Integration of Track-to-Track Fusion into Multiple-Model Filter

被引：0

作者：

Hess, Matthias ^{[1
]}

Pourvoyeur, Klaus ^{[1
]}

机构：

[1] Deutsch Flugsicherung GmbH DFS, SH P, Langen, Germany

来源：

2014 Tyrrhenian International Workshop on Digital Communications: Enhanced Surveillance of Aircraft and Vehicles (TIWDC/ESAV) | 2014年

关键词：

ATC system; track-to-track fusion; Kalman filter; covariance intersection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Surveillance in air traffic control (ATC) uses different kinds of sensors, for instance radar, ADS-B or multi-lateration sensors (MLAT). These sensors might be either pre-tracked individually or already combined e.g. in an SMGCS tracking system that potentially inhibits the use of Kalman filter based tracking methods in multi-sensor data fusion (MSDF). This paper addresses this particular problem in MSDF for air traffic control. We present a method that aims at combining Kalman based filtering methods with other methods such as covariance intersection on a very deep level. An implementation of this method is integrated into the PHOENIX system developed at DFS [3] and some results will be presented.

引用

页码：101 / 105

页数：5