CKF filtering-based vehicle dynamic model auxiliary inertial navigation combined navigation method

Abstract

The invention discloses a CKF filtering-based vehicle dynamic model auxiliary inertial navigation combined navigation method. The CKF filtering-based vehicle dynamic model auxiliary inertial navigation combined navigation method comprises the following steps: calculating posture, speed and position of a vehicle according to angle increment and specific force output by a micro-inertia device and by an inertial navigation numerical value updating algorithm; establishing a three-degree-of-freedom vehicle dynamic model, and calculating the speed of a carrier by taking a steering wheel angle and a longitudinal force as control input quantity and by a fourth order Ronge-Kutta method in real time; designing a CKF filter by taking an inertial navigation equation as a state equation and speed difference between a dynamical model and inertial navigation calculation to perform state estimation on a combined navigation system; performing output correction on strapdown inertial navigation calculation result by the position the speed and the posture error obtained by CKF estimation, and performing feedback correction on the inertial navigation through peg-top and adding error. The method aims at the problems that the inertial navigation error is accumulated along with time and navigation precision cannot be maintained for a long time, and the accuracy and the reliability of a vehicle navigation system can be improved.

Description

technical field [0001] The invention belongs to the technical field of vehicle integrated navigation, and in particular relates to a vehicle dynamics model-assisted inertial navigation integrated navigation method based on CKF filtering. Background technique [0002] With the rapid development of micro-inertial devices, an inertial navigation system (INS) can meet the needs of low-cost and miniaturized vehicle navigation systems. However, INS will produce errors accumulated over time and cannot maintain navigation accuracy for a long time. Therefore, it is necessary to introduce information measured by auxiliary sensors and INS to form an integrated navigation system to work. The most common of these is the inertial navigation / satellite integrated navigation system. However, in practical applications, the satellite navigation system (Global navigation satellite system, GNSS) has poor autonomy, is susceptible to interference, and GNSS signals are easily blocked. In the GNSS ...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a vehicle dynamics model-assisted inertial navigation integrated navigation method based on CKF filtering, which can improve the accuracy of the vehicle navigation system for the problem that the inertial navigation error accumulates over time and cannot maintain navigation accuracy for a long time and reliability

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