Matrix analysis
GLRT-based adaptive detection algorithms for range-spread targets
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive Detection With Bounded Steering Vectors Mismatch Angle
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive Detection and Interference Rejection of Multiple Point-Like Radar Targets
IEEE Transactions on Signal Processing
Adaptive detection of range distributed targets
IEEE Transactions on Signal Processing
Performance of the adaptive sidelobe blanker detection algorithm inhomogeneous environments
IEEE Transactions on Signal Processing
Rao Test for Adaptive Detection in Gaussian Interference With Unknown Covariance Matrix
IEEE Transactions on Signal Processing - Part II
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Radar Detection and Classification of Jamming Signals Belonging to a Cone Class
IEEE Transactions on Signal Processing
An ABORT-Like Detector With Improved Mismatched Signals Rejection Capabilities
IEEE Transactions on Signal Processing
Adaptive CFAR Radar Detection With Conic Rejection
IEEE Transactions on Signal Processing
GLRT-Based Direction Detectors in Homogeneous Noise and Subspace Interference
IEEE Transactions on Signal Processing
An Improved Adaptive Sidelobe Blanker
IEEE Transactions on Signal Processing
A Subspace-Based Adaptive Sidelobe Blanker
IEEE Transactions on Signal Processing
Adaptive beamformer orthogonal rejection test
IEEE Transactions on Signal Processing
Digital Signal Processing
Persymmetric adaptive detection of distributed targets in partially-homogeneous environment
Digital Signal Processing
Hi-index | 35.68 |
In this paper we deal with the problem of adaptive detection of mismatched mainlobe targets and/or sidelobe interfering signals that are distributed in range. To this end, we investigate the impact of modeling the actual useful signal as a vector belonging to a proper cone with axis the nominal steering vector as a means to improve the robustness of the decision rule in presence of mainlobe targets; similarly, in order to improve the rejection capabilities of the decision rule in presence of sidelobe interferers we study the effects of replacing the usual noise-only hypothesis with a noise-plus-interferers hypothesis where interferers belong to the complement of a cone with axis the nominal steering vector. At the design stage we resort to the two-step GLRT-based design procedure; to this end, we assume that a set of training data is available, namely data free of signal components, but sharing the same Gaussian distribution of the noise in the cells under test. Remarkably, proposed detectors possess the CFAR property under the noise-only hypothesis. The performance assessment, conducted by Monte Carlo simulation, is aimed at assessing the effectiveness of proposed solutions, also in comparison to existing ones.