Ray-Tracing-Assisted Fingerprinting Based on Channel Impulse Response Measurement for Indoor Positioning

Tseng, Po-Hsuan; Chan, Yao-Chia; Lin, Yun; Lin, Ding‐Bing; Wu, Nan; Wang, Tsai-Mao

doi:10.1109/tim.2016.2622799

Cited by 39 publications

(19 citation statements)

References 33 publications

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“…RF fingerprinting can be carried out using received signal features, in particular signal strength, such as RSSI, Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Channel Frequency Response (CFR)/CSI or equivalently the Channel Impulse Response (CIR) [3,5,15,16]. Time of Arrival (TOA), Timing Advancing (TA), Time Difference of Arrival (TDOA), and Angle of Arrival (AOA) are less frequently used in a fingerprinting-based approaches [17,18].…”

Section: Related Workmentioning

confidence: 99%

CSI-based fingerprinting for indoor localization using LTE Signals

Pecoraro

Domenico

Cianca

et al. 2018

EURASIP J. Adv. Signal Process.

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This paper addresses the use of channel state information (CSI) for Long Term Evolution (LTE) signal fingerprinting localization. In particular, the paper proposes a novel CSI-based signal fingerprinting approach, where fingerprints are descriptors of the "shape" of the channel frequency response (CFR) calculated on CSI vectors, rather than direct CSI vectors. Experiments have been carried out to prove the feasibility and the effectiveness of the proposed method and to study the impact on the localization performance of (i) the bandwidth of the available LTE signal and (ii) the availability of more LTE signals transmitted by different eNodeB (cell diversity). Comparisons with other signal fingerprinting approaches, such as the ones based on received signal strength indicator or reference signal received power, clearly show that using LTE CSI, and in particular, descriptors as fingerprints, can bring relevant performance improvement.

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Section: Related Workmentioning

confidence: 99%

CSI-based fingerprinting for indoor localization using LTE Signals

Pecoraro

Domenico

Cianca

et al. 2018

EURASIP J. Adv. Signal Process.

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“…The authors of [14] have used 3D RT and compared its performance and computational cost against the previously reported methods for indoor environments achieving a mean positioning error of 2.3m (using the same device) and also examined the sensitivity on the accuracy due to the inaccurate material parameters defined in the RT tool. The aforementioned works use RT for RSSI-based fingerprinting, but the authors of [24] have used RT to assist the creation of radiomaps for their fingerprintbased solution which uses a fused combination of RSSI and the Channel Impulse Response (CIR) as the position signature (fingerprint). Also, in [29] 3D RT has been used to create radiomaps for device-based and device-free cases achieving a mean error of 1.6m and 2.44m respectively, however this has done for a simple Line of Sight (LoS) scenario which is a limited case in indoor environments.…”

Section: Background a Propagation Modellingmentioning

confidence: 99%

“…The accuracy seems to depend on the volume and quality of this context and it was proven that the more information included in the process the higher the probability for producing more accurate position estimates [20]- [22]. This information may include radio parameters such as Received Signal Strength Indication (RSSI) [23], Magnetic Field Intensity (MFI) [7] and Channel Impulse Responses (CIR) [24] which could also be cleverly combined or fused to improve the performance [25]. However, the sole dependence on radio parameters imposes various limits that are hard to overcome therefore attempts where diverted in the use of non-radio parameters such as inertial, temperature, light/illumination measurements etc.…”

Section: Introductionmentioning

confidence: 99%

Multidevice Map-Constrained Fingerprint-Based Indoor Positioning Using 3-D Ray Tracing

Raspopoulos

2018

IEEE Trans. Instrum. Meas.

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Abstract-This paper studies the use of deterministic channel modelling through 3D Ray Tracing (RT) for constructing deviceindependent radiomaps for Wi-Fi RSSI-based fingerprinting indoor positioning, applicable to different devices. Device heterogeneity constitutes a limitation in fingerprint-based approaches and also constructing radiomaps through extensive in-situ measurement campaigns is laborious and time-consuming even with a single device let alone the need for radiomaps constructed using multiple different devices. This work tackles both challenges through the use of 3D RT for radiomap generation in conjunction with data calibration using a small set of device-specific measurements to make the radiomap device-independent. The efficiency of this approach is evaluated using simulations and measurements in terms of the time spent to generate the radiomap, the amount of device-specific data required for calibration and in terms of the achievable positioning accuracy. Potential accuracy improvements in the RT-based indoor positioning processes are further investigated, by studying the use of map constraints into the algorithm in the form of a-priori probabilities. In this approach, a Route Probability Factor (RPF), which reflects the likelihood of a user being in various locations inside the environment is used. The outcome of the evaluation process which includes a study of different RPF distributions, indicates the validity of the approach, demonstrated by a reduction in the positioning error for various devices. The versatility of this approach is also demonstrated for different scenarios, different devices and by considering different device-handling conditions.

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“…Although existing models are well-defined, they cause significant ranging errors because of their stochastic nature. Often, fingerprinting method or ray-tracing simulator [12], [13] can provide relatively accurate RSS values, but they have high computational complexity and exhibit extremely site-specific results.…”

Section: Introductionmentioning

confidence: 99%

Fine-Resolution Ranging Scheme Based on Signal Strength in Indoor Hallway With Rough-Surface Slab Waveguide

Park

Hyun

Lee

et al. 2021

IEEE Trans. Instrum. Meas.

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The received-signal-strength (RSS) is widely used in the range-based localization because of its practical advantages such as low-cost and low-complexity. For accurate ranging based on the RSS in indoor environments, well-defined propagation models that consider the distortion of the RSS due to abrupt obstructions are required. This paper proposes an exponential propagation model for indoor hallways whose structures can be modeled as a slab waveguide. This waveguide-shaped structure has two main power loss mechanisms: wave penetration and scattering. These loss mechanisms are quantified as exponential coefficients according to the law of conservation of energy. The surface-scattering theory and multi-mode waveguide concept are utilized for the quantification of scattering and penetration, respectively. The proposed model is verified through actual site measurements using the vector network analyzer-based channel sounding system at IEEE 802.11ax frequency bands. The estimated range obtained from the measured data indicates that the proposed model leads to the ranging estimation performance that could not be achieved with existing sounding-based indoor channel models.

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Ray-Tracing-Assisted Fingerprinting Based on Channel Impulse Response Measurement for Indoor Positioning

Cited by 39 publications

References 33 publications

CSI-based fingerprinting for indoor localization using LTE Signals

CSI-based fingerprinting for indoor localization using LTE Signals

Multidevice Map-Constrained Fingerprint-Based Indoor Positioning Using 3-D Ray Tracing

Fine-Resolution Ranging Scheme Based on Signal Strength in Indoor Hallway With Rough-Surface Slab Waveguide

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