Modeling of a Re-Configurable Indoor Positioning System Based on Software Defined Radio Architecture

Piccinni, G.; Avitabile, G.; Coviello, Giuseppe; Talarico, Claudio

doi:10.1109/ngcas.2018.8572294

Cited by 9 publications

(8 citation statements)

References 6 publications

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“…[12] devises a semi-automatic system capable of BLE-related parameters tuning to achieve high accuracy. [13] explores using software-defined radio to realize a reconfigure positioning system. [14] studies to deliver dynamic content Ads in multiple protocols with BLE beacons.…”

Section: Related Workmentioning

confidence: 99%

“…A removal fails if 1) tac is zero, which means a TP becomes uncovered or 2) tac and ac both appeared in ACset but belonging to different SIPGs, which means two TPs become unidentified (lines 10-12). Otherwise, the removal succeeds for ac, and all affected ACs should be recorded (lines [13][14]. Note that beacon i should be kept if any AC in ACset fails the above tests after ditching i.…”

Section: B Heuristic Algorithm For Beacon Deploymentmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Beacon Deployment for Large-scale Positioning

He¹,

Ho²,

Wang³

et al. 2021

J-NaNA

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Instant and precise localization of indoor mobile users is fundamental for supporting various sophisticated location-aware services. Using Bluetooth low-power beacons for mobile user positioning has been reported as an effective approach, where the beacon deployment positioning (BDP) problem has been defined. The paper introduces a novel approach for solving large-scale BDP problems, aiming to significantly reduce beacon consumption from existing solutions with much less computation complexity. Extensive simulations are conducted to verify the proposed algorithm, whose beacon consumption is about 1.14 to 1.67 times and 0.2 to 0.48 times compared to those of the Mixed Integer Linear Program (ILP) and a naive iBeacon solution respectively. We have also observed that the running time scales well with the growth of the number of Test Positions and attenuation factors.

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Section: Related Workmentioning

confidence: 99%

Section: B Heuristic Algorithm For Beacon Deploymentmentioning

confidence: 99%

Efficient Beacon Deployment for Large-scale Positioning

He¹,

Ho²,

Wang³

et al. 2021

J-NaNA

View full text Add to dashboard Cite

show abstract

“…For the direct echo a fixed distance d 0 of 5 meters was imposed, while, a variable distance in the d 0 + 0.9m and d 0 + 5mm range was considered. Due to signal bandwidth and the system sampling time, echoes placed beneath to the breakdown distance of d 0 + 0.9 are unresolved by the system because the cross-correlation function will exhibit a single pulse that contains both echoes [35]. Further, a LOS scenario was simulated, so the direct path is the first arriving echo at the receiver side, and, it exhibit the strongest amplitude (normalized to 1), whereas, a normalized amplitude of 0.8 was chosen for the multipath echo to simulate the arrival of a very strong multipath interference.…”

Section: B Multipath Channelmentioning

confidence: 99%

“…Moreover, it is important to note that the direct echo was estimated with a very high level of accuracy and precision directly from the channel model in (7). Any equalizer filter or iterative methods, as for example the search and subtract approach [27], [35], was introduced in the system.…”

Section: B Multipath Channelmentioning

confidence: 99%

Distance Estimation Algorithm for Wireless Localization Systems Based on Lyapunov Sensitivity Theory

2019

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The paper describes a novel distance evaluation algorithm based on the time-difference of arrival (TDOA) principle. The proposed method solves the distance estimation problem applying the Lyapunov theory. To perform this task, the distance evaluation problem is converted to a parameters identification process exploiting the sensing signal peculiarities. This latter combines the properties of the Frank-Zadoff-Chu (FZC) sequences with the Orthogonal Frequency-Division Multiplexing (OFDM) modulation scheme. The resulting signal can be used to improve accuracy and precision in distance estimation using a reduced signal bandwidth. The system was modeled considering either an additive white noise Gaussian channel and a moderate multipath model. The simulation results demonstrate that the system achieves an accuracy and a precision better than 10 cm considering SNR equal to 0 dB and signal bandwidths of only 125 MHz.

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“…Recently, the generation of three-dimensional (3D) models of the environment has garnered significant interest in various fields, e.g., building renovation [1], indoor navigation [2], architecture [3], and facility management [4,5]. With the availability of mature technology for data collection, rich environment information can be captured through many platforms such as light detection and ranging [6], RGB-D cameras [7], and stereo cameras [8].…”

Section: Introductionmentioning

confidence: 99%

A Novel Indoor Structure Extraction Based on Dense Point Cloud

Shi

Zeng

2020

IJGI

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Herein, we propose a novel indoor structure extraction (ISE) method that can reconstruct an indoor planar structure with a feature structure map (FSM) and enable indoor robot navigation using a navigation structure map (NSM). To construct the FSM, we first propose a two-staged region growing algorithm to segment the planar feature and to obtain the original planar point cloud. Subsequently, we simplify the planar feature using quadtree segmentation based on cluster fusion. Finally, we perform simple triangulation in the interior and vertex-assignment triangulation in the boundary to accomplish feature reconstruction for the planar structure. The FSM is organized in the form of a mesh model. To construct the NSM, we first propose a novel ground extraction method based on indoor structure analysis under the Manhattan world assumption. It can accurately capture the ground plane in an indoor scene. Subsequently, we establish a passable area map (PAM) within different heights. Finally, a novel-form NSM is established using the original planar point cloud and the PAM. Experiments are performed using three public datasets and one self-collected dataset. The proposed plane segmentation approach is evaluated on two simulation datasets and achieves a recall of approximately 99%, which is 5% higher than that of the traditional plane segmentation method. Furthermore, the triangulation performance of our method compared with the traditional greedy projection triangulation show that our method performs better in terms of feature representation. The experimental results reveal that our ISE method is robust and effective for extracting indoor structures.

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Modeling of a Re-Configurable Indoor Positioning System Based on Software Defined Radio Architecture

Cited by 9 publications

References 6 publications

Efficient Beacon Deployment for Large-scale Positioning

Efficient Beacon Deployment for Large-scale Positioning

Distance Estimation Algorithm for Wireless Localization Systems Based on Lyapunov Sensitivity Theory

A Novel Indoor Structure Extraction Based on Dense Point Cloud

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