Name
Abstract | ||
|---|---|---|
In order to weaken the error of inertial sensors and to improve assaulting precision of an air launched missile, the technology of neural networks was attempted to on-line calibration of Strapdown Inertial Navigation System (SINS). Aiming at the time-varied specialty of SINS on moving base, an input-output sample structure was proposed to treat the neural networks for calibrating and revising the error of inertial instrument. Consequently, when a missile was appending under the wing, the trained neural networks can be straightway used for automatic calibration in the free-flight phase; In order to resolve inconsistent measurement of gyroscopes and accelerometers when a missile was appending under the wing and in free-flight phase modes, the error angles between master and slave SINS were estimated in advance, then the input sample of neural networks can simulate the free-flight phase. As a result, the precision of inertial sensors can be greatly improved, and the simulation results indicate that the intelligent calibration method is feasible. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/PACIIA.2008.249 | PACIIA (1) |
Keywords | Field | DocType |
neural network,trained neural network,free-flight phase,kalman filter,inertial sensors,input-output sample structure,calibration,neural networks,knowledge based systems,on-line calibration,strapdown inertial navigation system,air launched missile,aerospace computing,automatic calibration,intelligent calibration method,inertial navigation system,free-flight phase modes,missiles,free-flight phase mode,intelligent calibration,accelerometers,error angle,sins,gyroscopes,inertial navigation,neural nets,inertial instrument,moving base,inertial sensor,filtering,artificial neural networks,input output | Inertial frame of reference,Inertial navigation system,Gyroscope,Control theory,Accelerometer,Missile,Computer science,Kalman filter,Inertial measurement unit,Artificial neural network | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-3490-9 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin-long Wang | 1 | 103 | 6.32 |
| Liangliang Shen | 2 | 0 | 0.34 |
| Longhua Guo | 3 | 0 | 0.34 |