This paper presents the implementation of flight path reconstruction (FPR) and wind estimation techniques applied to a high performance fighter aircraft. The analysis is carried out for the flight test data gathered and stored in a Crash Data Recorder (CDR). The data signals obtained from CDR are generally highly noisy, with frequent data drop outs and also with low sampling rate. The estimation technique applied for data reconstruction is the extended Kalman filtering (EKF). The reconstructed trajectories can be compared with the actual flight trajectories such that, in case of unavailability of data from other sources (e.g., digital flight control computer), the algorithm should be able to reconstruct the trajectories with the minimum set of data available from the CDR. Wind estimation along with the trajectory reconstruction can give better accuracy in airspeed as well as flow angles. The algorithm also aims at determining the bias/systematic instrument errors and generating accurate aircraft state trajectories. A standalone application is developed to reconstruct the flight trajectories for the full flight data. The algorithm is implemented using MATLAB®.