Vector search iterative matching method based on inertia/gravity matching integrated navigation

Abstract

The invention relates to a vector search iterative matching method based on inertia / gravity matching integrated navigation, the vector search iterative matching method is characterized by comprising the following steps of estimating a matched search scope and a current matching performance by an inertial navigation output location; taking a correlative extremal function as a target search to determine an optimal matching transformation; performing constant weighted iteration on the result of matching position to obtain an optimal matching position finally. The vector search iterative matching method provided by the invention serves as a hub for connecting component parts of a gravity matching system; a calculating process from gravity measurement information in real time to a carrier position can be completed; an inertial navigation error range is taken as a matching scope; a global optimum solution can be obtained, and divergence can be restrained; the requirement of an initial position error is low; the error and divergence problems caused by database linear processing of gravity data can be effectively avoided; the efficiency and the property of an algorithm are improved, and the vector search iterative matching method has a strong robustness on an gravity measurement random error and an inertial navigation system variable error.

Description

technical field [0001] The invention belongs to the technical field of inertial / gravity combined navigation systems, in particular to a vector search iterative matching method based on inertial / gravity matching combined navigation. Background technique [0002] The inertial / gravity matching integrated navigation system is an important development direction of contemporary integrated navigation. It uses a passive method to effectively suppress the accumulated error of the inertial navigation system, and has important applications in the fields of navigation, aerospace and precision guidance. The gravity reference library, gravity sensor and gravity matching positioning algorithm are the three key technologies of the combined system, among which the gravity matching algorithm is the core calculation module of the gravity matching navigation, and its algorithm performance directly affects the accuracy and robustness of the gravity matching navigation system . [0003] The exis...

AI Technical Summary

Problems solved by technology

Commonly used matching algorithms include batch correlation matching algorithm, closest point iterative matching algorithm and Kalman filter matching algorithm. The batch correlation matching positioning algorithm has a large amount of calculation and is sensitive to the deformation error of the reference trajectory. The closest point matching algorithm is easy to converge to the local minimum. Excellent solution, when the initial error is large, the performance is poor, the various error statistical models required by the Kalman filter algorithm are not easy to obtain, and the linearization of the gravity field will cause the filter to diverge

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