Estimation of motion parameters by isolating scatterers using time-frequency filtering

Abstract

In SAR/ISAR imaging, estimation of motion parameters of moving objects is needed in order to compensate for translational motion that causes image blurring. Phase parameter estimation from signals corresponding to one scatterer buried in complex white Gaussian noise is a problem for which various successful techniques have been devised. For multicomponent signals, it is difficult to use these parametric methods. Isolating the signal's components in order to do the estimation can help. The authors have previously proposed the isolation of scatterers for instantaneous frequency estimation. This process allows not only the extraction of components but also the manipulation of each object separately. In this paper, we study the use of time-frequency filtering on parameter estimation for a complex exponential signal with polynomial phase modulation. Our study is limited to the use of the Discrete Polynomial- Phase Transform (DPT) of Peleg and Friedlander. Our approach is to simplify the problem of parameter estimation from multicomponent signals by isolating them and then performing the estimation on each one separately. The process of isolating components is also shown to be improved by applying superresolution in the computation of the time- frequency representation. We also formulate an approach using the DPT for motion parameter estimation on a signal model for stepped-frequency ISAR returns from a scatterer.