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

<div>Estimation of the measurement noise covariance using SQP. (a) Estimation of the measurement noise covariance in velocity. (b) Estimation of the measurement noise covariance in position.</div>

Mathematical Problems in Engineering

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Figure 5: Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 

Figure 5 | Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 