Title :
Threshold Setting for Adaptive Matched Filter and Adaptive Coherence Estimator
Author :
Liu, Jiangchuan ; Li, Huaqing ; Himed, Braham
Author_Institution :
Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´an, China
Abstract :
It is known that the probabilities of false alarm (PFAs) of several celebrated adaptive detectors including the adaptive matched filter (AMF) and the adaptive coherence estimator (ACE) can be expressed as integral forms. Nevertheless, it is inconvenient to set the detection thresholds by using these integral expressions. Here, we propose two computationally efficient schemes to calculate the thresholds of the AMF and ACE. In the first method, approximate expressions, in forms of elementary functions, for the PFAs of the AMF and ACE are derived. The thresholds of the AMF and ACE can be numerically computed by using these elementary expressions instead of the integrals, for reducing computational complexity. In the second approach, further approximations are employed to lead to highly simple expressions for the thresholds of the AMF and ACE, which enable us to directly compute the thresholds for a given PFA. Compared to the first one, the second scheme is more computationally efficient, but at the cost of a slight loss in accuracy. Numerical results verify the effectiveness of the two proposed schemes.
Keywords :
adaptive filters; matched filters; probability; ACE; AMF; PFA; adaptive coherence estimator; adaptive matched filter; approximate expressions; computational complexity; elementary expressions; elementary functions; integral expressions; probabilities of false alarm; Accuracy; Approximation methods; Coherence; Covariance matrices; Detectors; Noise; Training data; Adaptive coherence estimator; Laplace approximation; Rao test; adaptive detection; adaptive matched filter; generalized likelihood ratio test;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2345757