Forest canopy height is a very important forest structural attribute. LiDAR and SAR are able to penetrate the forest canopy to obtain information on the understory and canopy vertical structure. But the single data of LiDAR or SAR has its own shortcomings in forest height extraction. We jointly use LiDAR and ALOS PALSAR data to retrieve forest canopy height. First, the extinction degree of the canopy is extracted using airborne LiDAR. The canopy is assumed to be uniform, and the extinction degree is divided by the canopy height to obtain the average extinction coefficient. Then, the extinction coefficient is substituted into random volume over ground (RVoG), and the forest canopy height is obtained. Experimental results showed that the collaborative inversion algorithm based on RVoG model proposed in this paper improves the accuracy of forest canopy height retrieval.