This paper presents a matching pursuit (MP)-based inverse synthetic aperture radar (ISAR) imaging algorithm in missing-data case. The valid ISAR data matrix is presented as linear combination of a set of basis sub-signals, which are generated by discretizing the target spatial domain and synthesizing the ISAR data for every discretized spatial position. Then ISAR imaging problem is converted into a basis sub-signal selection problem and solved via MP-based algorithm. In the case of unknown rotation rate, multiple ISAR images are firstly formed by the proposed algorithm with multiple rotation rate candidates, and then the true rotation rate is determined by searching the maximal contrast among all ISAR image candidates. Numerical examples show that the proposed algorithm can produce high resolution and remove sidelobe artifacts in missing-data case.