Robust adaptive signal processing methods for heterogeneous radar clutter scenarios
Signal Processing - Special section: New trends and findings in antenna array processing for radar
Kernel Spectral Matched Filter for Hyperspectral Imagery
International Journal of Computer Vision
A comparative analysis of kernel subspace target detectors for hyperspectral imagery
EURASIP Journal on Applied Signal Processing
Hybrid Detectors for Subpixel Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive subspace detection of range-distributed target in compound-Gaussian clutter
Digital Signal Processing
Adaptive detection and estimation in the presence of useful signal and interference mismatches
IEEE Transactions on Signal Processing
A new parametric GLRT for multichannel adaptive signal detection
IEEE Transactions on Signal Processing
Detection algorithms to discriminate between radar targets and ECM signals
IEEE Transactions on Signal Processing
Kernel oblique subspace projection approach for target detection in hyperspectral imagery
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Parametric adaptive radar detector with enhanced mismatched signals rejection capabilities
EURASIP Journal on Advances in Signal Processing
Detection performance analysis of tests for spread targets in compound-gaussian clutter
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Moving steganography and steganalysis from the laboratory into the real world
Proceedings of the first ACM workshop on Information hiding and multimedia security
Target detection based on a dynamic subspace
Pattern Recognition
Persymmetric adaptive detection of distributed targets in partially-homogeneous environment
Digital Signal Processing
| Hi-index | 35.69 |
The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Previously, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a target signal in noise whose covariance structure and level are both unknown and whose covariance structure is estimated with a sample covariance matrix based on training data. We show here that the CFAR ASD is GLRT when the test measurement is not constrained to have the same noise level as the training data, As a consequence, this GLRT is invariant to a more general scaling condition on the test and training data than the well-known GLRT of Kelly (1986)