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This paper presents an analytic method for synthetic-aperture inversion when the measurements are corrupted with noise and clutter. We use microlocal analysis in a statistical setting to develop filtered-backprojection-type reconstruction methods. The inversion method is applicable in non-ideal scenarios, such as those involving arbitrary source(More)
— It is well known that motor current is a nonsta-tionary signal, the properties of which vary with respect to the time-varying normal operating conditions of the motor. As a result, Fourier analysis makes it difficult to recognize fault conditions from the normal operating conditions of the motor. Time–frequency analysis, on the other hand, unambiguously(More)
We consider a monostatic synthetic aperture radar system traversing an arbitrary trajectory on a non-flat topography. We present a novel edge detection method applicable directly to SAR received signal. Our method first filters the received data, and then backprojects. The filter is designed to detect the edges of the scene in different directions at each(More)
We develop a new passive image formation method capable of exploiting information about multiple scattering in the environment, as well as statistics of the objects to be imaged, additive noise and clutter, using measurements from a sparse array of receivers that rely on illumination sources of opportunity. The array of receivers can be distributed(More)
We derive a new image reconstruction method for distributed apertures operating in complex environments. The aperture elements can be distributed spatially in an arbitrary fashion, can be several hundred wavelengths apart, and can involve transmission from multiple elements simultaneously. Moreover, the object to be imaged can be either in the near-field or(More)
We derive an optimal transmit waveform for filtered backprojection-based synthetic-aperture imaging. The waveform is optimal in terms of min-imising the mean square error (MSE) in the resulting image. Our optimization is performed in two steps: First, we consider the minimum-mean-square-error (MMSE) for an arbitrary but fixed waveform, and derive the(More)
Diffuse optical tomography (DOT) in the near infrared involves the reconstruction of spatially varying optical properties of a turbid medium from boundary measurements based on a forward model of photon propagation. Due to the nonlinear nature of DOT, high quality image reconstruction is a computationally demanding problem which requires repeated use of(More)
In this work, we present spatially resolved pharmacokinetic rate images of indocyanine green (ICG) obtained from three breast cancer patients using near infrared imaging methods. We used a two-compartment model, namely, plasma and extracellular extravascular (EES), to model ICG kinetics around the tumor region. We introduced extended Kalman filtering (EKF)(More)