DocumentCode :
2080114
Title :
A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition
Author :
Dehghan, Seyed Mohammad Mehdi ; Moradi, Hadi
Author_Institution :
Adv. Robot. & Intell. Syst. Lab., Univ. of Tehran, Tehran, Iran
fYear :
2013
fDate :
13-15 Feb. 2013
Firstpage :
43
Lastpage :
48
Abstract :
The hybrid localization using Angle of Arrival (AOA) and Received Strength Signal Indicator (RSSI) of an RF source, such as a cell phone in a search and rescue mission, with unknown power and None Line Of Sight (NLOS) condition have been proven to be advantageous compared to using each method separately. The hybrid approach has been proposed to benefit from both RSSI and AOA measurements. In this paper, the initial hybrid method, which was implemented using particle filters due to the multi-modal/non-Gaussian nature of localization in NLOS condition, has been replaced by a multi-step Gaussian filtering approach which provides nearly similar accuracy with better performance. The proposed method has been implemented using extended Kalman filter and Unscented Kalman filter. The simulation results show that the multi-step Gaussian filtering is comparable to particle filter in all cases with better performance. For further evaluation, the effects of uncertainty in the propagation parameters have been studied to show the robustness of each filter to these uncertainties.
Keywords :
Gaussian processes; Kalman filters; direction-of-arrival estimation; geophysical signal processing; nonlinear filters; radiocommunication; radiowave propagation; source separation; AOA measurements; NLOS condition; RF source localization; RSSI measurements; aerial localization; angle of arrival measurement; extended Kalman filter; hybrid localization; multimodal-nonGaussian localization; multistep Gaussian filtering; nonGaussian distribution effect; nonline of sight condition; propagation parameter uncertainty; received strength signal indicator; unscented Kalman filter; Atmospheric measurements; Equations; Measurement uncertainty; Particle filters; Particle measurements; Scattering; Shadow mapping; Extended Kalman Filter; Localization; NLOS propagation; Particle Filter; Unscented Kalman Filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Mechatronics (ICRoM), 2013 First RSI/ISM International Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4673-5809-5
Type :
conf
DOI :
10.1109/ICRoM.2013.6510079
Filename :
6510079
Link To Document :
بازگشت