A MIXED KALMAN/ H_∞ FILTERING APPROACH FOR AUGMENTED PROPORTIONAL NAVIGATION GUIDANCE

摘要

The Augmented Proportional Navigation (APN) guidance approach is widely used for autonomous terminal-phase guidance in space missions, maneuvering targets interceptions and robotic operations. The aim of this paper is to present an alternative filtering method for the APN guidance. There are two particular aspects analyzed in the proposed approach. The first one is to use a model with state-dependent noise for the filter design. This is motivated by the fact that some of the measurements used for filtering are corrupted both with additive and multiplicative white noises (for instance the range between the interceptor and the target). The second particularity is the design of a mixed Kalmanl H_∞ filter corresponding to the class of models with state-dependent noise considered for the APN guidance problem. The reason of imposing a certain H_∞ norm level of attenuation for the state estimation error is the requirement of accurate knowledge of the noises statistics in the case of Kalman filtering. Moreover, the proposed mixed Kalman/ H_∞ filter provides good filtering performance in the situations when the unknown target maneuvers are generated either by stochastic or by deterministic exogenous inputs. The proposed filtering procedure is illustrated by numerical simulations.