Initial Alignment Algorithm for Platform Inertial Navigation System Based on Fuzzy Kalman Filter

2018 ◽  
Author(s):  
Shenhang Wang ◽  
Qi Xu ◽  
Mengyu Liu ◽  
Yang Tang ◽  
Ruishi Lin
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Alignment Algorithm ◽  
Initial Alignment

A fast alignment of marine strapdown inertial navigation system based on adaptive unscented Kalman Filter

2020 ◽  
pp. 014233122093429 ◽  
Author(s):  
Hossein Rahimi ◽  
Amir Ali Nikkhah ◽  
Kaveh Hooshmandi
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Initial Alignment ◽  
External Perturbations ◽  
Adaptive Unscented Kalman Filter ◽  
Strapdown Inertial Navigation

This study has presented an efficient adaptive unscented Kalman filter (AUKF) with the new measurement model for the strapdown inertial navigation system (SINS) to improve the initial alignment under the marine mooring conditions. Conventional methods of the accurate alignment in the ship’s SINS usually fail to succeed within an acceptable period of time due to the components of external perturbations caused by the movement of sea waves and wind waves. To speed up convergence, AUKF takes into account the impact of the dynamic acceleration on the filter and its gain adaptively tuned by considering the dynamic scale sensed by accelerometers. This approach considerably improved the corrections of the current residual error on the SINS and decreased the influence due to the external perturbations caused by the ship’s movement. Initial alignment algorithm based on AUKF is designed for large misalignment angles and verified by experimental data. The experimental test results show that the proposed algorithm enhanced the convergence speed of SINS initial alignment compared with some state-of-the-art existing approaches.

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.

Kalman Filter Design for Initial Precision Alignment of a Strapdown Inertial Navigation System on a Rocking Base

2014 ◽  
Vol 68 (1) ◽  
pp. 184-195 ◽  
Author(s):  
Hanzhou Li ◽  
Quan Pan ◽  
Xiaoxu Wang ◽  
Xiangjun Jiang ◽  
Lin Deng
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Filter Design ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Alignment Algorithm ◽  
Attitude Tracking ◽  
Alignment Process ◽  
Strapdown Inertial Navigation

In this paper, a conventional Strapdown Inertial Navigation System (SINS) alignment method on a disturbed base is analysed. A novel method with an attitude tracking idea is proposed for the rocking base alignment. It is considered in this method that the alignment algorithm should track the rocking base attitude real changes in the alignment process, but not excessively restrain disturbance. According to this idea, a rapid alignment algorithm is devised for the rocking base. In the algorithm, coarse alignment is carried out within 30 s in the inertial frame with alignment precision less than 2°, which meets Kalman filter linearization conditions well. Then a Kalman filter with ten state vectors and four measurement vectors is applied for the fine alignment to improve the capability of the algorithm in tracking the vehicle attitude. A turntable rotation experiment is carried out to validate the capability of the fine algorithm in tracing the large magnitude change during alignment. It is shown that the repeated alignment precision is about 0·04° by the alignment experiment on a rocking vehicle, with alignment time of 180 s. The Laser Strapdown Inertial Navigation System (LINS) ground navigation experiment suggests that the algorithm proposed by this paper can be satisfied without the need of high precision SINS alignment.

A Rapid Initial Alignment Alogrithm Based on Strapdown Gyrocompass

2012 ◽  
Vol 532-533 ◽  
pp. 1563-1567 ◽  
Author(s):  
Si Hai Li ◽  
Gong Min Yan ◽  
Peng Xiang Yang ◽  
Yong Yuan Qin
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Alignment Algorithm ◽  
Initial Alignment ◽  
Basic Principles ◽  
Nonlinear Error ◽  
Alignment Algorithms ◽  
Navigation Computer ◽  
Large Memory

The basic principles for stabilized gyrocompass initial alignment are analyzed in platform inertial navigation system (PINS), then similar principles and initial alignment algorithms suitable for programming are proposed for strapdown inertial navigation system (SINS). The scheme of SINS gyrocompass initial alignment can be divided into four steps, including leveling alignment with header uncertainty, coarse header alignment, leveling realignment and gyrocompass alignment for header. By simplifying SINS nonlinear error model under header uncertainty, the formula of coarse header alignment is deduced. On the assumption of navigation computer having large memory and powerful computing ability, and basing on the ‘multiformity’ of SINS mathematical platform and the ability to attitude reverse control, a specific progress for SINS rapid gyrocompass alignment is introduced and designed in detail. Finally, some tests prove that the proposed alignment algorithm in this paper is effective.

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