Andere Kunden interessierten sich auch für
![Analysis of Cost Growth in U.S. Air Force Base Support Function Contracts]( "Analysis of Cost Growth in U.S. Air Force Base Support Function Contracts")
Analysis of Cost Growth in U.S. Air Force Base Support Function Contracts60,99 €![Estimating Procurement Cost Growth Using Logistic and Multiple Regression]( "Estimating Procurement Cost Growth Using Logistic and Multiple Regression")
Estimating Procurement Cost Growth Using Logistic and Multiple Regression60,99 €![Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression]( "Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression")
Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression60,99 €![Logistic and Multiple Regression: The Two-Step Approach to Estimating Cost Growth]( "Logistic and Multiple Regression: The Two-Step Approach to Estimating Cost Growth")
Logistic and Multiple Regression: The Two-Step Approach to Estimating Cost Growth60,99 €![Creating Cost Growth Models for the Engineering and Manufacturing Development Phase of Acquisition Using Logistic and Multiple Regression]( "Creating Cost Growth Models for the Engineering and Manufacturing Development Phase of Acquisition Using Logistic and Multiple Regression")
Creating Cost Growth Models for the Engineering and Manufacturing Development Phase of Acquisition Using Logistic and Multiple Regression60,99 €![An Image-Based Bidirectional Reflectivity Distribution Function Experiment]( "An Image-Based Bidirectional Reflectivity Distribution Function Experiment")
An Image-Based Bidirectional Reflectivity Distribution Function Experiment61,99 €![Multiple Model Adaptive Estimation for Time Series Analysis]( "Multiple Model Adaptive Estimation for Time Series Analysis")
Multiple Model Adaptive Estimation for Time Series Analysis60,99 €
To estimate the state of a maneuvering target in clutter, a tracking algorithm must becapable of addressing measurement noise, varying target dynamics, and clutter. Traditionally, Kalman filters have been used to reject measurement noise, and their multiple model form can accurately identify target dynamics. The Multiple Hypothesis Tracker (MHT), a Bayesian solution to the measurement association problem that retains the probability density function of the target state as a mixture of weighted Gaussians, offers the greatest potential for rejecting clutter, especially when based on an advanced mixture reduction algorithm (MRA) such as the Integral Square Error (ISE) cost function.This research seeks to incorporate multiple model filters into an ISE cost-function based MHT to increase the fidelity of target state estimation.