Gradient test for double subspace signal detection
Weijian Liu, Can Huang, Daipeng Xiao, Jun Liu, Binbin Li, Hui Chen · IET conference proceedings. · 2024
In this paper, we consider the detection problem for double subspace signal detection and devise an effective detector according to the criterion of gradient test, which possesses the constant false alarm rate (CFAR) property with respect to unknown noise covariance matrix. Numerical examples show that the proposed detector can achieve better detection performance than existing ones. We also show the factors which can affect the detection performance.