The track geometry state measuring instrument using GNSS positioning cannot work in GNSS rejection environment such as tunnel and subway. Since the railroad track is still close to the design alignment even if it is deformed, the difference between the actual track position and its design value always remains within a certain range. For this reason, a track irregularity detection algorithm considering design attitude assisted IMU/ODO was proposed by combining railroad design parameters with inertial guidance/odometer information, which combined design attitude with inertial guidance solved attitude for Kalman filtering and uses odometer velocity for heading projection. Through computational experiments, the effect of track design attitude information on the improvement of track irregularity detection accuracy was analyzed. The experimental results show that the railroad design attitude information can significantly improve the track irregularity detection accuracy, and the proposed method is comparable to the dynamic detection method based on the total station assisted by the 30m chord track irregularity detection accuracy, and the overall detection efficiency is high to meet the needs of daily track detection.