A comparison of several nonlinear filters for ballistic missile tracking on re-entry

被引：0

作者：

Singh, Nikhil Kumar ^{[1
]}

Bhaumik, Shovan ^{[2
]}

Bhattacharya, Samar ^{[1
]}

机构：

[1] Jadavpur Univ, Dept Elect Engn, Kolkata 700032, India

[2] Indian Inst Technol Patna, Dept Elect Engn, Patna, Bihar, India

来源：

2016 IEEE FIRST INTERNATIONAL CONFERENCE ON CONTROL, MEASUREMENT AND INSTRUMENTATION (CMI) | 2016年

关键词：

component; ballistic missile; missile tracking; cubature Kalman filter; cubature quadrature Kalman filter; Gauss-Hermite filter; sparse-grid Gauss-Hermite filter; ensemble Kalman filter; unscented Kalman filter; KALMAN FILTER; QUADRATURE; ALGORITHMS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, ballistic missile tracking on re-entry has been considered. Position, velocity and ballistic coefficient are considered as states of the target. As no prior information about the target shape, mass and area is available, ballistic coefficient of the target has been considered as a state variable. Different type of nonlinear filters such as ensemble Kalman filter (EnKF), unscented Kalman filter (UKF), Gauss-Hermite filter (GHF), sparse-grid Gauss-Hermite filter (SGHF), cubature quadrature Kalman filter (CQKF) are used to estimate states of the target. The performance of all the above mentioned filters has been compared on the basis of estimation accuracy, computational time and missed distance. The 3 points GHF provides lowest miss distance at reasonably low computational time; so GHF-3 is recommended for this problem.

引用

页码：459 / 463

页数：5

共 14 条

[1]

[Anonymous], 2003, Ocean Dynamics, DOI [10.1007/s10236-003-0036-9, DOI 10.1007/S10236-003-0036-9]

[2] Nonlinear Kalman filtering algorithms for on-line calibration of dynamic traffic assignment models [J].

Antoniou, Constantinos ;

Ben-Akiva, Moshe ;

Koutsopoulos, Haris N. .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2007, 8 (04) :661-670

[3] Discrete-time nonlinear filtering algorithms using Gauss-Hermite quadrature [J].

Arasaratnam, Ienkaran ;

Haykin, Simon ;

Elliott, Robert J. .

PROCEEDINGS OF THE IEEE, 2007, 95 (05) :953-977

[4] Cubature quadrature Kalman filter [J].

Bhaumik, Shovan ;

Swati .

IET SIGNAL PROCESSING, 2013, 7 (07) :533-541

[5]

Chalasani G., 2012, P IEEE ICIEA JUL

[6] Tracking a ballistic target: Comparison of several nonlinear filters [J].

Farina, A ;

Ristic, B ;

Benvenuti, D .

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2002, 38 (03) :854-867

[7]

Jia B., 2010, P IEEE ACC JUL

[8] Sparse-grid quadrature nonlinear filtering [J].

Jia, Bin ;

Xin, Ming ;

Cheng, Yang .

AUTOMATICA, 2012, 48 (02) :327-341

[9] An Iterative Ensemble Kalman Filter [J].

Lorentzen, Rolf J. ;

Naevdal, Geir .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2011, 56 (08) :1990-1995

[10] COMPARISON OF SEVERAL NONLINEAR FILTERS FOR REENTRY VEHICLE TRACKING [J].

MEHRA, RK .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1971, AC16 (04) :307-&

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