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Tensor Invariant Processing for Munitions/Clutter Classifications Interim Report on SNR and Background Leveling Requirements

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Interim rept.

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The intent of this research project is to explore alternatives to conventional dipole inversion for extracting target features from multi-axis EMI sensor array data. Conventional dipole inversion searches for the target parameter values location and polarizabilities which minimize the difference between measured signals and those calculated using the dipole response model. Here, we consider an alternative approach that seeks to determine the parameter values which minimize an objective function based on the dispersion in estimates of the target s polarizability using different combinations of transmitters and receivers. A fortiori the approach allows for direct calculation of the uncertainty in the estimated polarizability. This interim report documents results on the convergence properties of a downhill simplex based algorithm for determining a target s location and polarizabilities using this approach. Specifically we examined convergence of the algorithm for data collected with the 2x2 TEM array at the former Camp Beale in 2011 and found no impact due to signal-to-noise ratio SNR and background leveling effects. However, the minimum polarizability dispersion does vary systematically with SNR targets with higher SNR tend to have less uncertainty dispersion in the polarizability estimate than those with lower SNR. Testing shows that polarizability dispersion based inversion can produce more accurate polarizabilities than conventional dipole inversion in some cases. However, the fraction of targets in the ESTCP classification demonstrations that cannot be accurately analyzed using conventional dipole inversion may be small enough 5 that modest improvements in calculating the polarizability are likely to have very little effect on classification performance.

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  • Theoretical Mathematics
  • Electricity and Magnetism

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