A Kalman Filter Integrated Navigation Design for the IAR Twin Otter Atmospheric Research Aircraft (Methode de Navigation Integree a Filtre de Kalman Destinee au Twin Otter de L'Ira Charge des Recherches Atmospheriques)

Abstract : The IAR Twin Otter Atmospheric Research Aircraft has a continuing requirement for more accurate, inertially-based navigation data for both track recovery and the calculation of wind gust components. This navigational accuracy is necessary, not just during post-flight analysis, but also for real-time, in- flight guidance and wind computation. Previous developmental work on advanced navigation systems has demonstrated the benefits of a Kalman filter integrated navigation approach in order to satisfy the most stringent navigational requirements. A significant upgrade to the navigation sensor suite onboard the Twin Otter has resulted in the potential, via Kalman filtering, for generating very high quality inertial velocity and positional information in real time, together with improved airborne wind components. The Kalman filter integrated navigation design described in this report is based on the optimal blending of data from an LTN-90-100 strapdown Inertial Reference System (IRS), a Decca Type 72 Doppler velocity sensing (DVS) system and an ARNAV R-40 airborne Loran-C receiver - sensors that are available on the Twin Otter at the present time. In the Twin Otter's real-time computing/data acquisition system, all three of these navigation sensors are interfaced to the onboard LSI-11/73 microcomputer data parameters from the LTN-90-100 IRS, required for proper design of an IRS-based Kalman filter, are available with sufficient resolution and at a suitable digital sampling rate.