When the traditional error-state Kalman filter algorithm is used for aircraft attitude estimation without heading reference, significant errors can occur due to inaccurate linearization. To address this issue, this paper proposes an error-state Kalman filter algorithm based on the navigation coordinate system (NCS-ESKF). An aircraft attitude estimation system is designed, and both indoor static turntable experiments and DA40 airborne flight experiments with a general aviation aircraft are conducted. Experimental results show that, compared to three traditional algorithms, the proposed NCS-ESKF algorithm produces smaller errors, with mean absolute errors (MAE) for roll and pitch angles of just 0. 809° and 0. 934°, respectively. During the taxiing and flight phases of the airborne experiments, a segmented threshold method was employed to set different horizontal maneuvering acceleration thresholds, resulting in MAEs of 0. 954° for roll and 0. 867° for pitch. This effectively improves the accuracy of aircraft attitude estimation. The NCS-ESKF algorithm significantly reduces estimation errors and enhances aircraft attitude estimation performance, contributing to improved stability in flight control for general aviation aircraft.