Robust Estimation for Optimal Guidance Laws

Abstract:

The aim of the paper is to present an alternative filtering method for the Augmented Proportional Navigation Guidance (APNG). Two main aspects distinguish the proposed filtering technique with respect to the ones used in the existing APNG laws. The first is the fact that by contrast with the classical Kalman filtering, some state-dependent noises in the measurements are taken into account. The second aspect is the use of a mixed filter for models with state-dependent noise which combines the benefits of the and Kalman type filtering. The aim is to cover the situations when the unknown target meneuvers are generated both by stochastic or by deterministic exogenous inputs. A case study together with comparative analysis of the numerical results illustrate and validate the proposed approach.

• Periodical: Applied Mechanics and Materials (Volume 332)
• Pages: 71-78
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.332.71
• Online since: July 2013
• Authors: Adrian Mihail Stoica
• Keywords: Augmented Proportional Navigation Guidance, Mixed Kalman/H_∞ Filtering, State-Dependent Noise, Stochastic Models

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