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Integrated sensing and communication (ISAC) is a key feature in 6G wireless communication systems, providing ubiquitous sensing and communication (S&C) services. In this letter, we focus on improving the performance of the ISAC system by utilizing constructive interference (CI) to optimize the sensing performance, which is characterized by the Cramér-Rao bound (CRB) of target response matrix (TRM) estimation. To achieve higher estimation accuracy while maintaining communication quality, we propose two methods: a heuristic semidefinite relaxation (SDR)-based alternative minimization approach and a successive convex approximation (SCA) method. These methods address the optimization problem by dealing with the non-convexity present in the objective function. The numerical results demonstrate the effectiveness of the proposed algorithms in enhancing the ISAC performance compared to the baseline block-level based precoding designs.