Evaluation of CST Studio Suite for simulation of radar cross-section

Detta är en Uppsats för yrkesexamina på avancerad nivå från Umeå universitet/Institutionen för fysik

Författare: Jonas Lindgren; [2021]

Nyckelord: CST; RCS;

Sammanfattning: When designing military vehicles, it is of interest to make the vehicles difficult to detect using radar. The radar cross-section (RCS) property indicates how easily a vehicle is detected by radar and should thus be minimized. However, the RCS of a vehicle represents the cross-sectional area of a perfectly reflecting sphere that would produce the same reflection strength as the vehicle in question. Since this is extremely complicated to calculate as military vehicles are quite complex, these calculations are performed using computational simulations. BAE Systems Hägglunds is looking into changing from their current simulation software OPTISCAT to CST Studio Suite and thus want to know how CST performs and compares against OPTISCAT. In this work, we show that CST obtains results within 2% of theoretical data when simulating a sphere and a slab. When simulating vehicles, the RCS difference between the two software is from 3% to 55% while showing similar general behavior. Results indicate that CST performs well when simulating simple objects but deviates from OPTISCAT when simulating the vehicle. It is not surprising that the software does not match up perfectly since they use different theoretical approaches, OPTISCAT uses physical optics while CST an extension to physical optics called the Shooting Bouncing Ray method. Even though the software differs to this extent it is most likely possible that CST can be a suitable replacement for OPTISCAT. When looking at RCS the important part is the location of spikes and since they have similar general behavior, those spikes may still be possible to identify. This thesis will hopefully act as a starting point for further examination of CST as a software for simulating RCS, for example by comparing results from CST to experimentally measured data. Hopefully it will also be used to improve the design process of making military vehicles harder to detect.

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