1. Several authors have discussed techniques for evaluating the effect of erroneous assumptions in a priori statistics and plant dynamics on Kalman filter response. (16-20) A unique problem arises in the performance evaluation of Kalman filters for hybrid-navigation systems, however, in that the technique employed must properly simulate the wide range of control options generally employed in these systems. Once the Kalman filter has estimated significant system errors, these estimates will generally be used to correct the system output in feedforward manner or to control system errors in a feedback implementation as illustrated in Figs. 5 and 6. Often both forms of system correction will be used. Proper simulation of feedback control effects are particularly important since this form of control can substantially alter system performance. This is especially true with regard to those "real world" errors which are not estimated in the Kalman filters. Three typescif feedback control are possible - reset or impulsive control, rapid torquing, and continuous control. A set of error covariance equations which are particularly suited to hybrid navigation system performance evaluation are developed in Appendix A.
2. System Configuration
3. ALT=15000' ALT=12000'