Abstract
Iterative algorithms based on saved data have been researched for strapdown inertial navigation system to make the best use of sensor data, and different alignment algorithms can be carried out during the iterative process to fulfil initial alignment. This paper firstly analysed two interactive processes. The forward-backward process needs to change the normal system model in the backward process and have additional error factors. While the forward-forward process is easy to be carried out without changing the system model, the transition error will also decrease the accuracy. In addition, traditional iterative methods always need to save a large amount of data and do redundant computation, which is not highly effective, especially in view of the real-time property. To address these effects, a forward-forward solution in the inertial frame based on Kalman filter is analysed. This method calculates the attitude transfer matrix in the inertial frame to deal with angular disturbances and avoids saving all the original measurement data during the process, which makes the method more stable and faster to fulfil in the real-time system. Simulation and turntable test validates the performance of the proposed method.
Highlights
Strapdown inertial navigation system (SINS) is widely used in the field of navigation and positioning, such as vehicles, ships, submarines, and aircrafts [1]
The horizontal misalignment angles will be less than one degree, and the heading misalignment angle is constrained in several degrees [10]
Fast initial alignment methods for SINS based on the saved data and iterative calculation have been researched a lot in recent years [17, 22,23,24,25]. e iterative process could be divided into forward-forward process and forward-backward process, and the normal fine alignment algorithm is combined with the iterative process
Summary
Strapdown inertial navigation system (SINS) is widely used in the field of navigation and positioning, such as vehicles, ships, submarines, and aircrafts [1]. Different from KF, the compass method is based on the classical control theory to realize initial alignment It does not need precise mathematical models and noise models, whereas it cannot estimate the sensor bias. The same set of sensor data can be used in the fine alignment process repeatedly to get a better attitude matrix with less navigation errors. Fast initial alignment methods for SINS based on the saved data and iterative calculation have been researched a lot in recent years [17, 22,23,24,25]. Error model of the inertial frame is adopted to fulfil the alignment, while decreasing the amount of saved data and shortening the time of iterative calculation.
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