equation that preferably uses u201c current state u201d sensor atmospheric data the code heavily relies on the computation of u201c magnus moment u201d and utilization of the u201c initial firing geometry u201d the regression algorithm utilizes a series of filters and data bases where u201c prior state u201d data is stored the combinations of sensors are shown in the table appearing in fig6 the subroutines and databases identified by the letters a j in fig5 are as follows subroutine a u2014 sensor data is checked to verify data is in an allowable range truth table subroutine b u2014 with identification of sensors combinations the algorithm accesses default data from data base u201c h u201d and computes a probabilistic u201c best fit u201d solution using non linear kalman filter techniques and methods subroutine c u2014 u201c prior state data u201d in data base u201c j u201d is compared to results of subroutine b solution if available ammunition data base information is used in the subroutine this subroutine also utilizes bias error histograms located in data base u201c l u201d to the refine solution subroutine d u2014 a final regression analysis subroutine again using non linear kalman filtering techniques with a bias check sub routine generates the final solution that the operating system will display in the gui subroutine e u2014 pre shot biases are recorded in data base u201c l u201d actual u201c registration of shot data time u201d information such as projectile yaw muzzle velocity and position in flight time or position at impact time is collected and loaded to prior state data base u201c j u201d subroutine f u2014 bias error analysis from shot is executed and data base u201c l u201d is updated subroutine.