Distributed filtering device for MIMU and GPS combined navigation system

Abstract

The invention discloses a distributed filtering device for a MIMU and GPS combined navigation system, which comprises 5 difference comparison units and 5 filters. The difference comparison units and the filters respectively filter the course and speed information as measurement input and outputted by the MIMU and GPS, and transmit the information after filtering back to the MIMU for rectification; finally, the rectified speed, attitude and position information is used as the final output of the MIMU / GPS combined navigation system. The filtering device can reduce the calculated quantity of the system, has high error tolerance capacity, also compensates through real-time gyrodrift estimation, and accordingly improves the accuracy of the output information of the MIMU / GPS combined navigation system.

Description

technical field [0001] The present invention relates to a filtering device, more particularly, to a distributed filtering device suitable for a micro-inertial and global positioning integrated navigation system (MIMU / GPS). Background technique [0002] Micro-inertial measurement system (MIMU) is an inertial navigation system composed of micro-mechanical gyroscopes, micro-mechanical accelerometers and integrated circuits. It has the advantages of complete autonomy, no external interference, high short-term accuracy and fast data update, and low cost. Small size, light weight, low power consumption. The disadvantage is that the accuracy is low, the system error accumulates over time, and it is difficult to be competent for long-term navigation tasks. [0003] The Global Positioning System (GPS) is a satellite navigation system that has the advantages of high positioning accuracy and long-term stability. The disadvantages are that the autonomy is poor, the signal is easy to l...

AI Technical Summary

Problems solved by technology

The disadvantage is that the accuracy is low, the system error accumulates over time, and it is difficult to be competent for long-term navigation tasks

The disadvantages are that the autonomy is poor, the signal is easy to lose lock, and the sampling rate is low, so it cannot be applied in a high dynamic and high interference environment

However, the MM method requires multiple models to run in parallel, and the amount of calculation is large. In the low-cost integrated navigation system, the application of the MM method is hindered by the limitation of hardware processing capabilities.

[0007] In addition, the accuracy of micromachined gyroscopes and micromachined accelerometers is low, and more accurate modeling with high-order Kalman filters will produce large model errors. At the same time, the increase in the order of the model leads to a cubic increase in the amount of calculation , which limits engineering applications

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