### Abstract

Language | English |
---|---|

Pages | 873-889 |

Number of pages | 17 |

Journal | IEEE Transactions on Aerospace and Electronic Systems |

Volume | 54 |

Issue number | 2 |

Early online date | 3 Nov 2017 |

DOIs | |

Publication status | Published - 11 Apr 2018 |

### Fingerprint

### Keywords

- Received Signal Strength (RSS)
- coloured noise
- Allan variance
- Kalman filter
- RSS simulation
- RSS based localization

### Cite this

*54*(2), 873-889. https://doi.org/10.1109/TAES.2017.2768278

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**Characterisation of Received Signal Strength Perturbations using Allan Variance.** / Luo, Chunbo; Casaseca-de-la-Higuera, Pablo; McClean, Sally; Parr, Gerard; Ren, Peng.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Characterisation of Received Signal Strength Perturbations using Allan Variance

AU - Luo, Chunbo

AU - Casaseca-de-la-Higuera, Pablo

AU - McClean, Sally

AU - Parr, Gerard

AU - Ren, Peng

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PY - 2018/4/11

Y1 - 2018/4/11

N2 - The received signal strength (RSS) of wireless signalsconveys important information that has been widely used in wirelesscommunications, localisation and tracking. Traditional RSS-basedresearch and applications model the RSS signal using a deterministiccomponent plus a white noise term. This paper investigates theassumption of white noise to have a further understanding of theRSS signal and proposes a methodology based on the Allan Variance (AVAR) to characterise it. Using AVAR, we model the RSS unknown perturbations as correlated random terms. These terms can account for both coloured noise or other effects such as shadowing or small scale fading. Our results confirm that AVAR can be used to obtain a flexible model of the RSS perturbations, as expressed by coloured noise components . The study is complemented by introducing two straightforward applications of the proposed methodology: 1) The modelling and simulation of RSS noise using Wiener processes, and 2) RSS localisation using the extended Kalman filter.

AB - The received signal strength (RSS) of wireless signalsconveys important information that has been widely used in wirelesscommunications, localisation and tracking. Traditional RSS-basedresearch and applications model the RSS signal using a deterministiccomponent plus a white noise term. This paper investigates theassumption of white noise to have a further understanding of theRSS signal and proposes a methodology based on the Allan Variance (AVAR) to characterise it. Using AVAR, we model the RSS unknown perturbations as correlated random terms. These terms can account for both coloured noise or other effects such as shadowing or small scale fading. Our results confirm that AVAR can be used to obtain a flexible model of the RSS perturbations, as expressed by coloured noise components . The study is complemented by introducing two straightforward applications of the proposed methodology: 1) The modelling and simulation of RSS noise using Wiener processes, and 2) RSS localisation using the extended Kalman filter.

KW - Received Signal Strength (RSS)

KW - coloured noise

KW - Allan variance

KW - Kalman filter

KW - RSS simulation

KW - RSS based localization

U2 - 10.1109/TAES.2017.2768278

DO - 10.1109/TAES.2017.2768278

M3 - Article

VL - 54

SP - 873

EP - 889

IS - 2

ER -