the mode by using the positionand the variance of the submersible vehicle at the next moment; finally obtaining a complete matching track. The matching error can be effectively reduced; the navigation positioning precision of thegravity assistance inertial navigation system is improved.

Description

technical field [0001] The invention belongs to the technical field of navigation, guidance and control, and in particular relates to a gravity matching method based on an adaptive robust unscented Kalman filter. Background technique [0002] There are abundant resources in the ocean, which can provide strategic reserves for our country's resource security issues. Therefore, our country is paying more and more attention to the development of marine resources. The underwater vehicle technology is needed for both marine resource development and military comprehensive sea control, so the research on underwater vehicle navigation technology has very important strategic significance. Underwater navigation and positioning usually use inertial navigation, but the position error of inertial navigation will accumulate over time, and its positioning accuracy cannot meet the needs of long-term voyage, so it is necessary to use other navigation technologies to assist inertial navigation...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G01C21/16
CPCG01C21/165G01C21/20
Inventor 邓志红李成殷利建王博
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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