The tomographic scanning (TOSCA) imager was invented by the author in 2003. Initially, the system was based on
reconstructing an image from the signal of a simple single pixel, conical scan FM-reticle sensor using tomographic
techniques. Although the system has been used for several decades for real-time tracking purposes, the imaging
properties of the single pixel conical scan reticle system was left undiscovered until recently, although multi-target
discrimination was demonstrated with multi-spectral versions of the system. The initial system presented by the author
demonstrated the ability to discriminate between multiple spots in the field of view in a fairly simple scenario.
Advances have been made in both theory and technology, mainly with the introduction of the nutating circular aperture
in the scanning optics, and the use of Fourier transform ramp filters during reconstruction, and TOSCA is in principle
found to be a perfect imaging system, only limited by practical aspects such as the number of angular scans, the spatial
sampling, noise and vibration. The simplicity of the hardware, together with the rapid advances in high performance,
low cost computing means the system has a potential for low-cost applications such as in expendable multi-spectral
thermal imagers. This paper will present the current state of the technology, including improvements in algorithms and reticle shapes, and
look at artefacts found in various images due to different geometries, as well as ways to handle these artefacts. Several
noise generating processes and their effects will be presented and illustrated with results from digital simulations.
Requirements for image processing in terms of computing power are investigated, together with the potential for