Learn More
This work deals with source localization with time-difference-of-arrival (TDOA) measurements in two-dimensional (2-D) scenarios. Although the celebrated two-step weighted least squares (2WLS) method is quite successful, its drawback lies in an ill-conditioning problem when the sensor array is quasi-linear. This work presents a multidimensional scaling(More)
—We propose a novel 6-degree-of-freedom (DoF) visual simultaneous localization and mapping (SLAM) method based on the structural regularity of man-made building environments. The idea is that we use the building structure lines as features for localization and mapping. Unlike other line features, the building structure lines encode the global orientation(More)
—This work addresses the robust reconstruction problem of a sparse signal from compressed measurements. We propose a robust formulation for sparse reconstruction which employs the 1-norm as the loss function for the residual error and utilizes a generalized nonconvex penalty for sparsity inducing. The 1-loss is less sensitive to outliers in the measurements(More)