Abstract: The generalized Wald test algorithm is derived to implement range-distributed targets detection embedded in K-distributed clutter which is modeled as a spherically invariant random process (SIRP). The range-distributed target is modeled as a subspace random signal. The algorithm performs an incoherent processing over all the cells under test and is shown that it ensures CFAR property with respect to the unknown statistics of the clutter texture component. First of all, every cell under test is computed by the ratio of the energy of the whitened data that lies in the transformed signal subspace to the energy of it that lies in the orthogonal subspace, the so-called noise subspace. And then, the final decision statistics is the summation of the ratio in every cell under test. Performances of the proposed detector are assessed by means of Monte Carlo simulation strategy. In particular, the simulation results highlight that the proposed detector has better detection performances compared with adaptive Wald receiver which was proposed in ［5］