Title :
Detection of weak random signals in IID non-Gaussian noise
Author :
Kolodziejski, Kevin R. ; Betz, John W.
Author_Institution :
Mitre Corp., Bedford, MA, USA
fDate :
2/1/2000 12:00:00 AM
Abstract :
This paper considers the detection of weak random signals in circularly symmetric, independent, identically distributed noise. Locally optimum detectors and ad hoc nonlinearities are considered, with asymptotic expressions provided for evaluation of detection performance. The analytical expressions are used to evaluate the robustness of detectors to mismatch in the noise models. Finite-sample Monte Carlo simulation results indicate the reliability of these asymptotic measures in cases of practical interest. The results show that, as has been found for detection of weak known signals in non-Gaussian noise, reasonably configured ad hoc nonlinearities are nearly optimum and robust to modest errors in the noise statistics
Keywords :
Monte Carlo methods; noise; optimisation; random processes; signal detection; statistical analysis; ad hoc nonlinearities; analytical expressions; asymptotic expressions; asymptotic measures reliability; circularly symmetric independent identically distributed noise; detection performance; detector robustness; finite-sample Monte Carlo simulation results; i.i.d. nonGaussian noise; locally optimum detectors; noise models; noise statistics; weak random signals detection; Acoustic signal detection; Additive noise; Detectors; Gaussian noise; Noise robustness; Signal detection; Signal processing; Statistical analysis; Statistics; Testing;
Journal_Title :
Communications, IEEE Transactions on