You might be interested by the Orfeo Toolbox which might have some useful feature for you (i only know about the tool, not the detailed procedure).
Orfeo ToolBox (OTB) is an open-source project for state-of-the-art
remote sensing. Built on the shoulders of the open-source geospatial
community, it can process high resolution optical, multispectral and
radar images at the terabyte scale. A wide variety of applications are
available: from ortho-rectification or pansharpening, all the way to
classification, SAR processing, and much more!
All of OTB’s algorithms are accessible from Monteverdi, QGIS, Python,
the command line or C++. Monteverdi is an easy to use visualization
tool with an emphasis on hardware accelerated rendering for high
resolution imagery (optical and SAR). With it, end-users can visualize
huge raw imagery products and access all of the applications in the
toolbox. From resource limited laptops to high performance MPI
clusters, OTB is available on Windows, Linux and Mac. It is community
driven, extensible and heavily documented.
You say in one of your comment : "the data is in raw instrument swath projection". You might specifically be interested by the Orfeo Toolbox recipes structured in articles and with code examples :
From raw image to calibrated product
This section presents various pre-processing tasks that are presented
in a classical order to obtain a calibrated, pan-sharpened image.
Optical radiometric calibration
Digital Elevation Model management
Ortho-rectification and map projections
In the same area, one more page should help you out :
Image registration is a fundamental problem in image processing. The
aim is to align two or more images of the same scene often taken at
different times, from different viewpoints, or by different sensors.
It is a basic step for orthorectification, image stitching, image
fusion, change detection, and others.
Sensor model is generally not sufficient to provide image
registrations. Indeed, several sources of geometric distortion can be
contained in optical remote sensing images including earth rotation,
platform movement, non linearity, etc.
They result in geometric errors on scene level, image level and pixel
level. It is critical to rectify the errors before a thematic map is
generated, especially when the remote sensing data need to be
integrated together with other GIS data.