  A complex-valued signal is improper if it is correlated with its complex
conjugate. The dimension of the improper signal subspace, i.e., the number of
improper components in a complex-valued measurement, is an important parameter
and is unknown in most applications. In this letter, we introduce two
approaches to estimate this dimension, one based on an information- theoretic
criterion and one based on hypothesis testing. We also present reduced-rank
versions of these approaches that work for scenarios where the number of
observations is comparable to or even smaller than the dimension of the data.
Unlike other techniques for determining model orders, our techniques also work
in the presence of additive colored noise.
