Ultrasonic diffraction tomography (DT) offers a way to achieve high-resolution imaging of the wavespeed map, and hence has strong potential applications in medical diagnosis and Nondestructive evaluation (NDE). Ideal images can be obtained with a complete array of sensors surrounding the scatterer, provided that the measurement data are fully sampled in space, obeying the Nyquist criterion. Spatial undersampling causes the image to be distorted and introduce unwanted circular artefacts. In this paper we propose an iteration approach using virtual transducers to achieve high-resolution tomographic imaging with undersampled measurements. At each iteration stage, the extent constraint estimated from the shape of the object of interest is applied on the image space to obtain a regularized image, based on which the ultrasonic measurement data at virtual transducers are calculated using a forward model. The full dataset composed of original and virtual measurements is then used for tomography in the next stage. A final image with sufficiently high resolution is obtained after only a few iterations. The new imaging method yields improvements in the robustness and accuracy of ultrasonic tomography with undersampled data.We present numerical results using complicated wavespeed maps from realistic corrosion profiles. In addition, an experiment using guided ultrasonic waves is performed to further evaluate the imaging method.