Polarimetric detection for slowly moving/stationary targets in inhomogeneous environments

Charles Hsu; Howard Mendelson; Albert Burgstahler; Dan Hibbard; Jim Faist

doi:10.1117/12.889220

3 June 2011 Polarimetric detection for slowly moving/stationary targets in inhomogeneous environments

Charles Hsu, Howard Mendelson, Albert Burgstahler, Dan Hibbard, Jim Faist

Proceedings Volume 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX; 80581G (2011) https://doi.org/10.1117/12.889220
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The detection of slowly moving/stationary targets in a heavy-clutter environment is a challenging problem in a surveillance system. Recent researches [1-3] illustrate that polarization diversity can provide a measure to detect the symmetry of a target in inhomogeneous clutter, especially when discrimination by Doppler effects is not possible, and detection performance could be further enhanced if the polarization of transmitted signal is optimally selected to match the target polarimetric aspects. In this paper, we address the challenges of threat detection in inhomogeneous clutter such as in the riverine wetland environment. Second, a local sequential polarimetric diversity algorithm using dual (horizontal and vertical) polarizations is presented to calculate the singularity of polarization diversity for potential threat detection. The singularity of polarization diversity is a measure to discriminate the difference (less similarity) of targets from the neighborhood (background), which area can be decided by the size of the sliding processing window. Next, a field test using a Vector Network Analyzer collected dual-polarized scatterings of targets and accomplished a multiple frequency band (200 MHz - 18 GHz from UHF to Ku bands) threat characterization and detection on the same stationary threats. Finally, we show the testing result using the local sequential polarimetric diversity algorithm to detect potential threats in inhomogeneous environments.

Citation Download Citation

Charles Hsu, Howard Mendelson, Albert Burgstahler, Dan Hibbard, and Jim Faist "Polarimetric detection for slowly moving/stationary targets in inhomogeneous environments", Proc. SPIE 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX, 80581G (3 June 2011); https://doi.org/10.1117/12.889220

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