Deep Integration of a Flight Vehicle Dynamic Model in a Vector Tracking Software Defined Receiver

Abstract

The greater occurrence of signal interference on Global Navigation Satellite Systems (GNSS) requires additional alternative navigation solutions to provide robust, reliable localization of flight vehicles when measurements from GNSS are unavailable. This thesis proposes a Flight Vehicle Dynamic Model (FVDM) that is deeply integrated with Global Positioning System (GPS) correlator measurements for aircraft state estimates in GPS-challenged environments. It is well-documented that large, modern aircraft feature an array of sensors that work in tandem to provide robust positioning performance. However, the sizing limitations of low Size, Weight, Power, and Cost (SWaP-C) do not allow for such redundant sensor suites, meaning an alternative navigation solution is required. Furthermore, low cost flight vehicles typically feature lower quality sensors that are subject to vibrations and subsequently faulty, unreliable measurements that provide no benefit to the flight vehicle when GNSS measurements are also considered unreliable. The FVDM is a high-fidelity flight vehicle model based on the Diamond DA-40 singlepropeller fixed wing aircraft. The aircraft model features a piston engine model that generates thrust power through a shaft that spins a numerically modeled 3-blade propeller. The speed of the propeller is controlled through a electric governor, and the pitch is controlled to maintain efficient propeller action onto the incident airflow. The aerodynamics of the aircraft are modeled using a discretized aerodynamic coefficient technique, also known as strip theory. Although not used in this work, a landing gear model incorporates the three landing gear on the Diamond DA-40 and evaluates the forces and moments applied during landing as a second-order springmass- damper system. An International Standard Atmosphere (ISA) model is used to calculate the density, temperature, and ambient pressure based on aircraft altitude. To close the loop of the FVDM, a set of controllers in collaboration with a waypoint manager are used to actuate the control surfaces on the aircraft. Multiple planned paths are demonstrated during this work and are presented in their respective sections. The proposed navigation filter presented in this work provides a closed loop solution fusion of the vector tracking loop algorithms and the FVDM process model via a Vector Delay and Frequency Lock Loop (VDFLL). Vector tracking loops are able to maintain channel lock on satellite signals when either signal interference is present, or the dynamics of the collection platform are too high for scalar loops to track the signal consistently. The results within this work showcase the improvements in flight vehicle state estimates when compared to a standard VDFLL zero-mean acceleration kinematic model. In simulation, two trajectories are flown under varying levels of signal degradation. The first trajectory is a steady-level, un-accelerated flight path where the aircraft is maintaining a constant altitude and heading for the duration of the 60 second simulation. For this trajectory, it is expected that the standard VDFLL implementation performs comparably to the proposed navigation filter. The second trajectory features a more dramatic flight bath – full of oscillatory turns and a constant climb segments. For the second trajectory, the proposed navigation filter out performs the standard VDFLL due to its capability to predict the behavior of the aircraft given a set of control inputs. Each of the trajectories and subsequent cases of signal degradation are tested in 100-run Monte-Carlo sims to further test the robustness of the proposed navigation filter.