Research of rapid transfer alignment and observability analysis
Zhihua Feng, Jiang Wei-wei, Gao Shesheng
Abstract
Zhihua Feng, Jiang Wei-wei, Gao Shesheng
Abstract
This paper presents a new method for rapid transfer alignment of strapdown inertial navigation system (SINS). It adopts the concept of local observability in the first time to rapid transfer alignment for analyzing the observability of SINS. The simplified system state and observation models are established for analyzing the observability of the SINS attitude error. Based on the simplified models, the observability matrix is constructed to determine the local observability of SINS. The condition number of the matrix is introduced to measure the observability degree during the process of maneuver alignment. Simulation experiments and comparison analysis have been conducted, demonstrating that the proposed method cannot only effectively measure the local observability of SINS, but it can also enhance the performance of SINS rapid transfer alignment with improved observability and reduced alignment time.
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This paper presents a new method for rapid transfer alignment of strapdown inertial navigation system (SINS). It adopts the concept of local observability in the first time to rapid transfer alignment for analyzing the observability of SINS. The simplified system state and observation models are established for analyzing the observability of the SINS attitude error. Based on the simplified models, the observability matrix is constructed to determine the local observability of SINS. The condition number of the matrix is introduced to measure the observability degree during the process of maneuver alignment. Simulation experiments and comparison analysis have been conducted, demonstrating that the proposed method cannot only effectively measure the local observability of SINS, but it can also enhance the performance of SINS rapid transfer alignment with improved observability and reduced alignment time.
Key concepts: Observability, Inertial navigation system, Measure (data warehouse), Control theory (sociology), Inertial frame of reference, Matrix (chemical analysis), Computer science, Process (computing)