Based on linear mixture assumption or training the classifiers by large amount of data, many methods used to recognize and estimate gas mixtures were adopted the nonorthogonal decomposition of steady response signal. Considering orthogonal decomposition approaches were mainly applied to analyze transient response signals, a gas mixture estimation model based on response equivalent and orthogonal decomposition of transient response signals was put forward. A novel nonlinear gas-mixing model was built after the analysis of MOS(Metal Oxide Semiconductor) gas sensor response characteristics based on the component equivalent expression for different gas responses. A new orthogonal basis function, the EQL (Extended Quasi-Legendre) basis, was proposed and applied to the decomposition of a transient response signal from the gas sensor. After the exponential relationship between the coefficients and the gas concentration was verified via regression analysis, the components in the gas mixture were separated, and their concentrations were estimated simultaneously. Experimental result shows that even though only the prior knowledge of single gas responses was applied to build the model, the concentration determined from the transient response of the gas mixture can reach an error within 15%.