  The paper addresses the problem of designing radar detectors more robust than
Kelly's detector to possible mismatches of the assumed target signature, but
with no performance degradation under matched conditions. The idea is to model
the received signal under the signal-plus-noise hypothesis by adding a random
component, parameterized via a design covariance matrix, that makes the
hypothesis more plausible in presence of mismatches. Moreover, an unknown power
of such component, to be estimated from the observables, can lead to no
performance loss. Derivation of the (one-step) GLRT is provided for two choices
of the design matrix, obtaining detectors with different complexity and
behavior. A third parametric detector is also obtained by an ad-hoc
generalization of one of such GLRTs. The analysis shows that the proposed
approach can cover a range of different robustness levels that is not
achievable by state-of-the-art with the same performance of Kelly's detector
under matched conditions.
