On Extensions of the Frank-Wolfe Theorems
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Convex Optimization
Strong Duality in Nonconvex Quadratic Optimization with Two Quadratic Constraints
SIAM Journal on Optimization
Complex Matrix Decomposition and Quadratic Programming
Mathematics of Operations Research
The adaptive coherence estimator: a uniformly most-powerful-invariant adaptive detection statistic
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Robust Gaussian and non-Gaussian matched subspace detection
IEEE Transactions on Signal Processing
A computationally efficient two-step implementation of the GLRT
IEEE Transactions on Signal Processing
The CFAR adaptive subspace detector is a scale-invariant GLRT
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
Signal modeling and detection using cone classes
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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
Adaptive beamformer orthogonal rejection test
IEEE Transactions on Signal Processing
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This paper considers adaptive detection and estimation in the presence of useful signal and interference mismatches. We assume a homogeneous environment where the random disturbance components from the primary and secondary data share the same covariance matrix. Moreover, the data under test contains a deterministic interference vector in addition to the possible useful signal. We focus on the situation where an energy fraction of both the useful signal and the deterministic interference may lie outside their nominal subspaces (conical uncertainty model). Under these conditions, we devise a procedure for the computation of the joint maximum likelihood (ML) estimators of the useful signal and interference vectors, resorting to a suitable rank-one decomposition of a semidefinite program (SDP) problem optimal solution. Hence, we use the aforementioned estimators for the synthesis of adaptive receivers based on different generalized likelihood ratio test (GLRT) criteria. At the analysis stage, we assess the performance of the new detectors in comparison with some decision rules, available in open literature.