Launch Point Estimation for a Ballistic Missile using the Phase Division Least Square Method
نویسندگان
چکیده
منابع مشابه
Airborne Boost-Phase Ballistic Missile Defense
Boost-phase ballistic missile defense is alluring because rocket boosters are easy to detect and track, they are relatively vulnerable due to the large axial loads on a missile under powered flight, the entire payload (single or multiple warheads and midcourse penetration aids) may be destroyed in a single shot, and countermeasures to defeat boostphase defense are more difficult to devise than ...
متن کاملDistributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements
Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...
متن کاملSoftware for Ballistic Missile Defense
A battle management system for comprehensive ballistic missile defense must perform with near perfection and extraordinarily reliability. It will be complex to an unprecedented degree, untestable in a realistic environment, and provide minimal time for human intervention. The feasibility of designing and developing such a system (requiring upwards of ten million lines of code) is examined in li...
متن کاملA Note on Change Point Detection Using Weighted Least Square
This paper is concerned with the application of weighted least square method in change point analysis. Testing shift in the mean normal observations with time varying variances as well as of a GARCH time series are considered. For both cases, the weighted estimators are given and their asymptotic behaviors are studied. It is also described that how the resampling methods like Monte Carlo and bo...
متن کاملUsing an Efficient Penalty Method for Solving Linear Least Square Problem with Nonlinear Constraints
In this paper, we use a penalty method for solving the linear least squares problem with nonlinear constraints. In each iteration of penalty methods for solving the problem, the calculation of projected Hessian matrix is required. Given that the objective function is linear least squares, projected Hessian matrix of the penalty function consists of two parts that the exact amount of a part of i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Institute of Control, Robotics and Systems
سال: 2014
ISSN: 1976-5622
DOI: 10.5302/j.icros.2014.13.1948