Next Article in Journal
Previous Article in Journal
Sensors 2013, 13(5), 6636-6650; doi:10.3390/s130506636
Article

Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications

*  and
Received: 22 March 2013; in revised form: 14 May 2013 / Accepted: 15 May 2013 / Published: 17 May 2013
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [365 KB, updated 21 June 2014; original version uploaded 21 June 2014]   |   Browse Figures
Abstract: The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC) system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM) system that is enabled by global positioning system (GPS) technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF), is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF), is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.
Keywords: radar; Kalman filter; interacting multiple model; probabilistic data association filter; air traffic management radar; Kalman filter; interacting multiple model; probabilistic data association filter; air traffic management
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Jan, S.-S.; Kao, Y.-C. Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications. Sensors 2013, 13, 6636-6650.

AMA Style

Jan S-S, Kao Y-C. Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications. Sensors. 2013; 13(5):6636-6650.

Chicago/Turabian Style

Jan, Shau-Shiun; Kao, Yu-Chun. 2013. "Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications." Sensors 13, no. 5: 6636-6650.



Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert