Covariance matrix estimation for CFAR Detection in correlated heavy tailed clutter
Signal Processing - Signal processing with heavy-tailed models
A maximum entropy framework for space-time adaptive processing
Signal Processing - Special section: New trends and findings in antenna array processing for radar
One-and two-stage tunable receivers
IEEE Transactions on Signal Processing
One-and two-stage tunable receivers
IEEE Transactions on Signal Processing
Detection algorithms to discriminate between radar targets and ECM signals
IEEE Transactions on Signal Processing
Parametric adaptive radar detector with enhanced mismatched signals rejection capabilities
EURASIP Journal on Advances in Signal Processing
| Hi-index | 35.69 |
A two-dimensional (2-D) adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter (AMF) in nonhomogeneous environments. The algorithm's utility has been demonstrated empirically. Considering theoretic performance analyses of the ASB detection algorithm as well as the AMF generalized likelihood ratio test (GLRT), and the adaptive cosine estimator (ACE), under nonideal conditions, can become fairly intractable rather quickly, especially in an adaptive processing context involving covariance estimation. In this paper, however, we have developed and exploited a theoretic framework through which the performance of these algorithms under nonhomogeneous conditions can be examined theoretically. It is demonstrated through theoretic analysis that in the presence of undernulled interference, the ASB is a pliable false alarm regulatory (FAR) detector that maintains good target sensitivity. A viable method of ASB threshold selection is also presented and demonstrated