Aimed at the problems that the computational of classical sparse reconstruction algorithms is very complicated, and real\|time imaging processing capability is insufficient in radar systems subjected to the mentioned\|above faced with large\|scale radar echo data, quantum algorithms are applied to sparse signal processing of inverse synthetic aperture radar (ISAR) imaging in this paper, which brings the advantage of quantum computation in processing large\|scale data in a short time for radar sparse imaging. Firstly, based on the classical algorithm of ISAR sparse imaging, the quantization methods of classical algorithms such as matched filtering and sparse reconstruction algorithm are analyzed, and the mapping relationship between the classical algorithm and the quantum algorithm is established. Secondly, on the basis of determining the corresponding quantum algorithm and steps, a quantum circuit capable of realizing the function of the classical algorithm of sparse imaging is constructed, and an ISAR sparse imaging method based on quantum algorithms is proposed. Finally, according to the constructed quantum circuits in combination with the radar echo signal, the corresponding quantum states prepared are input into the quantum circuit to obtain the imaging results. The simulation results show that in comparison with the classical sparse imaging algorithm, the proposed sparse imaging method based on the quantum algorithms can greatly reduce the computational complexity during the data processing in radar imaging, ensuring the imaging quality.