Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration

<div>Attitude errors of the UAV by the CKF, HRCKF, and MLCKF for the case of Gaussian noise with inaccurate covariance.</div>

Mathematical Problems in Engineering

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Figure 7

Figure 7: Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 

Figure 7 | Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 