A new approach for semiparametric detection

Semiparametric detection consists of combining the statistical optimality of a parametric test to the robustness regarding the data of a nonparametric test. This approach is specially interesting in presence of statistical hypotheses depending on unknown probability distributions. The proposed semiparametric approach consists of splitting the measurement vector into two parts such that the first part has a known statistical distribution. Then, it is proposed to calculate a likelihood ratio test based both on the first part and the detection result of a nonparametric test applied to the second part. The statistical performance of the proposed test is analytically established.