Flight Test Results of Terrain Referenced Aircraft Navigation with Laser Altimeter

Abstract

Inertial Navigation Systems (INS) are the main part of the integrated navigation for most of the aerial vehicles. However, the accuracy of an inertial navigation solution decreases with time as the inertial instrument (e.g., gyroscope and accelerometer) errors are integrated through the navigation equations. Therefore, different aiding techniques are used to limit the drift in these systems. One of the commonly used techniques is the integration of INS with Global Navigation Satellite System (GNSS) signals. By means of this integration, the advantages of both technologies are combined to give a complete and accurate navigation solution. However, GNSS signals travelled from the satellites to the receiver are at a very low power level. This low power level makes the signals susceptible to interference from other unintentional or intentional signals transmitted in the GNSS frequency range. If the interfering signal is sufficiently powerful, it becomes impossible for the receiver to detect the low power GNSS signal. There are different types of interference signals like jamming and spoofing. GNSS jamming, also referred as intentional jamming, is when a jammer generates sufficiently powerful disruptive noise signals at frequency bands used by a GNSS system in order to prevent GNSS receivers from tracking signals and calculating reliable navigation data. As for GNSS spoofing, unlike jamming, deceives the receiver into calculating an incorrect navigation data by generating a false signal that is either created by a signal generator or is a replica of a real recorded GNSS signal. The need for Terrain Referenced Navigation (TRN) arises when these GNSS signals are unavailable, jammed or blocked. In recent years, research on the application of TRN to aerial vehicles has been increased rapidly with the developments in the accuracy of digital terrain elevation database (DTED). Since the land profile is inherently nonlinear, TRN becomes a nonlinear estimation problem. Because of the highly nonlinear problem, linear or linearized estimation techniques such as Kalman or Extended Kalman Filter (EKF) do not work properly for many terrain profiles. In our previously published works, we already presented the nonlinear estimation techniques that can be suitable for the solution of TRN problem. In this paper, we move onto the real-time application of TRN algorithm and present an overview of the real-time flight test results. Thanks to our previous research, a nonlinear filtering method namely the Unscented Kalman Filter (UKF) based on the Unscented Transform (UT) of sigma points is selected and utilized for the real-time solution of problem due to its simplicity and low processor capacity requirement. The designed UKF algorithm is used to provide essentially continuous terrain navigation through closed-loop estimation of navigation errors in combination with fixed-angle-mounted laser altimeter ground clearance measurements and onboard Level-1 DTED obtained from open internet resources. A real-time implementation of the algorithm is integrated into a general aviation aircraft equipped with a commercial fiber-optic navigation grade INS using a multi-frequency, multi-constellation GNSS receiver. By means of this system, the performance of the algorithm is monitored during real-time flight test. The recorded flight data show that the implemented TRN algorithm successfully estimates the aircraft horizontal position states with an accuracy of less than DTED resolution.