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

<div>The actual value, initial value, and mean estimation by the proposed method using SQP and genetic algorithm for the measurement noise covariance.</div>

Mathematical Problems in Engineering

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Table 1

Table 1: Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 

Table 1 | Maximum Likelihood-Based Measurement Noise Covariance Estimation Using Sequential Quadratic Programming for Cubature Kalman Filter Applied in INS/BDS Integration 