A Cramér--Wold theorem for elliptical distributions

According to a well-known theorem of Cramér and Wold,
if P and Q are two Borel probability measures on R^d whose projections P_L,Q_L onto each line L in R^d satisfy P_L=Q_L, then P=Q.
Our main result is that, if P and Q are both elliptical distributions,
then, to show that P=Q, it suffices merely to check that P_L=Q_L for a certain set of (d^2+d)/2 lines L.
Moreover (d^2+d)/2 is optimal. The class of elliptical distributions contains the Gaussian
distributions as well as many other multivariate distributions of interest.
Our theorem contrasts with  other variants of the Cram\'er--Wold theorem,
in that no assumption is made about the finiteness of moments of P and Q.
We use our results to derive a statistical test for equality of elliptical distributions,
and carry out a small simulation study of the test, comparing it
with other tests from the literature. We also give an
application to learning (binary classification), again illustrated with a small simulation.