《Table 1 MCKF computational complexity》

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《Marginalized cubature Kalman filtering algorithm based on linear/nonlinear mixed-Gaussian model》

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We derive computational complexity to further analyze the proposed algorithm.For time k，it is assumed that system state and measurement satisfy ，respectively.In MCKF implementation process，nonlinear state and linear state are .The equivalent computational complexity of matrix Cholesky factorization with n1×n1and n×n dimension are c1=n13/3+2n12and c'1=n3/3+2n2，respectively.The equivalent computational complexity of m×m matrix inversion is c2=m3.The computations for standard CKF[7]and MCKF are given in Table 1 and Table 2.