Localization algorithms for asynchronous time difference of arrival positioning systems

He, Shuai; Dong, Xiaodai; Lu, Wu-Sheng

doi:10.1186/s13638-017-0851-1

Cited by 14 publications

(10 citation statements)

References 34 publications

(45 reference statements)

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“…A new two-step algorithm was proposed by He et al [ 20 ]. In the first step, the positioning algorithm combines Taylor Series method Semidefinite Programming (SDP) to achieve the global convergence and estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of Localization Systems in NLOS Urban Scenario with Multipath Ray Tracing Fingerprints and Machine Learning

Sousa

Thomä

2018

Sensors

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A hybrid technique is proposed to enhance the localization performance of a time difference of arrival (TDOA) deployed in non-line-of-sight (NLOS) suburban scenario. The idea was to use Machine Learning framework on the dataset, produced by the ray tracing simulation, and the Channel Impulse Response estimation from the real signal received by each sensor. Conventional localization techniques mitigate errors trying to avoid NLOS measurements in processing emitter position, while the proposed method uses the multipath fingerprint information produced by ray tracing (RT) simulation together with calibration emitters to refine a Machine Learning engine, which gives an extra layer of information to improve the emitter position estimation. The ray-tracing fingerprints perform the target localization embedding all the reflection and diffraction in the propagation scenario. A validation campaign was performed and showed the feasibility of the proposed method, provided that the buildings can be appropriately included in the scenario description.

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Section: Introductionmentioning

confidence: 99%

Enhancement of Localization Systems in NLOS Urban Scenario with Multipath Ray Tracing Fingerprints and Machine Learning

Sousa

Thomä

2018

Sensors

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“…Although, the conventional TDOA‐based positioning systems require synchronization between measuring units , some asynchronous indoor positioning systems have been proposed and implemented where additional mechanisms have been used to obtain valid TDOA measurements . An asynchronous time difference of arrival (A‐TDOA) named as Whistle has been presented in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…The A‐TDOA positioning system described in Ref. uses a single node to measure TDOA in contrast to conventional TDOA system which deploys a pair of synchronized measuring units to determine a single TDOA measurement. The system does not require clock synchronization neither between transmitter and measuring unit nor between the measuring units.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast to previous presented works , where the time synchronization requirement for TDOA based localization is avoided either by deploying additional measuring nodes or using complex computational algorithms, this work presents a asynchronous time‐difference‐of‐arrival (A‐TDOA) localization system using three ultra low power CC1101 radio devices working at 434MHz as measuring receivers placed at known locations to receive signal from single transmitter for its localization in two dimensional space. All three receivers have been interfaced to different laptops through CC debugger and time synchronization is obtained by initial time offset in two TDOA pulses by using a calibration transmitter at known location.…”

Section: Introductionmentioning

confidence: 99%

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A novel power efficient asynchronous time difference of arrival indoor localization system using CC1101 radio transceivers

Nawaz

Bozkurt

Tekin

2017

Micro & Optical Tech Letters

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results shown in , and 8, in spite of the power amplifier, we obtain a proper S 22 characteristic.The power amplifier is also measured using an IEEE 802.11n WLAN signal (OFDM 64-QAM, 20 MHz bandwidth, and 9.6 dB PAPR). Figure 12 shows the measured gain and PAE with a 2.45-GHz IEEE 802.11n WLAN signal. The power amplifier achieved 7.0% PAE at a linear output power of 21.28 dBm and 26.6 dB power gain. As shown in Figure 13, the maximum linear output power of 21.28 dBm is obtained with 3.8% EVM, which meets the IEEE 802.11n MCS 7 standard. CONCLUSIONIn this work, we design a linear CMOS power amplifier for IEEE 802.11n WLAN applications. We first identify a suitable output transformer structure for a linear CMOS power amplifier. From the results, the driver and power stage of the power amplifier are located outside of the output transformer to mitigate the stability issues. Next, we provide the design procedure of the output matching network to minimize the output return loss. The measured maximum linear output power is 21.28 dBm, while the measured EVM for the IEEE 802.11n input signal is 23.8%. The power amplifier achieved 212.3 dB output return loss. From the measured results, we confirm the feasibility of the proposed linear CMOS power amplifier.ABSTRACT: This paper presents a novel 434MHz asynchronous time difference of arrival (A-TDOA) Indoor Localization System (ILS) using

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“…Therefore this technique requires to calculate the values of the signal strength at every sample point which is time consuming process also these values changes even if there is a slight change in the indoor structures. D)TDOA (Time Difference of Arrival)[12]:…”

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confidence: 99%

Hybrid Mechanism for Multiple User Indoor Localization Using Smart Antenna

Sharma¹,

Gulhane²

2015

2015 Fifth International Conference on Advanced Computing &Amp; Communication Technologies

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GPS is commonly used for navigation. But Location estimation in indoor environments is not possible using GPS, as GPS signals cannot work in indoor environment. In indoor localization there is a huge impact of multipath parameters like shadowing, reflection, refraction, diffraction phenomena which have an impact on the position estimation which leads to inaccurate localization. Large number of Access Points (APs) equipped with single antenna could receive enough Receive Signal Strength (RSS) information that gives information about signal characteristics of the target area. But this results in a large cost of deployment. Various localization methods available are: TDOA, TOA, AOA, Location Finger Printing, GPS and RSSI.However in all these approaches the localization depends either on distance or on angle or on time only. In this paper the hybrid mechanism of range and angle measurements is considered. This proposed mechanism will provide an indoor positioning solution using the smart antenna architecture to increase the location estimation accuracy using mode of RSSI values followed by adaptive filtering.

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Localization algorithms for asynchronous time difference of arrival positioning systems

Cited by 14 publications

References 34 publications

Enhancement of Localization Systems in NLOS Urban Scenario with Multipath Ray Tracing Fingerprints and Machine Learning

Enhancement of Localization Systems in NLOS Urban Scenario with Multipath Ray Tracing Fingerprints and Machine Learning

A novel power efficient asynchronous time difference of arrival indoor localization system using CC1101 radio transceivers

Hybrid Mechanism for Multiple User Indoor Localization Using Smart Antenna

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