Parametric estimation of multi-line parameters based on slide algorithm

Abstract

The subspace-based line detection (SLIDE) algorithm enables the estimation of parameters of multiple lines within a digital image by mapping these lines to frequency modulated (FM) signals. In this paper, we consider the estimation of such obtained FM signals by using estimators developed for polynomial-phase signals (PPSs). For this purpose, a recently proposed method that combines the cubic phase function (CPF) and high-order ambiguity function (HAF), referred to as the product CPF-HAF (PCPF-HAF), has been used. Simulations show that the PCPF-HAF-based estimator is more accurate than the estimators based on time-frequency representations.