Abstract: The attitude control and navigation accuracy of launch vehicles highly depends on the accurate acquisition of atmos-pheric data. The Flush Air Data Sensing System (FADS) can map key atmospheric data by measuring the pressure distribution on the launch vehicle's nose surface. However, in complex flight environments, blockages in pressure transmission pipelines from surface pressure taps to sensors may easily cause failures in atmospheric data meas-urement and flight control. Thus, it is necessary to establish real-time pressure transmission fault identification and atmospheric data redundancy design to enhance the reliability of launch vehicle flight control.Research was con-ducted on a launch vehicle model with a spherical nose and double cone configuration. A pressure database was built via wind tunnel calibration tests, and atmospheric data calculation was performed using the Kalman filter algo-rithm. Moreover, a fault detection and identification (FDI) algorithm was designed based on the chi-square distribu-tion principle, and a full-process closed-loop redundancy architecture of "calculation-detection-identification-isolation-voting" was established, with verification supported by offline simulations and online wind tunnel tests.The results show that: under subsonic conditions with small angles of attack (AoA), the AoA calculation accuracy of the Kalman filter algorithm is ＜ 0.105°, and the Mach number (Ma) calculation accuracy is ＜ 0.0165; offline simulations confirm that the redundant FADS can accurately detect and locate single-point and multi-point faults, with the fluctu-ation of AoA calculation accuracy ＜ 0.023° and Ma accuracy ＜ 0.01 before and after fault identification and isolation; in online wind tunnel tests simulating single-point faults, the redundant FADS achieves real-time fault detec-tion/identification and high-precision redundant calculation output at a 100Hz frequency, with AoA calculation accu-racy ＜ 0.08° and Ma calculation accuracy ＜ 0.0067. This study provides an engineering reference and experimental support for improving the fault tolerance and reliability of launch vehicle FADS in complex flight environments.