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The initial alignment error model of strap-down inertial navigation system is nonlinear under large azimuth misalignment angle condition, and it could be processed by the particle filter algorithm. In order to solve the problem that importance density function of the particle filter is difficult to select, a new robust adaptive cubature particle filter algorithm is proposed. The equivalent weight...
In this paper, a new Krein space approach to robust filtering for linear systems with multiple uncertainties is developed. The multiple uncertainties satisfy the energy-type constraints, entering into both state and measurement equations. The proposed approach is used to tackle the sub-optimization problem arising from a sum quadratic constraint (SQC) of system uncertainties. To this end, a novel...
Zero Velocity Update (ZUPT) utilizes the zero velocity condition for stationary Strapdown Inertial Navigation System (SINS), executes navigation errors estimation and emendation to control SINS position growth. The improved filter estimation ZUPT is proposed in this paper. Two technologies, separate-bias Kalman filter and yaw error rapid estimation, are applied in the proposed method. Separate-bias...
This paper proposes the fusion of GPS measurements and inertial sensor data from gyroscopes and accelerometers in tightly-coupled GPS/INS navigation systems. Usually, an extended Kalman filter (EKF) is applied for this task. However, as system dynamic model as well as the pseudorange and pseudorange rate measurement models are nonlinear, the EKF is sub-optimal choice from theoretical point of view,...
The optimal two-position alignment using Kalman filter is newly derived for strapdown inertial navigation system (SINS). During the alignment process, SINS is rotated with respect to the heading axis. The Kalman filter estimates the misalignments and gyro drifts at these two positions. In terms of the relationship between yaw misalignments and gyro drifts, the horizontal gyro drifts can be computed...
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