Synthetic Aperture Radar (SAR) is a valuable tool for acquiring information about landscapes through forming two-dimensional images remotely. SAR has useful applications for defense, intelligence, humanitarian, and urban planning efforts, among others. Because of increased competition for suitable transmission frequencies in the electromagnetic spectrum from wireless communication corporations, passive bistatic radar has been extensively studied over the last few decades as a means of circumventing that obstacle. However, it does not come without its own introduced challenges - because telecommunication waveforms are continually changing, that variability introduces a large computational burden. In order to model data generation in a simulation environment, it is necessary to develop processing methods that will perform in a timely manner. In this work we present the Reverse Backprojection Algorithm, derived from the adaptable, commonly-used, yet brute force backprojection imaging algorithm, as a novel approach to generate simulated passive bistatic SAR data. To demonstrate the algorithm's effectiveness, we conduct a variety of simulations employing 4G Long Term Evolution (LTE) waveforms. Because LTE waveforms are not designed for radar usage, self-ambiguities within the waveform autocorrelation function degrade image quality. Simulations performed on point scatterers and distributed scenes illustrate these introduced artifacts, and meaningful comparisons are provided to determine which configurations more suited for SAR operation and identify additional processing needs.