Are you developing an atmospheric remote sensing
instrument, maybe one based on absorption spectroscopy?Predicting the actual performance of a remote sensing system is a
difficult multidisciplinary task that requires knowledge of many
fields:
- Inverse methods: Mathematical foundations, numerical methods, prior selection, bias and precision analysis
- Radiative transfer: Spectroscopy, atmospheric physics, profile representation, surface modeling
- Focal plane array modeling: Quantum efficiency, noise modeling, effects of readout electronics
- Optics: Radiometry, distortions and aberrations, stray light
- Space observation geometry: Orbital motion and manoeuvers, stability, terrain representation, refraction
This specialized knowledge can only properly be acquired through experience.Having provided services to multiple companies, including level 0 to Level 4 algorithms, I can help you
with the following:
- Instrument optical design, performance estimation and optimization
- Design and implementation of complete end-to-end toolchains including
retrieval algorithms, instrument and observation simulators
- On-board calibration systems
- Requirements, architecture and development for optical, electronical and
software aspects
- Focal plane array characterization and modeling
- Optical modeling, including stray light, ghosting, polarization, spectral effects
- Gas plume detection and quantification estimates
Recently, I have started studying muon-based remote sensing.
This non-optical, density-based sensing modality is particularly
useful in geophysical exploration. Here is an online tool
(under development) for exploring muon sensing and comparing
it to gravimetry, in the context of dense orebody exploration:
Muography vs. gravimetry evaluation tool