Target Signal Detection With Function of Covariance Matrices in Clutter Environment
Clutter has a strong interference on target signal detection. Different statistical model should be applied to specific situation. In this paper, the authors propose a function of covariance matrix based algorithm to detect target signal under clutter environment. The statistical covariance matrices with and without target signal are usually different, thus they can find the target signal present or absent. The advantage of proposed algorithm is it works effectively under extremely low SNR, like lower than -30 dB with limited sample data. The experimental results using sinusoidal target signal on Rayleigh distribution clutter model and log-normal distribution clutter model show that the algorithm is valid for different clutter models.