maximum entropy bandwidth extrapolation technique using wavelet subspaces

This dissertation is concerned with the development of a bandwidth extrapolation technique that performs maximum entropy estimations over wavelet subspaces. Bandwidth extrapolation techniques have been used in radar applications to improve range and cross range resolution of radar cross section (RCS) images. Comparisons are made of the performance of conventional maximum entropy estimation to maximum entropy estimation over wavelet subspaces. A least squares prediction error measure is used to compare original measured RCS data to extrapolated data. Then a relative error is defined as the ratio of prediction error using conventional maximum entropy to prediction error using maximum entropy over wavelet subspaces. Application of the bandwidth extrapolation technique is to measured RCS data of two objects. The first object consists of two 3/8" diameter conducting spheres placed 4" apart. Measurements used are for vertical polarization and 0 degree aspect angle covering a frequency range of 8.0 to 12.3827 GHz. The second object is a 1.6 meter aluminum cone. Measurements used are for vertical polarization and 0 degree aspect angle (nose on) covering a frequency range of 4.64 to 18.00 GHz. Results are shown for extrapolate measured data plus the original data with Gaussian white noise added to noise ratios of 25 dB, 20 dB, 15 dB, and 10 dB.