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Updated: Dec 8, 2025

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
Published on: July 30, 2020
Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve
Stephan Orzada1,2, Thomas M Fiedler3, Andreas K Bitz4
1Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Kokereiallee 7, 45141, Essen, Germany. Stephan.orzada@uni-due.de.
Objective:
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Method:
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Result:
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
Conclusion:
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
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