The stochastic linear quadratic(LQ) optimal control problem is solved for stochastic linear continuous-time systems with the partly unknown parameter by using the policy iteration approach. The feasibility of the stochastic LQ optimal control problem is equivalent to the solvability of the stochastic algebra Riccati equation(SARE). Firstly, the stochastic differential equation is converted into the deterministic equation by using Itˆo formula, and the solution sequence of SARE is obtained by using the policy iteration approach. Then, convergence analysis is presented to prove that the solution sequence of SARE reaches the solution of SARE, and the proof of mean square stability of the systems in the process of iteration is also given. Finally, a simulation example is given to illustrate the feasibility of the policy iteration approach.