Title :
A robust exponential mixture detector applied to radar
Author :
Stein, David W J
Author_Institution :
SPAWAR Syst. Center, San Diego, CA, USA
fDate :
4/1/1999 12:00:00 AM
Abstract :
Exponential mixture probability density functions (pdfs) are shown to be useful models of radar sea clutter. The variability of certain parameters leads to estimation error and degradation in the performance of detection algorithms derived from this model. Robust implementations are introduced by assuming that parameters are known within certain intervals and selecting values to prevent an excessive number of false alarms. An empirical study demonstrates an average 6-9 dB gain in comparison with a constant false-alarm rate (CFAR) processor
Keywords :
Bayes methods; Gaussian distribution; Poisson distribution; exponential distribution; maximum likelihood detection; maximum likelihood estimation; radar clutter; radar detection; radar resolution; radar theory; time series; 6 to 9 dB; X-band radar; amplitude only processing; detection algorithms performance; estimation error; excessive number of false alarms; expectation maximization; exponential mixture PDF; high resolution radar data; locally optimal Bayes detection; parameter estimation; radar sea clutter models; robust exponential mixture detector; robust implementations; spiky data; time series; univariate models; Detection algorithms; Detectors; Doppler radar; Gaussian distribution; Gaussian noise; Radar clutter; Radar detection; Radar signal processing; Robustness; Signal processing algorithms;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on