Information geometry based matrix CFAR (Constant False Alarm Rate) detector provides a way to the problem of radar target detection

which mainly consists of the estimation of mean matrix and the calculation of test statistics. The detection performance is closely related to the geometric measures on the matrix manifold. The existing geometric measures are considered from Frobenius norm. By contrast

this paper considers the geometric measure and the estimation of mean matrix by utilizing matrix spectral norm on matrix manifold. The mean matrix estimation is transformed into the optimization problem on the matrix manifold. The approximate mean matrix with low computational complexity is obtained according to the properties of the objective function. In addition

we propose several matrix CFAR detectors based on different mean matrix estimation methods. Finally

the detection power analysis and simulation results show that the detection performance of the proposed methods with lower computational complexity are superior to other existing matrix CFAR detectors. It provides a new effective technique for radar target detection under sea clutter background.