PRACTICAL DEMONSTRATION OF TRACK-TO-TRACK DATA ASSOCIATION USING THE BHATTACHARYYA DIVERGENCE

被引：0

作者：

Roscoe, Christopher W. T. ^{[1
]}

Hussein, Islam I. ^{[1
]}

Gerber, Joseph D. ^{[1
]}

Stauch, Jason ^{[1
]}

Kelecy, Tom ^{[1
]}

Wilkins, Matthew P. ^{[1
]}

Schumacher, Paul W., Jr. ^{[2
]}

机构：

[1] Appl Def Solut Inc, 10440 Little Patuxent Pkwy,Suite 600, Columbia, MD 21044 USA

[2] Air Force Res Lab, 535 Lipoa Pkwy,Suite 200, Kihei, HI 96753 USA

来源：

SPACEFLIGHT MECHANICS 2017, PTS I - IV | 2017年 / 160卷

关键词：

D O I：

暂无

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

Building and maintaining a space object catalog requires rigorous methods for data association in order to maintain consistent object custody. There are three primary types of data association of interest in space surveillance: the observation-totrack association (OTTA) problem, the observation-to-observation association (OTOA) problem, and the track-to-track association (TTTA) problem. Recent work in the community has suggested the use of a number of information theoretic quantities as metrics for performing data association. This work presents a practical demonstration of using one of these quantities, the Bhattacharyya divergence, for TTTA in a small GEO catalog generation and maintenance exercise fed by data from a consortium of commercial electro-optical sensor providers. The Air Force Research Lab-developed Constrained Admissible Region-Multiple Hypothesis Filter (CAR-MHF) is used for primary orbit determination and track maintenance, including solving the OTTA and OTOA problems.

引用

页码：2135 / 2147

页数：13

共 50 条

[1] On Track-to-Track Data Association for Automotive Sensor Fusion
Duraisamy, Bharanidhar
Schwarz, Tilo
Woehler, Christian
[J]. 2015 18TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2015, : 1213 - 1222
[2] Mixing kinematics and identification data for track-to-track association
Leibowicz, I
Nicolas, P
[J]. SENSOR FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS III, 1999, 3719 : 288 - 299
[3] Probabilistic Track-to-Track Association
Zajic, Tim
[J]. SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXIV, 2015, 9474
[4] TRACK-TO-TRACK ASSOCIATION USING INFORMATION THEORETIC CRITERIA
Hussein, Islam I.
Roscoe, Christopher W. T.
Wilkins, Matthew P.
Schumacher, Paul W., Jr.
[J]. ASTRODYNAMICS 2015, 2016, 156 : 203 - 212
[5] Track-to-track association using informative prior associations
Danu, Daniel G.
Sinha, Abhijit
Kirubarajan, Thiagalingam
[J]. SIGNAL AND DATA PROCESSING OF SMALL TARGETS 2007, 2007, 6699
[6] Track-to-track association and bias removal
Stone, LD
Williams, ML
Tran, TM
[J]. SIGNAL AND DATA PROCESSING OF SMALL TARGETS 2002, 2002, 4728 : 315 - 329
[7] Track-to-track association using a phase-only filter
Stubberud, Stephen C.
Kramer, Kathleen A.
[J]. SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XIX, 2010, 7697
[8] Reference Pattern-Based Track-to-Track Association With Biased Data
Tian, Wei
Wang, Yue
Du, Xiongjie
Shan, Xiuming
Yang, Jian
[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2016, 52 (01) : 501 - U554
[9] Improvement in Track-to-Track Association from using an Adaptive Threshold
Stone, Lawrence D.
Tran, Thy M.
Williams, Mark L.
[J]. FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2009, : 1627 - +
[10] Sensor Bias Estimation for Track-to-Track Association
Tokta, Aybars
Hocaoglu, Ali Koksal
[J]. IEEE SIGNAL PROCESSING LETTERS, 2019, 26 (10) : 1426 - 1430

← 1 2 3 4 5 →