Crawling Wave Sonoelastography (CWS) provides quantitative information of tissue stiffness by the application of two mechanical vibrations into the tissue. However, most of the shear wave speed (SWS) estimators for CWS report lateral artifacts that could undermine the detection accuracy of lesion by increasing the false-positive rate. In previous works, a low-cost estimator (WAVE) based on the crawling wave spatial wavelength (CSPW) averaging along the slow-time domain was proposed, where an underestimation in stiffer inclusions with size smaller than the CSPW was reported. In this study, an improved estimator is developed from the linear model of the CSPW function and solved with an implementation of generalized Tikhonov regularization. Experiments with inclusion phantoms demonstrate that the new estimator copes with the underestimation of WAVE while increase lateral resolution and contrast-to-noise ratio in comparison with other estimators found in the literature.