Coherent array imaging using phased subarrays

This research was motivated by the need to reduce the front-end hardware complexity of 3D ultrasound imaging systems using 2D transducer arrays. The results apply to other coherent array imaging applications including sonar, radio astronomy, and seismic imaging. Conventional full phased array (FPA) imaging requires parallel front-end electronic hardware to process the signals from each element independently. While currently used for commercial 2D ultrasound imaging using 1D transducer arrays, FPA imaging does not scale well to 3D imaging due to the overwhelming number of transducer elements.; Phased subarray (PSA) imaging has been proposed as a method to reduce the imaging system's front-end hardware complexity while achieving near-FPA image quality. Each scan line is formed using multiple subsets of adjacent elements—subarrays—that span the full array. PSA imaging reduces the number of front-end hardware channels to the number of elements in the subarray.; This dissertation extends the capabilities of PSA imaging. A mathematical model of the imaging response in the spatial domain and spatial frequency domain, or k-space, is developed for PSA imaging. This model is used as the basis for two new methods of designing subarray reconstruction filters for wideband PSA imaging.; PSA and FPA imaging are compared using experimental data for 2D imaging and simulated data for 3D imaging. Experimental images were formed of a wire phantom using a 128-element capacitive micromachined ultrasound transducer array. PSA imaging had little or no affect on the axial resolution and little or no effect on the lateral resolution within the focal region. The SNR of the PSA images was slightly lower than that of the FPA images when using 32-element subarrays, and decreased for smaller subarrays. The contrast-to-noise ratio of PSA and FPA imaging was compared using simulated pulse-echo data of a cyst phantom and was slightly lower for all PSA imaging methods. The results illustrate that PSA imaging reduces the front-end hardware complexity and can enable real-time 3D ultrasound imaging.