Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm

Abstract

This paper introduces a modified random sample consensus (M-RANSAC) and short-time fractional Fourier transform (STFRFT)-based algorithm for feature extraction of synthetic aperture radar (SAR) scattering centers. In this algorithm, the range migration curve (RMC) of a scattering center is formulated as a parametric model. By estimating these parameters, the backscattering envelope of scattering center, corresponding to the backscattering variation in synthetic aperture time, is extracted directly from a time-domain range-compressed signal. The estimated parameters can also reconstruct the geographical location and along-track velocity of scattering centers. Thus, even without knowing explicit knowledge of platform velocity and forming a SAR image, this algorithm is capable of realizing feature extraction. To estimate parameters scatter by scatter, M-RANSAC approach is proposed as an implementary method with iterative procedure. In the iterations, fitting precision indicator (FPI) works cooperatively with construction fitness coefficient (CFC) to determine the optimal parameters of different scattering centers. Adapting this method to more general cases, STFRFT is introduced to separate the overlapped trajectories of RMCs of scattering centers. The root mean squared errors (RMSEs) of parameter estimation are close to their Cramér-Rao lower bounds (CRLB). The effectiveness of feature extraction based on the devised algorithm is validated by both simulated and real SAR data.

Simple Household Space Design Based on Soft Decoration of Furniture

“…In the face of image calculation, the image can be analyzed in the form of a matrix, which is accurate and efficient (Zhai Qet al2016) [6] . The computational research of RANSAC algorithm has been applied in practical engineering, which adds a new research path to the computation of image processing in the world (Sheng Het al2016) [7] .…”

Accurate Parameter Estimation of Over-the-Horizon Radar Signals Using Ransac and Music Algorithms

“…A high percentage of the estimated IF entries is corrupted by clutter, noise and other phenomena, and we use the random samples consensus (RANSAC) algorithm [11][12][13] to improve the IF estimate. The STFT and the RANSAC algorithms produce a coarse estimate of the IF of all received components while in the next stage high-resolution estimation of the close signal components is performed.…”