scholarly journals An Adaptive Initial Alignment Algorithm Based on Variance Component Estimation for a Strapdown Inertial Navigation System for AUV

Symmetry ◽  
2017 ◽  
Vol 9 (8) ◽  
pp. 129 ◽  
Author(s):  
Qianhui Dong ◽  
Yibing Li ◽  
Qian Sun ◽  
Ya Zhang
Keyword(s):  
Navigation System ◽  
Variance Component ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Alignment Algorithm ◽  
Variance Component Estimation ◽  
Initial Alignment ◽  
Component Estimation ◽  
Strapdown Inertial Navigation

scholarly journals An Improved Strapdown Inertial Navigation System Initial Alignment Algorithm for Unmanned Vehicles

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3297 ◽  
Author(s):  
Ya Zhang ◽  
Fei Yu ◽  
Wei Gao ◽  
Yanyan Wang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Unmanned Vehicles ◽  
Frequency Noise ◽  
Alignment Algorithm ◽  
Initial Alignment ◽  
System Nonlinearity ◽  
Strapdown Inertial Navigation

Along with the development of computer technology and informatization, the unmanned vehicle has become an important equipment in military, civil and some other fields. The navigation system is the basis and core of realizing the autonomous control and completing the task for unmanned vehicles, and the Strapdown Inertial Navigation System (SINS) is the preferred due to its autonomy and independence. The initial alignment technique is the premise and the foundation of the SINS, whose performance is susceptible to system nonlinearity and uncertainty. To improving system performance for SINS, an improved initial alignment algorithm is proposed in this manuscript. In the procedure of this presented initial alignment algorithm, the original signal of inertial sensors is denoised by utilizing the improved signal denoising method based on the Empirical Mode Decomposition (EMD) and the Extreme Learning Machine (ELM) firstly to suppress the high-frequency noise on coarse alignment. Afterwards, the accuracy and reliability of initial alignment is further enhanced by utilizing an improved Robust Huber Cubarure Kalman Filer (RHCKF) method to minimize the influence of system nonlinearity and uncertainty on the fine alignment. In addition, real tests are used to verify the availability and superiority of this proposed initial alignment algorithm.

Self-Alignment Algorithm for Strapdown Inertial Navigation System under Strong Flurry Interference

2013 ◽  
Vol 347-350 ◽  
pp. 3667-3671 ◽  
Author(s):  
Yue Gang Wang ◽  
Jia Sheng Yang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
The Body ◽  
Alignment Algorithm ◽  
Result Show ◽  
Linear Movement ◽  
Initial Attitude ◽  
Strapdown Inertial Navigation

For the strong flurry interrupting, the body will suffer large swaying motion when it is in erecting state ,the output of its strapdown inertial navigation system (SINS) will be disturbed for the high gravitational. center of IMU, the conventional methods are difficult to achieve alignment rapidly and accurately, to solve this problem, an anti-interference self-alignment algorithm for SINS which under strong flurry is presented, which utilizes the continuous attitude update in inertial reference frame to record the attitude changes caused by sway interrupt to remove the angular interrupting, and uses the characteristics that the body exists a shake center whose speed is zero to remove the linear movement interrupting by acquiring the equivalent specific force of the shake center, and then uses the estimation of the initial attitude to determinate the attitude of the body. The simulation result show that the presented algorithm can accomplish alignment quickly even in the presence of strong flurry interference without coarse alignment phase.

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