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.

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.

scholarly journals Multistage Attitude Determination Alignment for Velocity-Aided In-Motion Strapdown Inertial Navigation System with Different Velocity Models

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 665 ◽  
Author(s):  
Shutong Li ◽  
Yanbin Gao ◽  
Meng Liu
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Attitude Determination ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Alignment Accuracy ◽  
Alignment Algorithm ◽  
Model Errors ◽  
Velocity Models ◽  
Strapdown Inertial Navigation

A novel multistage attitude determination alignment algorithm with different velocity models is proposed to implement the alignment process of in-motion attitude determination alignment (IMADA) aided by the ground velocity expressed in body frame () in this paper. Normally, The-based IMADA is used to achieve the coarse alignment for strapdown inertial navigation system (SINS). The higher the coarse alignment accuracy, the better initial condition can be achieved to guarantee the performance of the subsequent fine alignment. Consider the influence of the principal model errors and the calculation errors on the alignment accuracy in traditional-based IMADA, this paper deals with a novel alignment algorithm by integrating two different velocity-based IMADAs and the multiple repeated alignment processes. The power of this novel alignment algorithm lies in eliminating the principal model errors and decreasing the calculation errors. Then, the higher alignment accuracy is achieved. Simulations and vehicle experiment are performed to demonstrate the validity of the proposed algorithm.

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