Parametric analysis of target/decoy performance
Abstract
As infrared sensing technology matures and the development of space-based optical sensors
becomes feasible, interest has grown in protecting both ballistic and orbiting objects from detection by
optical sensors. Such sensors may have high spatial resolution and sense in several wavelength bands
simultaneously. This has lead to an increasing interest in the development and analysis of optical decoys
that will prevent identification of high value objects in space.
This paper describes an analytical approach to the parametric analysis of target/decoy
discrimination performance as a function of various controllable object characteristics.
This analysis tool can be used to answer the question, "how distinct in physical characteristics do a
target and decoy have to be before they can be easily discriminated?" Three main characteristics of the
objects are considered in this analysis: temperature, projected area, and rate of rotation. These
characteristics are given assumed models for their statistics and described by a set of parameters including
their first and second order moments.
Based upon the statistical parameters and models for the object characteristics, a set of equations
are derived to compute the mean and covariance of the optical signature as seen by a sensor for the decoy
and target classes. An estimate of the classification performance between the classes is made using a
function of a statistical distance measure. This estimate is used as a performance measure in a parameter
tradeoff analysis during an example decoy concept development process. While a purely analytical
approach such as this lacks the fidelity of a sophisticated simulation model, it is computationally much
simpler and is most appropriately applied during decoy concept development before the application of
more rigorous simulation-based analysis.