TY - JOUR
T1 - A novel joint navigation state error discriminator based on iterative maximum likelihood estimation
AU - Wang, Yongqing
AU - Luo, Yu
AU - Wang, Pai
AU - Wu, Siliang
N1 - Publisher Copyright:
© Siene China Press and Springer-Verlag Berlin Heidelberg 2015.
PY - 2015/12
Y1 - 2015/12
N2 - To break through the limitations of traditional discriminators used in vector tracking loops, this paper presents an iterative maximum likelihood estimation (IMLE) method for extracting navigation state errors from multi-satellite signals. The IMLE method takes into account both computational cost and estimation accuracy. The associated gradient vector and Hessian matrix of the MLE cost function are derived. The characteristics of the proposed joint discriminator are analyzed based on the properties of the MLE cost function, gradient vector, and Hessian matrix. The effectiveness of IMLE is verified by Monte Carlo simulation.
AB - To break through the limitations of traditional discriminators used in vector tracking loops, this paper presents an iterative maximum likelihood estimation (IMLE) method for extracting navigation state errors from multi-satellite signals. The IMLE method takes into account both computational cost and estimation accuracy. The associated gradient vector and Hessian matrix of the MLE cost function are derived. The characteristics of the proposed joint discriminator are analyzed based on the properties of the MLE cost function, gradient vector, and Hessian matrix. The effectiveness of IMLE is verified by Monte Carlo simulation.
KW - Cramer-Rao bound (CRB)
KW - Global navigation satellite system (GNSS)
KW - Iterative maximum likelihood estimation (IMLE)
KW - Joint navigation state error discriminator
KW - Vector tracking loop
UR - http://www.scopus.com/inward/record.url?scp=85068692590&partnerID=8YFLogxK
U2 - 10.1007/s11432-015-5438-z
DO - 10.1007/s11432-015-5438-z
M3 - Article
AN - SCOPUS:85068692590
SN - 1674-733X
VL - 58
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 12
M1 - 122201
ER -