Flexible intelligent metasurface (FIM) has emerged as a transformative technology to enhance wireless sensing by dynamically morphing its three-dimensional (3D) surface shape and electromagnetic response. Unlike conventional rigid arrays, an FIM consists of low-cost radiating elements that can independently adjust their positions and radiation characteristics, thereby allowing for real-time optimization of the sensing environment. This paper investigates the impact of FIM on wireless sensing performance. Specifically, we focus on the maximization of the cumulated power of the probing signals at the target locations under the per-antenna power constraint by jointly optimizing the transmit covariance matrix and the surface shape of the transmitting FIM. We propose a block coordinate descend (BCD) algorithm to find a locally optimal solution, by alternatively updating the FIM surface shape and the transmit covariance matrix, while keeping the other one fixed at each step. Furthermore, we analyze the computational complexity and convergence properties of the proposed algorithm and demonstrate that FIM enhances wireless sensing by providing a new design degree-of-freedom to coordinate the correlation between steering vectors at different angles. Numerical results demonstrate that FIM significantly improves wireless sensing performance under the considered multi-target scenario.