The refractive index structure constant $C_n^{\mathrm{2}}$ is an important atmospheric parameter reflecting turbulence intensity. Herein, a new $C_n^{\mathrm{2}}$ inversion method is proposed based on the coherence length $r_{\mathrm{0}}$ and isoplanatic angle ${\theta }_{\mathrm{0}}$ data of the entire atmospheric layer to address the problem related to the fact that many initial input data are needed for inversion and inversion without single type data. Based on the generalized Hufnagel-Valley (HV) turbulence model, the theoretical relationship between $r_{\mathrm{0}}$ and ${\theta }_{\mathrm{0}}$ is deduced. Based on the measured data of $r_{\mathrm{0}}$ and ${\theta }_{\mathrm{0}}$ in Nanshan, Xinjiang, the seven parameters of the generalized HV model are obtained using inverse calculations followed by the determination of the $C_n^{\mathrm{2}}$ profile. These seven parameter values are substituted into the deduced theoretical relationship of $r_{\mathrm{0}}$ and ${\theta }_{\mathrm{0}}$ to calculate the value of ${\theta }_{\mathrm{0}}$ on any single day. The simulation results show that the variation trend of the fitted average $C_n^{\mathrm{2}}$ and single-day $C_n^{\mathrm{2}}$ profiles are in good agreement with the Xianghe model, and the coincidence degree is high. The average value of the daily correlation coefficient between the calculated and the measured ${\theta }_{\mathrm{0}}$ profiles reaches 81.95%, and the highest value is 87%. The results verify the feasibility of the proposed method and provide a reference for the inversion of the $C_n^{\mathrm{2}}$ profile.