This project focuses on enhancing the accuracy of Position, Velocity, and Time (PVT) estimation in Global Navigation Satellite Systems (GNSS) using MATLAB. It leverages a theoretical foundation of Maximum Likelihood Estimation (MLE) integrated into an Extended Kalman Filter (EKF) to mitigate signal noise. By implementing complex moving window averages, the system achieved an 87% accuracy rate and reduced noise by 30%, making it suitable for high-precision navigation in LEO/GEO satellite orbits.

1. Signal Noise and Residuals: GNSS receivers often suffer from clock noise and carrier phase errors, leading to positional inaccuracies.
2. Dynamic Environment: Satellites in orbit move at extreme velocities; standard filters cannot always track these high-dynamic shifts without lag.
3. Confidentiality and Policy: This work was associated with the Space Application Center (SAC), ISRO, requiring strict adherence to security and data handling policies.

Designed a robust EKF in MATLAB to track the state vector (position and velocity) of a GNSS receiver. The filter uses a prediction-correction cycle to smooth out erratic signal inputs.

Forged a theoretical framework for using MLE to refine positioning by maximizing the likelihood function of the GNSS residuals. This updates the Covariance of Clock Noise (CNN) and Code/Carrier Phase (CEE) matrices dynamically.

Implemented a complex moving window average function in MATLAB. This serves as a critical pre-processing step, smoothing out short-term oscillations before the data enters the EKF, contributing to the 30% noise reduction.

The project successfully demonstrates that adaptive filtering techniques like MLE-enhanced EKF can significantly improve navigation precision for space-bound assets. By increasing accuracy to 87%, it provides a robust foundation for orbital determination and satellite constellation management.

1. High-Speed Rail Navigation: Ensuring precise location tracking for multi-coach trains moving at speeds exceeding 300km/h.
2. Financial Time-Stamping: Using precision time estimation for high-frequency trading (HFT) servers that require nanosecond sync across global data centers.
3. Defense Missilery: Providing terminal guidance systems with noise-resistant PVT estimation during flight.
4. Unmanned Aerial Vehicles (UAVs): Precise hovering and waypoint navigation for industrial inspection drones in high-altitude environments.
5. Smart Grid Synchronization: synchronizing phase measurements across large-scale electrical grids to prevent power surges and blackouts.