High-precision pedestrian foot navigation algorithm based on multi-information fusion compensation

Abstract

The invention discloses a high-precision pedestrian foot navigation algorithm based on multi-information fusion compensation. The high-precision pedestrian foot navigation algorithm is characterized in that the original measuring data of a gyroscope and an accelerometer is collected in real time, the error compensation of the initial gyroscope is zero, the error compensation of the accelerometer is also zero, and a strapdown inertial navigation calculating algorithm is used to perform strapdown calculation; on the basis above, a Kalman filter correction model is built to perform filter correction, state equation consistency is achieved while measurement equations are dynamically adjusted along with multi-dimensional measurement information, a corresponding algorithm is built under different multi-dimensional information detections, the measurement equation is transformed in real time, navigation positioning result errors and sensor errors are estimated and corrected, and the errors arereturned to the error compensation of the gyroscope and the error compensation of the accelerometer; a navigation positioning result which includes the position, speed and posture of a pedestrian isoutput. The high-precision pedestrian foot navigation algorithm has the advantages that a low-precision consumer-grade sensor chip and a magnetic sensor are used, the high-precision pedestrian positioning problem under an environment without a global navigation satellite system (GNSS) is solved, and the long-hour course divergence problem is solved.

Description

technical field [0001] The invention relates to a high-precision pedestrian foot navigation algorithm, in particular to a pedestrian high-precision foot navigation algorithm based on multi-information fusion compensation, which belongs to the technical field of pedestrian navigation. Background technique [0002] At present, research on pedestrian navigation technology is mainly divided into the following categories: wireless perception, pattern recognition, and inertial sensors. Among them, wireless sensing technology needs to deploy additional radio frequency equipment, including WIFI, UWB, etc., which has a narrow application range, easy to block signals, and high cost; while inertial sensors are independent, free from external interference, and low in cost, and are suitable for wide application. . However, the low-cost inertial sensor has a large error. If no compensation or other means are used to assist, it will cause errors above the meter level within a few seconds....

AI Technical Summary

Problems solved by technology

However, the low-cost inertial sensor has a large error. If there is no compensation or other means to assist, it will cause an error above the meter level within a few seconds.

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