Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors

To avoid the inherent defects of current airport surface surveillance systems, a distributed non-cooperative surface surveillance scheme based on geomagnetic sensor technology is proposed in this article. Furthermore, a surface target tracking algorithm based on improved interacting multiple model (...

Full description

Bibliographic Details
Main Authors: Xinmin Tang, Wenjie Zhao, Shangfeng Gao
Format: Article
Language:English
Published: SAGE Publishing 2020-02-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147720904563
id doaj-56367f73e2304085b359345fa8710f5d
record_format Article
spelling doaj-56367f73e2304085b359345fa8710f5d2020-11-25T03:54:36ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772020-02-011610.1177/1550147720904563Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensorsXinmin Tang0Wenjie Zhao1Shangfeng Gao2College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCommercial Aircraft Corporation of China, Ltd., Shanghai, ChinaTo avoid the inherent defects of current airport surface surveillance systems, a distributed non-cooperative surface surveillance scheme based on geomagnetic sensor technology is proposed in this article. Furthermore, a surface target tracking algorithm based on improved interacting multiple model (WIMM) is presented for use when the target is perceptible. In this algorithm, the weighted sum of the mean values of the residual errors, which is used to reconstruct the model probabilistic likelihood function, and the Markov model transition probability are updated using posterior information. When a target is imperceptible, its trajectory can be predicted by the target identified motion model and the adaptive model transition probability. Simulation results show that the WIMM algorithm can be used efficiently together with an observed small sample of velocity information for target tracking and trajectory prediction. Compared with the interacting multiple model and residual-mean interacting multiple model algorithms, the frequency of model switching and the rate of model identification were increased during the imperceptible period, and target prediction error was greatly reduced.https://doi.org/10.1177/1550147720904563
collection DOAJ
language English
format Article
sources DOAJ
author Xinmin Tang
Wenjie Zhao
Shangfeng Gao
spellingShingle Xinmin Tang
Wenjie Zhao
Shangfeng Gao
Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
International Journal of Distributed Sensor Networks
author_facet Xinmin Tang
Wenjie Zhao
Shangfeng Gao
author_sort Xinmin Tang
title Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
title_short Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
title_full Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
title_fullStr Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
title_full_unstemmed Improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
title_sort improved interacting multiple model algorithm airport surface target tracking based on geomagnetic sensors
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2020-02-01
description To avoid the inherent defects of current airport surface surveillance systems, a distributed non-cooperative surface surveillance scheme based on geomagnetic sensor technology is proposed in this article. Furthermore, a surface target tracking algorithm based on improved interacting multiple model (WIMM) is presented for use when the target is perceptible. In this algorithm, the weighted sum of the mean values of the residual errors, which is used to reconstruct the model probabilistic likelihood function, and the Markov model transition probability are updated using posterior information. When a target is imperceptible, its trajectory can be predicted by the target identified motion model and the adaptive model transition probability. Simulation results show that the WIMM algorithm can be used efficiently together with an observed small sample of velocity information for target tracking and trajectory prediction. Compared with the interacting multiple model and residual-mean interacting multiple model algorithms, the frequency of model switching and the rate of model identification were increased during the imperceptible period, and target prediction error was greatly reduced.
url https://doi.org/10.1177/1550147720904563
work_keys_str_mv AT xinmintang improvedinteractingmultiplemodelalgorithmairportsurfacetargettrackingbasedongeomagneticsensors
AT wenjiezhao improvedinteractingmultiplemodelalgorithmairportsurfacetargettrackingbasedongeomagneticsensors
AT shangfenggao improvedinteractingmultiplemodelalgorithmairportsurfacetargettrackingbasedongeomagneticsensors
_version_ 1724472809614213120