Abstract
Two viewpoints are given: (1) initial alignment of strapdown inertial navigation system (SINS) can be fulfilled with a set of inertial sensor data; (2) estimation time for sensor errors can be shortened by repeated data fusion on the added backward-forward SINS resolution results and the external reference data. Based on the above viewpoints, aiming to estimate gyro bias in a shortened time, a rapid transfer alignment method, without any changes for Kalman filter, is introduced. In this method, inertial sensor data and reference data in one reference data update cycle are stored, and one backward and one forward SINS resolutions are executed. Meanwhile, data fusion is executed when the corresponding resolution ends. With the added backward-forward SINS resolution, in the above mentioned update cycle, the estimating operations for gyro bias are added twice, and the estimation time for it is shortened. In the ship swinging condition, with the “velocity plus yaw” matching, the effectiveness of this method is proved by the simulation.
Highlights
Transfer alignment is a rapid and effective initial alignment method, which is widely used for inertial navigation systems (INSs) in ships and planes
In 1989, a fast transfer alignment method was presented by Kain and Cloutier, in which alignment can be fulfilled in 10 s, and 1 mrad accuracy can be got with swinging movement and “velocity plus attitude” matching [1]
Aviation transfer alignment experiments on Apache helicopter and F-16 fighter were conducted by Shortelle and Graham, respectively [3,4,5], and the test results indicated that, when the update frequency was 12.5 Hz, the alignment time could be reduced to 5 s and the accuracy could reach 1 mrad, with “velocity plus attitude” matching and Wing-Rock tactical action
Summary
Transfer alignment is a rapid and effective initial alignment method, which is widely used for inertial navigation systems (INSs) in ships and planes. The rapidity of initial alignment was studied, while the estimation for inertial sensor errors was not taken into account or not given sufficient attention. With the repeatedly data fusion of the added backward-forward SINS resolution results and the external reference data, the estimation time for sensor error will be shortened. With the above two viewpoints, a rapid transfer alignment method based on the added backward-forward SINS resolution, without any changes to the Kalman filter, is designed in detail. In one reference data update cycle, with a normal resolution and data fusion, an added backward and an added forward resolutions, and their data fusions, the time consumed for gyro bias estimation is effectively shortened The effectiveness of this method is proved by simulation results.
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