Title :
Super-resolution range-Doppler imaging
Author :
Zhu, Z.D. ; Ye, Z.R. ; Wu, X.Q. ; Yin, J. ; She, Z.S.
Author_Institution :
Dept. of Electron. Eng., Nanjing Univ. of Aeronaut. & Astron., China
fDate :
2/1/1995 12:00:00 AM
Abstract :
The general observation model for range-Doppler imaging is established from the point of view of multiple scatter-point localisation, and the optimum imaging procedure based on the maximum likelihood principle is given. Pursuing simplified procedures, the authors present three super-resolution range-Doppler imaging methods, including the linear prediction data extrapolation DFT (LPDEDFT), the dynamic optimisation linear least-squares (DOLLS), and the Hopfield neural network nonlinear least-squares (HNNNLS) methods. The live data of a metallised scale model B-52 aircraft mounted on a rotating platform in a microwave anechoic chamber and a flying Boeing-727 aircraft as well as the simulated data of an aircraft were processed. The imaging results indicate that, compared to the conventional Fourier method, a higher resolution for the same effective bandwidth of transmitted signals and total rotation angle of the object may be obtained by these super-resolution approaches
Keywords :
Doppler radar; Hopfield neural nets; aircraft; discrete Fourier transforms; extrapolation; image resolution; least squares approximations; maximum likelihood estimation; optimisation; prediction theory; radar imaging; Boeing-727 aircraft; Hopfield neural network nonlinear least-squares; bandwidth; dynamic optimisation linear least-squares; linear prediction data extrapolation DFT; maximum likelihood principle; metallised scale model B-52 aircraft; microwave anechoic chamber; multiple scatter-point localisation; optimum imaging; range-Doppler imaging; rotating platform; simulated data; super-resolution imaging; total rotation angle; transmitted signals;
Journal_Title :
Radar, Sonar and Navigation, IEE Proceedings -
DOI :
10.1049/ip-rsn:19951625
