Optimization of a strapdown inertial navigation system

The focus of this thesis is to find 21 error parameters in a Strapdown Inertial Navigation System (SINS) that would minimize objective functions or error functions to increase accuracy utilizing an optimization algorithm. The algorithm used is goal attainment by Gembiki which is a multi-objective optimization algorithm proven to outperform other optimization methods in terms of efficiency and accuracy over large numbers of problems. Simulations of a noise-free SINS mounted on an aircraft were done in a stationary and on the move scenario to simulate two conditions in which alignment could become necessary. The error parameters to find were sensor bias, sensor scale factor, position error, velocity error and orientation error. Moreover, this thesis investigates how accurate can the error parameters be computed and how much data must be collected to enable an acceptable degree of accuracy