Aiming at the problem of cumbersome process and low accuracy in the calibration of single-axis turntable, based on the in-depth analysis of the principle of turntable calibration, this paper presents a new type of coded stereo target and a multi-constraint optimization method for high-precision turntable parameters. Firstly, the target integrates three square planes with different positions and poses of coded feature points. The uniqueness of the code can accurately determine the pose changes of each plane. The parameters of the turntable can be calibrated with only a single adjustment of the target pose, significantly simplifies the calibration process. Secondly, an encoding feature point recognition and processing algorithm is designed. By generating an adaptive elliptical mask, the algorithm robustly separates and accurately identifies the coded feature points for reliable decoding, demonstrating strong robustness in various conditions. Finally, a multi-constraint optimization method for high-precision turntable parameters is designed. The objective function is established by combining point constraint, coplanar constraint and normal vector angle constraint, with appropriate weighting parameters to improve calibration accuracy. The experimental results show that the proposed method achieves a calibration accuracy of 0.021 mm with only a single adjustment of the target pose—an improvement of approximately 36.4% compared to traditional methods. Additionally, when assembling a standard sphere based on the calibration results, an accuracy of 0.025 mm is achieved, reducing the error by about 16.7% compared to conventional algorithms. This further validates the effectiveness of the proposed method. Moreover, under varying levels of noise, the optimization algorithm consistently produces stable results, demonstrating excellent robustness.