A Vision Aided Initial Alignment Method of Strapdown Inertial Navigation Systems in Polar Regions

Abstract

The failure of the traditional initial alignment algorithm for the strapdown inertial navigation system (SINS) in high latitude is a significant challenge due to the rapid convergence of polar longitude. This paper presents a novel vision aided initial alignment method for the SINS of autonomous underwater vehicles (AUV) in polar regions. In this paper, we redesign the initial alignment model by combining inertial navigation mechanization equations in a transverse coordinate system (TCS) and visual measurement information obtained from a camera fixed on the vehicle. The observability of the proposed method is analyzed under different swing models, while the extended Kalman filter is chosen as an information fusion algorithm. Simulation results show that: the proposed method can improve the accuracy of the initial alignment for SINS in polar regions, and the deviation angle has a similar estimation accuracy in the case of uniaxial, biaxial, and triaxial swing modes, which is consistent with the results of the observable analysis.

MEMS strapdown inertial attitude measurement system using rotational modulation technology

“…Assume that the time of both rotations is T. It can be inferred that the complete reciprocating rotation cycle is T 0 = 2T. Eq (5) shows the attitude error caused by gyroscopic constant bias during the complete cycle.…”

“…This is because the MEMS inertial navigation system only uses the accelerometer and gyroscope data provided by IMU for attitude calculation. Long time observation will lead to error accumulation, which will eventually affect the results and generate divergent inertial solutions [ 3 – 5 ]. Therefore, the inertial sensor error must be compensated to improve the performance of MEMS inertial navigation.…”

A novel framework of building operation algorithm for the block of technical diagnostics of aircraft’s automatic control system

“…Thus, the diagnostic block, in addition to the task of finding failures and determining the location, type, and form of failures, must also calculate and fix the failures [5]- [8]. If the failure is identified and corrected, the system is stable before failure [9]- [11]. To stabilise before failure, it is necessary to determine in the following order: i) identify abnormal phenomena of system instability; ii) analyze and identify unusual phenomena; and iii) restore the ability to work according to the requirements of the control object.…”

Methods to Estimate Positioning and Time Offset with Underwater Acoustic Positioning System

“…The shortcomings mentioned above limit the GNSS application used for AUV in the deep sea environment. At present, traditional underwater navigation could be divided into five types, namely INS [2,3], UAPS [4,5], the underwater visual navigation system (UVNS) [6], the geophysical navigation system (GNS) [7][8][9], and the underwater integrated navigation system [10][11][12].…”