The Maritime Augmented Guidance with Integrated Controls for Carrier Approach and Recovery Precision Enabling Technologies (MAGIC CARPET) effectively overcomes the drawbacks of traditional carrier-based aircraft landing methods, improving trajectory response speed and landing accuracy, while significantly easing the control burden for pilot. Analysis of the control structure of MAGIC CARPET reveals its high dependency on flight path angle signals. In this paper, a set of state equations and measurement equations for path angle estimation are proposed for nonlinear Kalman filter algorithm. The Unscented Kalman Filter (UKF) is applied to the designed state equations and measurement equations, then a complete nonlinear path angle estimation algorithm is obtained. The algorithm considers the constant drift of inertial sensors and the slow update frequency of GPS data in the design process. In the simulation verification section, this paper establishes sensor error models and aircraft carrier wake turbulence models. The algorithm constructs flight path angle signals in real-time and integrates them into the solution of the Integrated Direct Force Control (IDLC) control law. This paper also provides the flight path angle construction results of two other traditional algorithms for comparison. The results illustrate that based on UKF, the flight path angle construction algorithm is not affected by wind disturbances and does not diverge over time, effectively integrating information from inertial sensors and GPS velocity signals. The algorithm can be used in the MAGIC CARPET landing control loop.