Original methods for radar detection performance analysis are derived for a fluctuating or non-fluctuating target embedded in additive and a priori unknown noise. This kind of noise can be, for example, the sea or ground clutter encountered in surface-based radar for the detection of low grazing angle targets and/or in high-resolution radar. In these cases, the spiky clutter tends to have a statistic which strongly differs from the Gaussian assumption. Therefore, the detection theory is no longer appropriate since the nature of statistics has to be known. The new methods proposed here are based on the parametric modelling of the moment generating function of the noise envelope by Padé approximation, and lead to a powerful estimation of its probability density function. They allow to evaluate the radar detection performances of targets embedded in arbitrary noise without knowledge of the closed form of its statistic and in the same way to take into account any possible fluctuation of the target. These methods have been tested successfully on synthetic signals and used on experimental signals such as ground clutter.