This thesis outlines the dynamic system analysis of a 3D Ultrasonic neuro- navigation system for use in motion capture studies. The work entails the development and implementation of methods for achieving the same. The objective of the project is to come up with an accurate dynamic 3D ultrasonic neuro-navigation system which can deliver up to sub mm accuracy within the operating workspace for use in image guided neuro surgery. The major focus of the work is to come up with a second order Kalman filter which can take out the outliers occurring in a static system in real time, thereby making the system more robust and accurate. Once the filter achieves the requisites, it can be integrated into the current motion tracking software which allows for the real time tracking of transmitters, hence the points of interest.