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

<div>Mean attitude errors of the UAV by the CKF, HRCKF, and MLCKF in the time interval (500 s, 700 s) for the case of Gaussian noise with inaccurate covariance.</div>

Mathematical Problems in Engineering

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Figure 10: Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 

Figure 10 | Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 