Signal recovery from autocorrelation and cross-correlation data.
A signal recovery technique is motivated and derived for the recovery of several nonnegative signals from measurements of their autocorrelation and cross-correlation functions. The iterative technique is shown to preserve nonnegativity of the signal estimates and to produce a sequence of estimates whose correlations better approximate the measured correlations as the iterations proceed. The method is demonstrated on simulated data for active imaging with dual-frequency or dual-polarization illumination.
Schulz
Timothy J
TJ
Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, Michigan 49931, USA. schulz@mtu.edu
Voelz
David G
DG
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic