Publications

The state-dependent Riccati equation-based estimator is becoming a popular estimation tool for nonlinear systems since it does not use system linearization. In this paper, the state-dependent Riccati equation-based estimator is compared with the widely used extended Kalman filter for three simple examples that appear in the open literature. It is demonstrated that, by simulation, the state-dependent Riccati equation-based estimator at best has comparable results to the extended Kalman filter but is often worse than the extended Kalman filter. In some cases, the state-dependent Riccati equation-based estimator does not converge, even though the system considered satisfies all the mathematical constraints on controllability and observability. Sufficient detail is presented in the paper so that the interested reader cannot only duplicate the results but perhaps make suggestions on how to get the state-dependent Riccati equation-based estimator to perform better.

It is well known that interceptor performance against a weaving or spiraling target can be improved by use of a special purpose weave guidance law. However the weave guidance law requires knowledge of the target weave frequency. When the target weave frequency is unknown an extended Kalman filter is usually considered for the problem because it can be used to estimate the target weave frequency. However, the performance of the extended Kalman filter is sensitive to initialization errors. This paper offers an unusual linear Kalman filter bank approach, where each filter is tuned to a different target weave frequency, as a potential solution for estimating the target weave frequency. Rather than combining individual filter outputs in some probabilistic sense, a straightforward algorithm is presented for choosing the filter that is most closely tuned to the actual target weave frequency. This paper demonstrates that this filter bank approach is superior to that of the extended Kalman filter for the weaving target problem.

It is demonstrated that at high altitude the performance of a tail-controlled aerodynamic missile can degrade because of the existence of low frequency right-half plane zeroes in the airframe transfer function when either proportional navigation or optimal guidance is used. A new guidance law that accounts for the airframe zeroes is developed numerically and shown to have superior performance to existing guidance laws at the higher altitudes. Although no closed-form solution for the guidance law is presented, the resultant numerical values for the control gains of the guidance law can easily be stored as a multidimensional table in existing on-board flight control computers. Two methodologies for computing the guidance law control gains are presented.