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

Sensors

Wei Gao¹  Fei Yu¹  Ya Zhang¹  Yanyan Wang¹ 

[1] School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China;

关键词: strapdown inertial navigation system;    initial alignment;    denoising;    robust filter;    Cubarure Kalman filter;   

DOI  :  10.3390/s18103297

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown