
TL;DR
This paper introduces a fixed-gain tracking filter design using an augmented-state observer that incorporates models for signals and interference, enabling improved transient and steady-state tracking performance.
Contribution
It proposes a novel fixed-gain tracking filter design method utilizing augmented-state observers with specific signal and interference subspace models.
Findings
Incorporates an integrating Newtonian model for signals.
Uses a second-order maneuver model for constant-g turn scenarios.
Creates a Nyquist null to achieve smoother track estimates.
Abstract
A procedure for the design of fixed-gain tracking filters, using an augmented-state observer with signal and interference subspaces, is proposed. The signal subspace incorporates an integrating Newtonian model and a second-order maneuver model that is matched to a sustained constant-g turn; the deterministic interference model creates a Nyquist null for smoother track estimates. The selected models provide a simple means of shaping and analyzing the (transient and steady-state) response of tracking-filters of elevated order.
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