Guidance against maneuvering targets using Lyapunov optimizing feedback control

It has been recognized by several researchers that a guidance algorithm effective against maneuvering targets is the one that drives the heading error rapidly to zero and then maintains a zero heading error for the remainder of the flight. We have referred to this guidance algorithm as nonlinear guidance (NLG) as its implementation generally requires some nonlinear features. There are may ways in which NLG can be put into practice. We examine a new way of applying NLG that does not require knowledge of line-of-sight rate, or target acceleration. However, information on the target aspect angle is required. The new guidance law is derived using the Lyapunov optimizing feedback control method. We make some performance comparisons with augmented proportional navigation. Not only do we maintain the performance advantage previously demonstrated in our earlier applications (2000) of NLG (requiring line-of-sight rate and target acceleration) but we also obtain a dramatic improvement in performance in the presence of measurement noise.