The performance of estimators for nonlinear dynamical systems during a sensor failure can be improved by the use of fusion of multiple sensors. When linear sensor models are used, the effect of feeding back a priori estimates obtained from other sensors is not important. However, if nonlinear sensor models are required, significant performance enhancement can be obtained by using feedback through a central processor. In some cases, simple modifications of the linear estimation schemes can be used even for highly nonlinear sensors. "Outer logic" can be used to detect sen-sor failures and modify the estimation algorithms accordingly. Fusion equations and Monte-Carlo simulation runs of nonlinear radar models fused with infrared models demonstrate the effectiveness of "outer logic" design for sensor failures. Results show the sensor fusion tracking accommodations provided by good "outer logic" design can improve nonlinear dynamical system performance of used multi-sensor suites.