An Augmented Strapdown Inertial Navigation System using Jerk and Jounce of Motion for a Flying Robot

Abstract

This paper offers an algorithm for enhancement of positioning accuracy of a quad-rotor flying robot, based on jerk and jounce of motion. The suggested method utilises the first and second numerical derivatives of the vehicle's acceleration and augments the mathematical model in the estimation process. For this purpose, the Kalman Filter (KF) is implemented for integration of a Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS). The required data are collected from a low-cost/quality Micro Electromechanical Sensors (MEMS) during an assisted flight. For increasing the precision and accuracy of the collected data, all instruments including accelerometers, gyroscopes and magnetometers are calibrated before the experiments. Moreover, to reduce and limit the measurement noises of the MEMS sensor, a low-pass filter is applied; this is while sensors in the autopilot are affected by high levels of noise and drift, which makes them inappropriate for accurate positioning. The experimental results exhibit an improvement in positioning and altitude sensing through augmentation of the loosely coupled SINS/GNSS navigation method.

Analytical Expression for Uncertainty Propagation of Aerial Cooperative Navigation

“…As stated, an EKF estimator is used to performe the method. As usual, the EKF is divided into the prediction/ propagation and update cycles (Bayat & Atashgah, 2017). In the prediction phase, the knowledge concerning the state variables of the system is propagated to the next step; based on the evolution of the state variable equations, the measured control inputs, and the statistical behavior of the system noise.…”

“…Contrarily, in an FR group, the lack of this property causes navigation errors to diverge much faster. These issues can be resolved based on the incorporation of the dynamic model of the vehicle inside the navigation system (Bayat & Atashgah, 2017;Koifman & Bar-Itzhack, 1999). In the proposed method, all measurements including relative measurements can be used to estimate the model parameters.…”

Tilt Sensor with Recalibration Feature Based on MEMS Accelerometer

“…MEMS accelerometers are currently widely used in many electronic and mechatronic devices for a number of purposes primarily related to the sensing of linear acceleration, but also vibration [1], mechanical shock (jounce) [2], and one-axis tilt, i.e., inclination [3], or two-axial tilt [4]. Mathematical processing of the accelerometer output signal enables the sensing of linear velocity or displacement [5], such as in the case of applying MEMS accelerometers for a wheel odometer designed to determine the kinematics of a car [6].…”