Modeling inertial sensors errors using Allan variance.

摘要

It is well known that Inertial Navigation Systems (INS) can provide high accuracy information on the position, velocity, and attitude over a short time period. However, their accuracy degrades rapidly with time. The requirements for accurate estimation of navigation information necessitate the modeling of the sensors' noise components.; Allan variance is a method of representing root mean square (RMS) random drift error as a function of average time. It is simple to compute and relatively simple to interpret and understand. Allan variance method can be used to determine the character of the underlying random processes that give rise to the data noise. This technique can be used to characterize various types of noise terms in the inertial sensor data by performing certain operations on the entire length of data.; In this thesis, the Allan variance technique is used in noise analysis of different grade Inertial Measurement Units (IMU), which include: (1) Navigation grade IMU: The Honeywell Commercial IMU (CIMU); (2) Tactical grade IMU: The Honeywell HG1700; and (3) Consumer grade MEMS based IMU: The System Donner MotionPak II-3g. (Abstract shortened by UMI.)