This paper deals with convex relaxations for quadratic distance problems, a class of optimization problems relevant to several important topics in the analysis and synthesis of robust control systems. Some classes of convex relaxations are investigated, using the sum-of squares paradigm for the representation of positive polynomials. Relationships among the considered relaxations are discussed and numerical comparisons are presented, highlighting their degree of conservatism.