This letter addresses the problem of high-resolution radar detection in interference and nonhomogeneous noise. The target signal and interference lie in two linearly independent known subspaces, but with unknown coordinate. The noise is modeled by a compound-Gaussian process with unknown covariance matrix and random texture. According to the two-step generalized likelihood ratio test-based design approach, we derive a distributed target detector. Numerical examples show that the proposed detector can provide better detection performance than their counterparts in nonhomogeneous environments.