Target detection with function of covariance matrices under clutter environment

Clutter has a strong interference on target detection. Different statistical model should be applied to specific situation. In this paper, we propose a function of covariance matrix based algorithm to detect target under clutter environment. The statistical covariance matrices with and without target are usually different, thus we can find the target present or absent. The advantage of proposed algorithm is it works effectively with limited sample data when target signal strength is very weak. The probabilities of detection versus SNR and ROC curves using sinusoidal target on Rayleigh distribution clutter model, log-normal distribution clutter model, and Weibull distribution clutter model show that the algorithm is valid for different clutter models.