The estimation of wing flexure deformation in transfer alignment based on inertial sensors network

Wing flexure deformation is a key and difficult point in the transfer alignment process of air-launched missiles. Affected by airflow impulse and complicated maneuver, wing will have unforeseen flexure deformation. This could bring initial errors in inertial navigation system, because missiles deviate from their nominal positions. The performance of the weapon system will be greatly reduced. This paper aims to estimate wing flexure deformation by using an inertial sensors network. Firstly, wing flexure model of a single node is established based on relative position and relative attitude. Using the outputs of inertial sensors, flexure deformation could be estimated in a Kalman filter. Secondly, the estimation results of all nodes are processed in a data fusion algorithm to gain the whole wing flexure deformation. In the simulation, two typical kinds of flexure deformation are used to evaluate this innovative method. With the high precision accelerometers and gyros, the estimated errors in either kind of flexure deformation can be decreased to a millimeter level. Besides, data fusion algorithm can restrain the errors from nodes using low precision sensors. The final shape of wing flexure deformation is more in line with its actual situation.