Affordable State Estimation Using Inertial Navigation Sensor Arrays
Luisa D. Fairfax, Frank E. Fresconi, Mark Costello · AIAA Atmospheric Flight Mechanics Conference · 2011
An extended Kalman filter using a point mass dynamic model and commercial-off-theshelf inertial navigation system sensor arrays was developed by the U.S. Army Research Laboratory to provide affordable, GPS-denied state estimation in precision projectiles. The algorithm was implemented and simulations were conducted with a six degree-of-freedom model of a mortar flight. Sensors were simulated with typical MEMS device errors. Results demonstrate the behavior of the estimator as a function of sensor arrays size. Overall, position error is improved as an array of 100 sensors reduces position by 41% over the single array.