TY - GEN
T1 - Simulation research on GM navigation based on AFSA
AU - Zhu, Zhan Long
AU - Yang, Gong Liu
AU - Li, Jing
AU - Yang, Shu Jie
AU - Liu, Yuan Yuan
PY - 2014
Y1 - 2014
N2 - Geomagnetic matching (GM) is a new developmental technology in recent years. For resolving the cumulate errors of position, velocity, attitude in an inertial navigation system (INS), utilizing artificial fish swarm algorithm (AFSA) to carry on GM is proposed, and then the attained matching position regarded as measurement of filter to achieve the emendation of INS. Firstly, affine transformation model between inertial and real trajectories is displayed and the principle of INS/GM is explained. Secondly, the state of artificial fish (AF), distance and food consistence are defined afresh, and then the flow chart based on AFSA is given. Lastly, simulation analysis is performed in actual geomagnetic reference map (GRM). The results show that the algorithm actualizes the GM when the inertial system exist position, velocity and attitude error, that is the algorithm got the optimized global solution, with that, the data fusing is finished with the results that not only reduce error evidently but also verify the validity and feasible of the algorithm.
AB - Geomagnetic matching (GM) is a new developmental technology in recent years. For resolving the cumulate errors of position, velocity, attitude in an inertial navigation system (INS), utilizing artificial fish swarm algorithm (AFSA) to carry on GM is proposed, and then the attained matching position regarded as measurement of filter to achieve the emendation of INS. Firstly, affine transformation model between inertial and real trajectories is displayed and the principle of INS/GM is explained. Secondly, the state of artificial fish (AF), distance and food consistence are defined afresh, and then the flow chart based on AFSA is given. Lastly, simulation analysis is performed in actual geomagnetic reference map (GRM). The results show that the algorithm actualizes the GM when the inertial system exist position, velocity and attitude error, that is the algorithm got the optimized global solution, with that, the data fusing is finished with the results that not only reduce error evidently but also verify the validity and feasible of the algorithm.
KW - Affine transformation
KW - Artificial fish swarm algorithm
KW - Extended Kalman filter
KW - Geomagnetic matching
KW - Inertial navigation system
UR - https://www.scopus.com/pages/publications/84905833666
U2 - 10.4028/www.scientific.net/AMR.989-994.2555
DO - 10.4028/www.scientific.net/AMR.989-994.2555
M3 - 会议稿件
AN - SCOPUS:84905833666
SN - 9783038351733
T3 - Advanced Materials Research
SP - 2555
EP - 2559
BT - Materials Science, Computer and Information Technology
PB - Trans Tech Publications Ltd
T2 - 4th International Conference on Materials Science and Information Technology, MSIT 2014
Y2 - 14 June 2014 through 15 June 2014
ER -