On-line Flagging of Anomalies and Adaptive Sequential Hypothesis Testing for Fine-feature Characterization of Geosynchronous Satellites

نویسندگان

  • Anil Chaudhary
  • Tamara Payne
  • Kimberly Kinateder
  • Phan Dao
  • Elizabeth Beecher
  • Derek Boone
  • Brittany Elliott
  • Hailey Billing
چکیده

The objective of on-line flagging in this paper is to perform an interactive assessment of geosynchronous satellites anomalies such as cross-tagging of satellites in a cluster, solar panel offset change, etc. This assessment will utilize a Bayesian belief propagation procedure and will include an automated update of the baseline signature data for the satellite, while accounting for the seasonal changes. Its purpose is to enable an ongoing, automated assessment of satellite behavior through its life cycle using the photometry data collected during the synoptic search performed by a ground or space-based sensor as a part of its metrics mission. The change in the satellite features will be reported along with the probabilities of type I and type II errors. The objective of adaptive sequential hypothesis testing in this paper is to define future sensor tasking for the purpose of characterization of fine features of the satellite. The tasking will be designed in order to maximize new information with the least number of photometry data points to be collected during the synoptic search by a ground or space-based sensor. Its calculation is based on the utilization of information entropy techniques. The tasking is defined by considering a sequence of hypotheses in regard to the fine features of the satellite. The optimal observation conditions are then ordered in order to maximize new information about a chosen fine feature. The combined objective of on-line flagging and adaptive sequential hypothesis testing is to progressively discover new information about the features of geosynchronous satellites by leveraging the regular but sparse cadence of data collection during the synoptic search performed by a ground or space-based sensor. 1 Applied Optimization, Inc. 714 East Monument Ave, Suite 204 Dayton, OH 45402 2 Wright State University 3640 Colonel Glenn Hwy, Dayton, OH 45435 3 Air Force Research Laboratory Space Vehicles Directorate Kirtland AFB, Albuquerque, NM 87117 4 Air Force Research Laboratory Sensors Directorate Wright Patterson AFB, Dayton, OH 45433

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function

Introduction In recent years methods based on radio frequency waves have been used for detecting breast cancer. Using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. Materials and Methods In this paper, a new method is introduced for detection of backscattered signals which are received by...

متن کامل

A New Method for Characterization of Biological Particles in Microscopic Videos: Hypothesis Testing Based on a Combination of Stochastic Modeling and Graph Theory

Introduction Studying motility of biological objects is an important parameter in many biomedical processes. Therefore, automated analyzing methods via microscopic videos are becoming an important step in recent researches. Materials and Methods In the proposed method of this article, a hypothesis testing function is defined to separate biological particles from artifact and noise in captured v...

متن کامل

Predicting Flow Number of Asphalt Mixtures Based on the Marshall Mix design Parameters Using Multivariate Adaptive Regression Spline (MARS)

Rutting is one of the major distresses in the flexible pavements, which is heavily influenced by the asphalt mixtures properties at high temperatures. There are several methods for the characterization of the rutting resistance of asphalt mixtures. Flow number is one of the most important parameters that can be used for the evaluation of rutting. The flow number is measured by the dynamic creep...

متن کامل

Novel Radial Basis Function Neural Networks based on Probabilistic Evolutionary and Gaussian Mixture Model for Satellites Optimum Selection

In this study, two novel learning algorithms have been applied on Radial Basis Function Neural Network (RBFNN) to approximate the functions with high non-linear order. The Probabilistic Evolutionary (PE) and Gaussian Mixture Model (GMM) techniques are proposed to significantly minimize the error functions. The main idea is concerning the various strategies to optimize the procedure of Gradient ...

متن کامل

Adaptive Predictive Controllers Using a Growing and Pruning RBF Neural Network

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015