Bootstrap-based parametric adaptive matched filter detector: CFAR performance analysis

For parametric detection test, the probability of false alarm (PFA) always exceeds the preset level when the noise distribution is unknown, especially when the training data is limited. The PFA expression for parametric adaptive matched filter (PAMF) detector operating in both Gaussian and non-Gaussian clutter scenarios are lacked since the analysis becomes mathematically intractable. The bootstrap is a powerful technique for assessing the accuracy of a parameter estimator in situations where conventional techniques are not valid. The bootstrapped PAMF is carried out to compute the threshold when training data is limited. The result is outstanding when there is few training data.