Angle estimation error reduction method using weighted IMM and least squares
Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacti...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Choi, Seong Hee [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 |
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| Übergeordnetes Werk: |
Enthalten in: International Journal of Control, Automation and Systems - Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009, 15(2017), 1 vom: 19. Jan., Seite 354-361 |
|---|---|
| Übergeordnetes Werk: |
volume:15 ; year:2017 ; number:1 ; day:19 ; month:01 ; pages:354-361 |
| Links: |
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| DOI / URN: |
10.1007/s12555-015-0175-z |
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SPR026430142 |
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| 520 | |a Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. | ||
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10.1007/s12555-015-0175-z doi (DE-627)SPR026430142 (SPR)s12555-015-0175-z-e DE-627 ger DE-627 rakwb eng Choi, Seong Hee verfasserin aut Angle estimation error reduction method using weighted IMM and least squares 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. Angle estimation error (dpeaa)DE-He213 interacting multiple model (dpeaa)DE-He213 least squares (dpeaa)DE-He213 weighted interacting multiple model (dpeaa)DE-He213 Song, Taek Lyul aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 15(2017), 1 vom: 19. Jan., Seite 354-361 (DE-627)SPR026303256 nnns volume:15 year:2017 number:1 day:19 month:01 pages:354-361 https://dx.doi.org/10.1007/s12555-015-0175-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 15 2017 1 19 01 354-361 |
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10.1007/s12555-015-0175-z doi (DE-627)SPR026430142 (SPR)s12555-015-0175-z-e DE-627 ger DE-627 rakwb eng Choi, Seong Hee verfasserin aut Angle estimation error reduction method using weighted IMM and least squares 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. Angle estimation error (dpeaa)DE-He213 interacting multiple model (dpeaa)DE-He213 least squares (dpeaa)DE-He213 weighted interacting multiple model (dpeaa)DE-He213 Song, Taek Lyul aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 15(2017), 1 vom: 19. Jan., Seite 354-361 (DE-627)SPR026303256 nnns volume:15 year:2017 number:1 day:19 month:01 pages:354-361 https://dx.doi.org/10.1007/s12555-015-0175-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 15 2017 1 19 01 354-361 |
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10.1007/s12555-015-0175-z doi (DE-627)SPR026430142 (SPR)s12555-015-0175-z-e DE-627 ger DE-627 rakwb eng Choi, Seong Hee verfasserin aut Angle estimation error reduction method using weighted IMM and least squares 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. Angle estimation error (dpeaa)DE-He213 interacting multiple model (dpeaa)DE-He213 least squares (dpeaa)DE-He213 weighted interacting multiple model (dpeaa)DE-He213 Song, Taek Lyul aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 15(2017), 1 vom: 19. Jan., Seite 354-361 (DE-627)SPR026303256 nnns volume:15 year:2017 number:1 day:19 month:01 pages:354-361 https://dx.doi.org/10.1007/s12555-015-0175-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 15 2017 1 19 01 354-361 |
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10.1007/s12555-015-0175-z doi (DE-627)SPR026430142 (SPR)s12555-015-0175-z-e DE-627 ger DE-627 rakwb eng Choi, Seong Hee verfasserin aut Angle estimation error reduction method using weighted IMM and least squares 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. Angle estimation error (dpeaa)DE-He213 interacting multiple model (dpeaa)DE-He213 least squares (dpeaa)DE-He213 weighted interacting multiple model (dpeaa)DE-He213 Song, Taek Lyul aut Enthalten in International Journal of Control, Automation and Systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 15(2017), 1 vom: 19. Jan., Seite 354-361 (DE-627)SPR026303256 nnns volume:15 year:2017 number:1 day:19 month:01 pages:354-361 https://dx.doi.org/10.1007/s12555-015-0175-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_21 GBV_ILN_24 GBV_ILN_72 GBV_ILN_181 GBV_ILN_496 GBV_ILN_2002 GBV_ILN_2003 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2060 GBV_ILN_2470 AR 15 2017 1 19 01 354-361 |
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Angle estimation error reduction method using weighted IMM and least squares |
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Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 |
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Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 |
| abstract_unstemmed |
Abstract This paper proposes a new approach to reduce target estimation error, especially the measurement angle, when applied to medium- and long-range surveillance radars. If the target does not maneuver or change heading direction for a certain time interval, the predicted angle from the interacting multiple model (IMM) algorithm based on previous track information can be used to reduce the angle estimation error. In addition, the least squares algorithm should be used to calculate the accurate measurement angle. The proposed method, which is weighted IMM (WIMM), including the least squares, is tested using two simulation scenarios: a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new generated angle solution with the predicted azimuth and the measured azimuth works properly in these two scenarios and performs better than IMM. © Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2017 |
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