For the problem of range-spread detection in non-Gaussian clutter, the Autoregressive(AR) model and the generalized clutter-clustered model are combined and a generalized clutter-clustered model based on AR is established. Moreover, a Regressive Approximate Generalized Likelihood Ratio Test detector based on the Generalized Clutter-Clustered(RAGLRT-GCC) is proposed. The RAGLRT-GCC is an adaptive detector and it does not need secondary range cells to estimate the parameters of clutter. The RAGLRT-GCC makes full use of the clutter-clustered information and it improves the detection performance for spare scatterer targets of the detector. The simulation results also show that the detection performance of the RAGLRT-GCC is better than that of the Regressive Approximate Generalized Likelihood Ratio Test detector based on Compound Gaussian(RAGLRT-CG) at the same detection probability.