4,113 research outputs found

    Indoor localization based on multiple LEDs position estimation

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    This paper describes the simulation results and hardware implementation of an inexpensive, low-complexity LED based indoor positioning system. Localization by multiple LEDs estimation model (MLEM) approximates position of a mobile receiver by the acquisition of positional information from LED transmitters. Multiple LED orientation can either be with or without overlap. Receivers in a no-overlap LED orientation experience only single access while multiple access receivers are designed for orientations with overlaps. Single and multiple access systems were developed and implemented by the use of low cost ATMEG 328 microcontroller. Since multiple LEDs transmit data at the same wavelength and are asynchronous, overlap in multiple access system causes interference. The possibility of this interference is reduced by packet based pulse duration multiplexing (PDM) and a low duty cycle transmission protocol. By the use of MLEM, root mean square error in position estimation is reduced to about 1 percent of the length an indoor location. Experimental results show that overlap increases positional accuracy over a wider coverage region and that the multiple access system allows for a more reliable positioning

    An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

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    A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

    Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

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    Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

    Efficient AoA-based wireless indoor localization for hospital outpatients using mobile devices

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    The motivation of this work is to help outpatients find their corresponding departments or clinics, thus, it needs to provide indoor positioning services with a room-level accuracy. Unlike wireless outdoor localization that is dominated by the global positioning system (GPS), wireless indoor localization is still an open issue. Many different schemes are being developed to meet the increasing demand for indoor localization services. In this paper, we investigated the AoA-based wireless indoor localization for outpatients’ wayfinding in a hospital, where Wi-Fi access points (APs) are deployed, in line, on the ceiling. The target position can be determined by a mobile device, like a smartphone, through an efficient geometric calculation with two known APs coordinates and the angles of the incident radios. All possible positions in which the target may appear have been comprehensively investigated, and the corresponding solutions were proven to be the same. Experimental results show that localization error was less than 2.5 m, about 80% of the time, which can satisfy the outpatients’ requirements for wayfinding

    An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

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    Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy
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