Indoor Magnetic Signature Based Localization Algorithm without Person-Dependent Parameter Calibration

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

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An Efficient Area-Based Localization Algorithm for Wireless Sensor Networks

International Review on Computers and Software (IRECOS) ◽

10.15866/irecos.v10i10.7783 ◽

2015 ◽

Vol 10 (10) ◽

pp. 1062

Author(s):

A. Mesmoudi ◽

Mohammed Feham ◽

Nabila Labraoui ◽

Chakib Bekara

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Wireless Sensor ◽

Localization Algorithm

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Research of DV-Hop localization algorithm in indoor environment

Advanced Computer Control ◽

10.2495/icacc130491 ◽

2014 ◽

Author(s):

Yang Li ◽

Shu Xiang ◽

Guang Yang

Keyword(s):

Indoor Environment ◽

Localization Algorithm

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A vehicle localization algorithm based on histogram block characteristic value clustering

Information Science and Management Engineering II (Set) ◽

10.2495/isme20141431 ◽

2014 ◽

Author(s):

Dan Zhang ◽

Ningsheng Gong ◽

Jingwei Jiang ◽

Kaijiao Wu

Keyword(s):

Localization Algorithm ◽

Vehicle Localization ◽

Characteristic Value

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Detection and localization of helipad in autonomous UAV landing: a coupled visual-inertial approach with artificial intelligence

Transport and Communication Science Journal ◽

10.25073/tcsj.71.7.8 ◽

2020 ◽

Vol 71 (7) ◽

pp. 828-839

Author(s):

Thinh Hoang Dinh ◽

Hieu Le Thi Hong

Keyword(s):

Neural Network ◽

Unmanned Aerial Vehicles ◽

Fiducial Marker ◽

Localization Algorithm ◽

Challenging Problem ◽

Autonomous Landing ◽

Aerial Vehicles ◽

Set Up ◽

Detection And Localization ◽

Rotary Wing

Autonomous landing of rotary wing type unmanned aerial vehicles is a challenging problem and key to autonomous aerial fleet operation. We propose a method for localizing the UAV around the helipad, that is to estimate the relative position of the helipad with respect to the UAV. This data is highly desirable to design controllers that have robust and consistent control characteristics and can find applications in search – rescue operations. AI-based neural network is set up for helipad detection, followed by optimization by the localization algorithm. The performance of this approach is compared against fiducial marker approach, demonstrating good consensus between two estimations

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