The coordinatewise median of a multivariate data set is a highly robust location estimator, but it depends on the choice of coordinates. A popular alternative which avoids this drawback is the spatial median, defined as the value that minimizes the sum of distances to the individual data points. In this paper we introduce and discuss another orthogonal equivariant version of the multivariate median, obtained by averaging the coordinatewise median over all orthogonal transformations. We investigate the asymptotic behavior of this estimator and compare it to the spatial median.
"Orthogonalization of multivariate location estimators: the orthomedian." Ann. Statist. 24 (4) 1457 - 1473, August 1996. https://doi.org/10.1214/aos/1032298277