We develop maximum likelihood (ML) methods for location estimation using spatio-temporal received-signal strength (RSS) measurements in wireless fading channels. Fading and composite fading-shadowing scenarios with completely unknown and partially known source signals are considered. We adopt gamma (Nakagami-m) and lognormal models to describe fading and shadowing effects, respectively. We also derive Cram´er-Rao bounds (CRBs) for the location parameters and discuss initialization of the proposed algorithms. Numerical simulations demonstrate the performance of our estimators.