Accuracy are always relative terms. especially if one deals with classification. But if one wish for somewhat scientifically sound method, something has to be done. Errors are meant to be corrected through discussions.

The rest of the variables are in the “Pre-calculated variables” tab. There you can find the “working nuts and bolts” of the spreadsheet. It automatically estimates the loss budget, system noise temperatures and model some losses. The section in green can be edited but it can be left as is. I concept the sheet to be usable where the users can easily input variables they can find in the open source literature which usually very limited and let the sheet estimate rest of it.

For the MDS it always start from estimates of the system temperatures. This part of the sheet will estimate the system temperature.

The loss budget.

Most part are editable but can be left as is. The value are taken from typical loss value for radar in books like Radar Technology Encyclopedia and Basic Radar Analysis.

And this section is the important one as it consolidate and attempt to model pulse integrations. Here you can find how many pulses received and integrated.

And then estimates of fluctuation loss.

Other variables like weather attenuation and prediction of radar receiver noise figure can be found in the Atmospheric loss tab :

This part of worksheet are meant to be automated, it will estimate its own variables based on interpolations and simplified K.Barton model.

Another “automated part” is in the “Weighting algorithm” tab. Here you can find various tables regarding the antenna and supports for the drop down menus on the main sheet

In this sheet calculations of antenna dwell time and numbers of beams are carried out.

The simple shape would easily follows the wavelength dependency.Complex geometry Aircraft.. that could be a long way.

My paper search so far however was not lucky. My idea is to try actually make various shapes and run it through computer modeling then attempt to relate it to the natural wavelength dependence. However I’m limited to the code that available to me. POFACETS alone might not be enough.

1-This isn’t a big issue but i think it will be easier to use if you let the user input frequency in Ghz instead of Wavelength in meters.
2- I think the estimation of RCS difference might still be too big, at least for VLO aircraft.
Recently re-surfaced video (posted by mig31) indicate that at distance of 30 km, P-18 can’t detect F-117 with 3 out 4 of its frequency setting.

1.I agree thanks. Although i think MHz would be better.

2.As i mentioned at post predating the update post. The approximation works best for simple shapes, though my observation suggest that it might be applicable to real aircraft. That is of course limitations which i assume the user would be aware of. It may over-predict the possible RCS value. The problem is of course i haven’t able yet to find a good “fudge factor” to take account of such uncertainties. Lowering the dB value based on the XST image might work but will it be applicable to any other object ?. Thus why i release the sheet as is.

Rough extrapolate from the table
If radar height was 6.35 meters, P-18 will detect targets with RCS= 2.5 m2, cruising at 6km altitude from 132.5 km, reduce RCS by 10 times and we get 44% detection range reduction so F-117 RCS is smaller than 0.025m2 at frequencies >140 Mhz.
If radar height was 10.35 meters, P-18 will detect targets with RCS= 2.5 m2, cruising at 6km altitude from 180 km, reduce RCS by 10 times and we get 44% detection range reduction so F-117 RCS is smaller than 0.0025m2 at frequencies >140 Mhz.

Do you have any suggestion on possible fudge factor ?

Your extrapolation however i found rather complicated mainly because it requires vertical coverage diagram and taking account of multipath. These would make it hard to apply any result of the extrapolation in other radar, which may have different lobing structure on its vertical coverage.