arXiv:2610.07185v1 Announce Type: new Abstract: This paper proposes a subspace-based decision scheme to detect range-spread targets in presence of thermal noise, clutter, and intentional interference. The target and intentional interference (i.e., noise-like jammer) effects are confined to the covariance matrix of the received primary data vectors. The jammer is also present in the secondary data vectors necessary to estimate the clutter covariance matrix. Finally, an additional set of training data, acquired by the system in passive mode and, hence, not contaminated by target and clutter echoes, is used to avoid the jammer parameters are unidentifiable. The detection problem is addressed by deriving an architecture based upon the likelihood ratio test where the unknown second-order parameters are suitably estimated. To this end, a unified theoretical framework is defined also providing a geometrical interpretation of the estimation procedures. The performance assessment, conducted also in comparison to a natural competitor, highlights the effectiveness of the proposed solution.