Large Misalignment Angle Initial Alignment Using UKF

In inertial navigation systems, precise initial alignment is crucial for accurate performance. For optimal results, we recommend implementing Unscented Kalman Filter (UKF) for initial alignment procedures. The UKF algorithm represents an advanced filtering technique that effectively handles system noise and nonlinear dynamics through sigma point transformation, which propagates carefully selected points through the nonlinear system instead of linearizing the model. When implementing UKF for initial alignment, key functions include: - Sigma point generation around the current state estimate - Nonlinear propagation of sigma points through system dynamics - Measurement update using transformed sigma points - Covariance matrix maintenance for uncertainty quantification The UKF-based initial alignment approach significantly enhances navigation system accuracy and stability by properly addressing nonlinear large misalignment conditions. Furthermore, performing initial alignment with UKF provides deeper insights into navigation system operational principles and performance characteristics. Therefore, initial alignment constitutes a critical step in inertial navigation systems that requires careful implementation and validation.