A New Self-Alignment Method without Solving Wahba Problem for SINS in Autonomous Vehicles
CoRR(2024)
摘要
Initial alignment is one of the key technologies in strapdown inertial
navigation system (SINS) to provide initial state information for vehicle
attitude and navigation. For some situations, such as the attitude heading
reference system, the position is not necessarily required or even available,
then the self-alignment that does not rely on any external aid becomes very
necessary. This study presents a new self-alignment method under swaying
conditions, which can determine the latitude and attitude simultaneously by
utilizing all observation vectors without solving the Wahba problem, and it is
different from the existing methods. By constructing the dyadic tensor of each
observation and reference vector itself, all equations related to observation
and reference vectors are accumulated into one equation, where the latitude
variable is extracted and solved according to the same eigenvalues of similar
matrices on both sides of the equation, meanwhile the attitude is obtained by
eigenvalue decomposition. Simulation and experiment tests verify the
effectiveness of the proposed methods, and the alignment result is better than
TRIAD in convergence speed and stability and comparable with OBA method in
alignment accuracy with or without latitude. It is useful for guiding the
design of initial alignment in autonomous vehicle applications.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要