MIMU and GPS combined pedestrian navigation method based on augmented lagrangian condition

Abstract

The invention provides an MIMU and GPS combined pedestrian navigation method based on augmented lagrangian condition. A pedestrian navigation system is provided with a radio-frequency signal receiver and two MIMUs, wherein the radio-frequency signal receiver is fixed on the shoulder of a pedestrian, and the two MIMUs are respectively fixed on the tip of a toe and the heel of a foot, so that the system data can be acquired in real time; navigation calculation is carried out on the two MIMUs respectively, so that inertial navigation pedestrian position, speed and attitude information can be obtained; a radio-frequency signal is used for locating, so that the pedestrian position information can be obtained by the receiver; zero-speed correction is carried out on the two MIMUs respectively; a nonlinear equality constraint equation and a nonlinear inequality constraint equation are established; the constraint equations are combined with a kalman filter, and the state variable of the system is corrected by an augmented lagrangian equation, so that the problem of the location accuracy of the weak radio-frequency signal is lower can be solved. In the bad closed indoor navigation environment, the utilizability of the weak radio-frequency signal can be fully improved by the combined pedestrian navigation method.

Description

technical field [0001] The invention relates to an information fusion method of a pedestrian navigation system, in particular to an information fusion method based on augmented Lagrangian conditions. Background technique [0002] When the pedestrian navigation autonomous positioning device based on MIMU (Micro Inertial Measurement Unit) inertial calculation is working, the error divergence is serious when the micro-inertial device is working. The error of the micro-inertial device cannot be effectively compensated, the position error will diverge with the trend of the cube of time, and the system will eventually lose its navigation function. Therefore, the biggest difficulty in applying the micro-inertial system to pedestrian navigation and positioning lies in the effective correction of errors. [0003] From the current point of view, in order to reduce the navigation error of the micro-inertial system, the vast majority of products with pedestrian navigation and positioni...

AI Technical Summary

Problems solved by technology

However, they all have shortcomings such as poor dynamic performance and non-autonomousness, and are easily affected by objective factors. In complex surrounding environments, signal loss will occur, and the function of providing positioning information will fail.

[0004] In terms of filtering, the filtering methods currently used in most products with pedestrian navigation and positioning functions are not ideal for processing constraints, resulting in certain errors in information fusion, and the accuracy of navigation results is not high.

[0005] Generally speaking, the existing indoor pedestrian integrated navigation system has poor stability, the filtering effect is not ideal, and it is difficult to meet the requirements of accurate and reliable pedestrian navigation.

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