Imaging of aeroacoustic noise sources is routinely accomplished with geometrically fixed phased arrays of microphones. Several decades of research have gone into improvement and optimization of sensor layouts, selection of basis models, and deconvolution algorithms to produce sharper and more localized images of sound-producing regions in space. This paper explores an extension to conventional phased array measurements that uses slowly, continuously moving microphone arrays with and without coupling to rigid fixed arrays to improve image quality and better describe noise mechanisms on turbofan engine sources such as jet exhausts and turbomachinery components. Three approaches are compared in the paper: fixed receiver beamforming (FRBF), continuous-scan beamforming (CSBF), and multireference CSBF (MRCSBF). The third takes advantage of transfer function matrices formed between fixed and moving sensors to achieve effective virtual arrays with spatial density one to two orders of magnitude higher, with practical sensor budgets and scan speeds. The MRCSBF technique produces array sidelobe rejection that approaches the theoretical array pattern of a continuous two-dimensional (2D) aperture. The implications of this finding are that better source localization may be achieved with conventional delay and sum (DAS) beamforming (BF) with practical sensor budgets, and that an improved starting image of the sound source can be provided to deconvolution algorithms. These findings are demonstrated on analytical and experimental examples from a low-cost rotating phased array using point sound sources, as well as linear scanning array experiments of an impinging jets point source and a near-sonic jet nozzle exhaust.