Generalized spatial modulations (GSM) represent a novel multiple input multiple output (MIMO) scheme, which can be regarded as a compromise between spatial multiplexing MIMO and conventional spatial modulations, achieving both spectral efficiency and energy efficiency. Due to the high computational complexity of the maximum likelihood detector in large antenna settings and symbol constellations, in this correspondence paper we propose a lower complexity iterative suboptimal detector. The derived algorithm comprises a sequence of simple processing steps, namely, an unconstrained Euclidean distance minimization problem, an element-wise projection over the signal constellation, and a projection over the set of valid active antenna combinations. To deal with scenarios where the number of possible active antenna combinations is large, an alternative version of the algorithm, which adopts a simpler cardinality projection, is also presented. Simulation results show that, compared with other existing approaches, both versions of the proposed algorithm are effective in challenging underdetermined scenarios where the number of receiver antennas is lower than the number of transmitter antennas.