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Another food for thought i would like to present is the Radar Cross Section variable. This topic is admittedly very complex yet unavoidable if one wish to actually make better guesswork on radar performance. The big question is "What RCS value i have to fill for the variable ?". Given the multiple dependence nature of RCS. 0.001 sqm in one frequency would not be valid in another and one may not always have access to more complex modeling or information. Especially if one wish to do the assessment for low observable target.
As we know that there is wavelength dependency of RCS, i concentrated my efforts towards it. The "Radar Cross Section 2nd Edition" book by Knott and Tuley had the squared wavelength dependency, which need to be understood as base. It turns out that the dependency is basically a base 20 Logarithm of the frequency in question subtracted by the "target frequency". Example of use.
We have an object designed to have 0.001 sqm or -30 dB RCS in 3 cm wavelength, what's the likely RCS in L-band of 24 cm ?
We first do some logarithm works :
The 3 cm band (0.03 m)
20*LOG(0.03) = -30
Then the 24 cm band (0.24 m)
20* LOG(0.24) = -12
The we subtract the first band with second one. Thus. -30-(-12)=-18 Now we see the 18 dB difference. We can further subtract the RCS of the object in dB with the resulted value from our first equation.
RCS in L-band= -30-(-18)
RCS in L-band = -12 dB or 0.06 Sqm.
There are however always an exception as one cannot generally use the squared wavelength dependence on all stealth objects. As described in following papers :
and for those who interested in promises and features of low frequency radars the 2nd part of the paper
The squared wavelength dependence appears to only applies toward conical object or ogival, which would make it suitable for predicting missile weapon RCS. Other military systems which does not exhibit such shape might follow wavelength dependence (which if one interested can be run down with same procedure i described BUT using 10 as multiplier instead of 20).
and now the question is "Which dependence i should use to fill ?" This is mostly based on my own simple observation. Based on what was available, especially with this famous image, courtesy of secretprojects.
The object with many facets (the lockheed Have Blue) appears to follow the squared wavelength dependence while the Northrop XST which incorporates some curvi-linear elements (This feature would be observed in subsequent stealth fighters and missiles like YF-23A and B-2). One can see the dependence from the difference of RCS between high band (the X-K band) with the one in the lower 175 MHz band. The faceted have blue have 30 dB more RCS which quite close to the squared wavelength approximation (which put 34-39 dB of difference) The Northrop XST in other hand have 8 dB of difference which close to wavelength dependence (the procedure will give 17 dB of difference which basically 50% more).
This is admittedly subjective and would cause confusion. As there is no real measure to "see" how faceted or curved an objects are.
Another thing with the procedure i described above, one may find the conventional target to have "lower" RCS value in low band radar. Say 3 sqm fighter in X-band become 0.04 Sqm in L-band. This is not because the fighter is stealth, but it can be explained by simple antenna-beamwidth relationship. If we take aircraft as simple plane and expose it to radio signal of increasing wavelength, one might observe that as the wavelength grow, the reflected power would be weaker (thus lower RCS) One can see this in real life measurement of conventional aircraft RCS.
Further observation or suggestion however is appreciated.
My other observation toward shapes however still suggest that somewhat, even curvilinear shape can still follow squared wavelength dependency. This is the aircraft based on Tacit Blue. Frontal area RCS on multiple frequencies.
The aircraft :
RCS in Multiple frequencies.
Notice the 25 dB diffrence between X band and the VHF band.
My take on the matter however is to use both wavelength dependence to establish "best and worst" case approximation of the RCS of the object. Where the wavelength is best case and squared wavelength serve as worst. Then calculate detection range based on both values in the spreadsheet to generate possible detection range.