Dual Kalman filter navigation device and method based on mems sensor and vlc positioning fusion

Abstract

The invention discloses a fused dual-Kalman filter navigation device based on an MEMS sensor and VLC positioning, and a navigation method. The navigation device comprises an MEMS sensor, an inertial navigation system (INS) module, a pedestrian dead reckoning (PDR) positioning module, a visible light communication (VLC) positioning module, an attitude extended Kalman filter (A-EKF), and a location extended Kalman filter (L-EKF); for the A-EKF, an error equation edited mechanically based on the INS is used as a system equation, an observation equation comprises update of observation of an accelerometer and a magnetometer, and attitude information is output to the VLC positioning module and the PDR positioning module so as to correct attitude impact; and for the L-EKF, position information of a two-dimensional plane is used as a system state vector, a pedestrian dead reckoned error equation is used as a system equation, and a VLC positioning result is an observation equation. The navigation device and navigation method solve a problem that VLC positioning is easy to be affected by device attitude and cannot keep positioning continuously if an optical signal is blocked, and eliminate the influence of attitude on VLC positioning.

Description

technical field [0001] The invention relates to a navigation and positioning device and method, in particular to a dual Kalman filter navigation device and method based on MEMS sensor and VLC positioning fusion. Background technique [0002] With the development and application of indoor positioning technology, the indoor positioning technology based on visible light communication is also rising rapidly and has received widespread attention. In an environment with sufficient indoor light sources, the optical signals modulated by the multiplexing protocol are detected by optical sensors and other equipment, and the signal data of different light sources can be separated through signal demodulation technology, so that the positioning target relative to each light source can be calculated in combination with environmental parameters. The distance or angle information, and finally through the positioning algorithm such as trilateral positioning can complete the target positionin...

AI Technical Summary

Problems solved by technology

[0004] However, there are some problems in these schemes: 1) Compared with single-sensor positioning, multi-sensor combined positioning algorithms are complex and costly; Medium stability is poor

3) In the scene where the signal is frequently blocked, the target position estimated by the positioning system only through the VLC data and the filter still has a large deviation from the actual position, and the VLC positioning results are discontinuous and not smooth; In the guidance and positioning technology, a Kalman filter is often used for noise processing and positioning. However, simultaneous positioning and attitude measurement through a single filter will cause attitude and position to affect each other.

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