Uncertain Feature RCS Analyses based on Wavelet Decomposition
Abstract
A novel uncertainty analysis approach for radar cross section (RCS) data is proposed in this paper. The wavelet decomposition method is applied to separate the origin data for uncertain feature extraction. Methods of distribution fitting and analysis are studied and data uncertainty distribution characteristics are also compared. Several benchmark cases from RCS simulation are taken to validate the proposed method. The impact of attitude uncertainty on the target RCS is also studied.
DOI
10.12783/dtcse/cii2017/17260
10.12783/dtcse/cii2017/17260
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