Joint Particle Filter and UKF Position Tracking in Severe Non-Line-of-Sight Situations
The performance of localization techniques in a wireless communication system is severely impaired by biases induced in the range and angle measures because of the non-line-of-sight (NLOS) situation, caused by obstacles in the transmitted signal path. However, the knowledge of the line-of-sight (LOS...
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| Veröffentlicht in: | IEEE journal of selected topics in signal processing 2009-10, Vol.3 (5), p.874-888 |
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| creator | Huerta, J.M. Vidal, J. Giremus, A. Tourneret, J.-Y. |
| description | The performance of localization techniques in a wireless communication system is severely impaired by biases induced in the range and angle measures because of the non-line-of-sight (NLOS) situation, caused by obstacles in the transmitted signal path. However, the knowledge of the line-of-sight (LOS) or NLOS situation for each measure can improve the final accuracy. This paper studies the localization of mobile terminals (MT) based on a Bayesian model for the LOS-NLOS evolution. This Bayesian model does not require having a minimum number of LOS measures at each acquisition. A tracking strategy based on a particle filter (PF) and an unscented Kalman filter (UKF) is used both to estimate the LOS-NLOS situation and the MT kinetic variables (position and speed). The approach shows a remarkable reduction in positioning error and a high degree of scalability in terms of performance versus complexity. |
| doi_str_mv | 10.1109/JSTSP.2009.2027804 |
| format | Article |
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The approach shows a remarkable reduction in positioning error and a high degree of scalability in terms of performance versus complexity.</description><subject>Bayesian analysis</subject><subject>Bayesian methods</subject><subject>Computer Science</subject><subject>Engineering Sciences</subject><subject>Estimates</subject><subject>Global Positioning System</subject><subject>GSM</subject><subject>Localization</subject><subject>Mathematical models</subject><subject>Non-line-of-sight (NLOS)</subject><subject>Obstacles</subject><subject>particle filter</subject><subject>Particle filters</subject><subject>Particle measurements</subject><subject>Particle tracking</subject><subject>Pollution measurement</subject><subject>Position (location)</subject><subject>Position measurement</subject><subject>Rao-Blackwellization</subject><subject>Reduction</subject><subject>Signal and Image Processing</subject><subject>Signal processing</subject><subject>Tracking</subject><subject>unscented Kalman filter</subject><subject>Wireless communication</subject><issn>1932-4553</issn><issn>1941-0484</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkctOwzAQRSMEEqXwA7Cx2CAWgfErTpZVRXlVUCmFreWkTuuS2sVOK_H3JLTqgs3MaHTuXI1uFF1iuMMYsvuXfJpP7ghA1hYiUmBHUQ9nDMfAUnbczZTEjHN6Gp2FsATgIsGsF32-OGMbNFG-MWWt0cjUjfZI2Rn6eB2hiQumMc6iqVfll7FzZCzK9VZ7jd6cjcfG6thVcW7miwblptmoDg_n0Uml6qAv9r0ffYwepsOnePz--DwcjOOSCWhiUagEizRhZMYVnRVFBSWf4YSkwHGqREGZKlRRFASqjJcVK4FTqkknUdD-1I9ud3cXqpZrb1bK_0injHwajGW3A2AAgtItbtmbHbv27nujQyNXJpS6rpXVbhNkKjgQzLhoyet_5NJtvG0fkSkXjCSCdtZkB5XeheB1dfDHILtQ5F8osgtF7kNpRVc7kdFaHwScZEAFpr-3JIYk</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>Huerta, J.M.</creator><creator>Vidal, J.</creator><creator>Giremus, A.</creator><creator>Tourneret, J.-Y.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Bayesian analysis Bayesian methods Computer Science Engineering Sciences Estimates Global Positioning System GSM Localization Mathematical models Non-line-of-sight (NLOS) Obstacles particle filter Particle filters Particle measurements Particle tracking Pollution measurement Position (location) Position measurement Rao-Blackwellization Reduction Signal and Image Processing Signal processing Tracking unscented Kalman filter Wireless communication |
| title | Joint Particle Filter and UKF Position Tracking in Severe Non-Line-of-Sight Situations |
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