Resolution and sidelobe structure analysis for RF tomography

Radio frequency (RF) tomography utilizes a net work of spatially diverse sensors to trade geometric diversity for bandwidth, permitting images to be formed with narrowband waveforms. Such a constellation of sensors produces a sparsely and irregularly spaced set of Fourier space samples, complicating the definition and analysis of resolution for these systems. We present an analysis of resolution for RF tomography based on the Cramer Rao Bound (CRB) for estimation of target position and velocity. This approach allows the resolution for a given sensor configuration to be determined with minimal computational cost, thus providing a useful design tool for sensor placement and frequency selection for RF tomography. We also explore the impact of Fourier space "filling" with bistatic geometries on sidelobe structure of the ambiguity function. Several simulation results are presented to validate the resolution calculations from the CRB and to illustrate the importance of sensor placement for RF tomographic imaging.