You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
16 April 2008Spectral gating in hyperspectral-augmented target tracking
Hyperspectral images provide scientists and engineers with the capability of precise material identification in
remote sensing applications. One can leverage this data for precise track identification (ID) and incorporate the
high-confidence ID in the tracking process. Our previous work demonstrates that hyperspectral-aided tracking
outperforms kinematic-only tracking where multiple ambiguous situations exist. We develop a novel gating concept
for hyperspectral measurements, similar in concept to the gating of the Mahalanobis distance computed
from the Kalman residuals. Our spectral gating definition is based on the distance between the spectral distribution
of the class ID of a track and the spectral distribution of the class ID resulting from the classification
of a measurement. We further incorporate the distance between each class distribution (in spectral space) in
the track association portion of our hyperspectral-aided tracker. Since functional forms of the joint probability
distribution function do not exist, similarity measures such as the Kullback-Leibler divergence or Bhattacharyya
distance cannot be used. Instead, we compute all pair-wise distances between all samples of the two classes and
then summarize these distances in a meaningful way. This article presents our novel spectral gating approach
and its use in track association. It further explores different similarity measures and their effect on spectral
gating and track association.
The alert did not successfully save. Please try again later.
Neil A. Soliman, Michael J. Mendenhall, Juan R. Vasquez, "Spectral gating in hyperspectral-augmented target tracking," Proc. SPIE 6969, Signal and Data Processing of Small Targets 2008, 696907 (16 April 2008); https://doi.org/10.1117/12.777590