ARIMA-based time variation model for beneath the chassis UWB channel

Utku Demir,Sinem Coleri Ergen

doi:10.1186/s13638-016-0676-3

Utku Demir, Sinem Coleri Ergen

Open Access

https://doi.org/10.1186/s13638-016-0676-3

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Abstract

Intra-vehicular wireless sensor network (IVWSN) enables the integration of the wireless sensor network technology into the vehicle architecture through either eliminating the wires between the existing sensors and the corresponding electronic controller units (ECUs) or empowering new sensor technologies that are not currently implemented due to technical limitations. Ultra-wideband (UWB) has been determined to be the most appropriate technology for IVWSNs since it provides energy efficiency through the low duty-cycle operation and high reliability by exploiting the large bandwidth. In this paper, we propose a time variation model for UWB-based IVWSN-based on the extensive amount of data collected from the transmitter and receiver antennas at various locations and separation distances beneath the chassis of a vehicle moving at different speeds on different types of roads. We adopt the commonly used Saleh-Valenzuela (SV) model to represent the clustering phenomenon in the received power delay profiles (PDPs). The proposed novel time variation model then determines the time evolution of the PDPs by representing the changes in their cluster breakpoints, slopes, and break point amplitudes with the auto-regressive integrated moving average (ARIMA) model. ARIMA(5,1,0) has been demonstrated to fit the breakpoint, cluster slope, and breakpoint amplitude sequences collected at different vehicle speeds with different transmitter and receiver locations on asphalt and stone roads by using Box-Jenkins procedure. This model is validated with diagnostic checking. The absolute values of the model coefficients are observed to be mostly larger on asphalt road than their counterparts on the stone road while exhibiting no dependence on the vehicle speed nor the location of transmitter and receiver antennas.

Highlights

Intra-vehicular wireless sensor network (IVWSN) is a specific type of wireless sensor network between the vehicle sensors and their corresponding electronic controller units (ECUs) deployed with the purpose of either eliminating the currently existing wires or enabling new sensor technologies that cannot be integrated into the vehicle using wired means
The clustering phenomenon in the power delay profiles (PDPs) collected beneath the chassis of the vehicle has been previously represented by using modified SV model
We propose a novel auto-regressive integrated moving average (ARIMA)-based time variation model for the time series data corresponding to the parameters of the SV model including cluster arrival times, cluster amplitudes, and ray amplitude decay rates

Summary

Introduction

Intra-vehicular wireless sensor network (IVWSN) is a specific type of wireless sensor network between the vehicle sensors and their corresponding ECUs deployed with the purpose of either eliminating the currently existing wires or enabling new sensor technologies that cannot be integrated into the vehicle using wired means. The goal of this paper is to provide the time-variation model for the UWB channel beneath the chassis of a vehicle by employing time-series analysis on the data collected from the vehicle moving at different speeds on different types of roads with transmitter and receiver antennas at different locations and separation distances. We validate the proposed ARIMA model on the SV model parameters as a time-varying UWB channel model beneath the chassis of the vehicle based on the analysis of the residuals between generated and observed values and the sensitivity of the model parameters to different vehicle speeds, road types, and distances and locations of transmitter and receiver antennas This is the first work to analyze the validity of a time variation model across a wide range of scenarios.

Estimation of ARIMA model coefficients for SV parameter sequences

Findings

Conclusions