Accurate calibration of aircraft air data systems is essential for reliable measurement of flow angles, altitude, and airspeed, particularly during dynamic flight manoeuvres where errors can become significant. Externally mounted vanes and probes are used to measure flow angles, local pressures and temperature, respectively. However, because these sensors are positioned close to the aircraft fuselage, they operate within disturbed local flow fields that differ notably from the free-stream conditions. As a result, their outputs require Position Error Corrections (PEC) to accurately estimate free-stream parameters such as pressure, temperature, and flow angles. The pre-flight PEC data or calibration tables for these sensors are generated based on the CFD predictions/wind tunnel experiments. All the flight-measured local variables from air data sensors need to pass through the air data computers, which contain these lookup tables, to obtain the free stream information. Despite the pre-flight calibration, position errors are generally observed in the free stream parameters, which necessitates further calibration of air data sensors using flight test data. This paper discusses the technique used to refine the static pressure calibration techniques of a high-performance aircraft. Here, the pressure coefficient is estimated as a time-varying parameter in the flight path reconstruction environment implemented using the Extended Kalman Filtering technique along with scale factors and biases in other parameters and wind. Aircraft kinematic equations were used for the implementation of the state and measurement model, and the flight test data from full flight sorties were used for the estimation process. An extensive validation of the on-board air data calibration tables was conducted. Mean values of the static pressure coefficient were updated using data from multiple sorties, each including computed mean errors from three independent sensors. A comparative analysis between the pre-existing and estimated static pressure coefficients was performed to identify specific flight regimes or manoeuvres where further refinement is required. Finally, the accuracy of the estimated true static pressure was validated by comparing the corresponding pressure altitude with radio altimeter readings at low altitudes, demonstrating strong agreement and validating the effectiveness of the proposed calibration refinement method