An ARMA-Filter Based SAGE Algorithm for Ranging in Diffuse Scattering Environment

Range-based positioning using wireless signal has gained remarkable attention in past decades. Accurately extracting the distance information, i.e., estimating parameters of individual multipath, is of interest. It has been shown that diffuse multipath component (DMC) in wireless propagation channel...

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Vydáno v:IEEE transactions on vehicular technology Ročník 71; číslo 3; s. 3361 - 3366
Hlavní autoři: Jiang, Suying, Wang, Wei, Jost, Thomas, Peng, Peng, Sun, Yuzhe
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.03.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
ARMA filter
Autoregressive moving average
Autoregressive processes
Channel estimation
Colored noise
Distance measurement
DMC
Monte Carlo methods
Parameter estimation
ranging performance
SAGE
Scattering
Wireless communication
ISSN:0018-9545, 1939-9359
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Shrnutí:Range-based positioning using wireless signal has gained remarkable attention in past decades. Accurately extracting the distance information, i.e., estimating parameters of individual multipath, is of interest. It has been shown that diffuse multipath component (DMC) in wireless propagation channel has significant influence on channel estimation and, thus, the ranging performance. In addition to specular component (SC), DMC should be considered in order to improve the estimated accuracy of channel paths' parameters and, thus, the ranging performance. In this paper, we extend the quasi-maximum likelihood space-alternating generalized expectation-maximization (SAGE) algorithm by incorporating an autoregressive moving average (ARMA) filter to estimate the channel parameters under the presence of DMC. The parameters of both DMC and SC are estimated in an iterative approach, where the DMC is assumed as colored noise and the ARMA-filter is used to estimate the contributions from DMC. The validation of the algorithm based on measured data shows that both SC and DMC can be accurately estimated by the proposed approach. A comparison with standard SAGE and AR-SAGE is conducted, where the results reveal that the proposed method outperforms other two approaches in terms of ranging accuracy.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2022.3144828