The research presented in this thesis is concerned with multi-target localisation in MIMO radar. In particular, the aim is to develop novel algorithms which can improve the performance of target localisation. Firstly, a general spatiotemporal received signal model for MIMO radar is formulated. When the targets' relative delays are negligible, the general model turns into the spatial only signal model in which, in order to enjoy the enhanced parameter identifiability brought by the waveform diversity, a combined approach based on the virtual array structure is proposed for the multiple targets' directions and path gains estimation. The virtual array structure enables the proposed approach to identify more targets with accurate estimation. Besides, inspired by STAR manifold in communications, a novel spatiotemporal signal model for MIMO radar is proposed, which enables the existing multi-target localisation methods designed for the spatial only model working for the spatiotemporal one. Secondly, the multi-target localisation of MIMO radar operating in an envi- ronment with closely located targets is concerned. In such a scenario, the mu- tual interferences among targets severely degrade the performance of the current multi-target parameter estimators. Thus, an optimisation which takes account of the suppression of the mutual interferences for multi-target parameter estimation is formulated and the solutions to it are derived. Thirdly, based on these solu- tions, two novel multi-target parameter estimators are presented. By suppressing the interferences in the estimation, both the proposed methods outperform the existing ones. Finally, for the purpose of exploiting the high directional gain provided by the Tx beamforming in the multi-target localisation of MIMO radar, a joint Tx and Rx multi-target localisation approach is proposed. The cooperation between the Tx beamforming and target localisation enables the proposed approach to achieve better performance for the localisation of multiple targets.