In space defense, utilizing the micromotion features to distinguish real targets from interfering targets and decoys is effective. Due to the imaging of the high-speed precession target by microwave radar consisting of isolated scattering centers, there are many difficulties in using inverse synthetic aperture radar (ISAR) images for feature extraction. On the other hand, the inverse synthetic aperture ladar (ISAL) image is relatively continuous because of the short wavelength of laser, and the image sequence contains information about the variation in image length and Doppler width caused by target precession, which can be used for inverse motion parameters. By establishing an observation model of the precession target and performing image processing on the obtained ISAL image at different times, the image length sequence and Doppler width sequence can be obtained. Using the ellipse fitting method to process the obtained sequence, the precession parameters of the target can be obtained. The algorithm does not require prior information such as the radius and speed of the target motion, effectively improving the practicability of the algorithm. Finally, the effectiveness of the algorithm is verified by experimental results, and the error is controlled within 2%.