Mathematical Models For Navigation Systems

Mathematical Modelling of Aerospace Dynamic Systems with Practical Applications

Mathematical Modelling of Aerospace Dynamic Systems with Practical Applications provides mathematical models for several aerospace dynamic systems: aircraft, rotorcraft, missiles, unmanned aerial vehicles (UAVs), mini air vehicles (MAVs), autonomous underwater vehicles (AUWVs), and satellite-coordinate systems. Presenting the use of mathematical models for analysis, prediction, and control of these systems, this book discusses numerous applications in aircraft/helicopter parameter estimation, guidance and navigation of these vehicles, underwater object search, aerial terrain mapping, and satellite orbit determination. It explains path planning with obstacle avoidance, object occlusion detection and tracking, and multisensory target tracking and sensor data fusion. This book is intended for senior undergraduate mechanical and aerospace engineering students taking courses in aerospace systems and dynamics, flight dynamics and control, and dynamical systems and estimation. Instructors will be able to utilize a Solutions Manual and Figure Slides for their course.

Mathematical Models for Navigation Systems

GPS Stochastic Modelling

Global Navigation Satellite Systems (GNSS), such as GPS, have become an efficient, reliable and standard tool for a wide range of applications. However, when processing GNSS data, the stochastic model characterising the precision of observations and the correlations between them is usually simplified and incomplete, leading to overly optimistic accuracy estimates. This work extends the stochastic model using signal-to-noise ratio (SNR) measurements and time series analysis of observation residuals. The proposed SNR-based observation weighting model significantly improves the results of GPS data analysis, while the temporal correlation of GPS observation noise can be efficiently described by means of autoregressive moving average (ARMA) processes. Furthermore, this work includes an up-to-date overview of the GNSS error effects and a comprehensive description of various mathematical methods.