Sub-Nyquist Rate UWB Indoor Positioning Using Power Delay Profile and Time of Arrival Estimates

2017 ◽  
Author(s):  
Bilal Maqsood ◽  
Ijaz Haider Naqvi
Keyword(s):  
Indoor Positioning ◽  
Time Of Arrival ◽  
Power Delay Profile ◽  
Nyquist Rate

scholarly journals Improved energy detection receiver for ranging in IEEE 802.15.4a standard

2017 ◽  
Vol 10 (2) ◽  
pp. 141-148
Author(s):  
Abdelmadjid Maali ◽  
Geneviève Baudoin ◽  
Ammar Mesloub
Keyword(s):  
Estimation Algorithm ◽  
Energy Detection ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Accurate Estimation ◽  
Time Of Arrival ◽  
Power Delay Profile ◽  
Wideband Signals ◽  
Toa Estimation ◽  
Ieee 802.15.4A

In this paper, we propose a novel energy detection (ED) receiver architecture combined with time-of-arrival (TOA) estimation algorithm, compliant to the IEEE 802.15.4a standard. The architecture is based on double overlapping integrators and a sliding correlator. It exploits a series of ternary preamble sequences with perfect autocorrelation property. This property ensures coding gain, which allows an accurate estimation of power delay profile (PDP). To improve TOA estimation, the interpolation of PDP samples is proposed and the architecture is validated by using an ultra-wideband signals measurements platform. These measurements are carried out in line-of-sight and non-line-of-sight multipath environments. The experimental results show that the ranging performances obtained by the proposed architecture are higher than those obtained by the conventional architecture based on a single-integrator in both LOS and NLOS environments.

scholarly journals Collaborative Indoor Positioning Systems: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1002 ◽  
Author(s):  
Pavel Pascacio ◽  
Sven Casteleyn ◽  
Joaquín Torres-Sospedra ◽  
Elena Simona Lohan ◽  
Jari Nurmi
Keyword(s):  
Systematic Review ◽  
Belief Propagation ◽  
Satellite System ◽  
Indoor Positioning ◽  
Ultra Wideband ◽  
Evaluation Procedure ◽  
Future Research ◽  
Time Of Arrival ◽  
General View ◽  
Positioning Systems

Research and development in Collaborative Indoor Positioning Systems (CIPSs) is growing steadily due to their potential to improve on the performance of their non-collaborative counterparts. In contrast to the outdoors scenario, where Global Navigation Satellite System is widely adopted, in (collaborative) indoor positioning systems a large variety of technologies, techniques, and methods is being used. Moreover, the diversity of evaluation procedures and scenarios hinders a direct comparison. This paper presents a systematic review that gives a general view of the current CIPSs. A total of 84 works, published between 2006 and 2020, have been identified. These articles were analyzed and classified according to the described system’s architecture, infrastructure, technologies, techniques, methods, and evaluation. The results indicate a growing interest in collaborative positioning, and the trend tend to be towards the use of distributed architectures and infrastructure-less systems. Moreover, the most used technologies to determine the collaborative positioning between users are wireless communication technologies (Wi-Fi, Ultra-WideBand, and Bluetooth). The predominant collaborative positioning techniques are Received Signal Strength Indication, Fingerprinting, and Time of Arrival/Flight, and the collaborative methods are particle filters, Belief Propagation, Extended Kalman Filter, and Least Squares. Simulations are used as the main evaluation procedure. On the basis of the analysis and results, several promising future research avenues and gaps in research were identified.

scholarly journals A high-accuracy indoor positioning system based on UWB

2018 ◽  
Vol 173 ◽  
pp. 01021
Author(s):  
Hanyu Liu ◽  
Yanhan Zeng ◽  
Ruguo Li ◽  
Huajie Huang
Keyword(s):  
Indoor Positioning ◽  
Mobile Node ◽  
High Accuracy ◽  
Base Stations ◽  
Ultra Wideband ◽  
Time Of Arrival ◽  
Positioning System ◽  
Wide Range ◽  
Fixed Base ◽  
Indoor Positioning System

In this paper, a high-accuracy indoor positioning system based on the ultra-wideband (UWB) technique is proposed. The proposed system uses a simple ranging process to obtain the distance between the mobile node and the fixed base stations. Besides, an improved time of arrival (ToA) algorithm with Kalman filtering is proposed to improve the positioning accuracy. Measurements have been performed in the real indoor 13m*7.6m environment with many obstacles and the root-mean-square error (RMSE) is less than 0.3m. The proposed system offers a wide range of application in robotics, industrial automation, post-sorting system and so on.

scholarly journals Review on Ultra Wide Band Indoor Localization

2020 ◽  
Vol 2 (2) ◽  
pp. 99
Author(s):  
X Chi ◽  
G Wu ◽  
J Liu ◽  
J Xu ◽  
Qi Lu
Keyword(s):  
Indoor Localization ◽  
Technology Development ◽  
Wide Band ◽  
Indoor Positioning ◽  
Ultra Wide Band ◽  
Time Of Arrival ◽  
Localization Algorithms ◽  
Clear Insight ◽  
Important Means ◽  
Received Signal Strength Indication

Ultra-Wide Band (UWB) is an important means of indoor positioning. Carrying out the research of UWB is of great significance to the development of indoor positioning technology. This article gives a review of the application of UWB in indoor positioning. The motivation and development status of UWB are introduced. UWB localization algorithms such as received signal strength indication, time of arrival, time difference of arrival are analyzed one by one. In this paper, the derivations of the algorithm are summarized. Several technical difficulties of UWB technology development and future development of UWB are presented. This paper provides researchers with a clear insight into the UWB indoor positioning system so that they can further develop other advanced techniques.

scholarly journals Advanced Heterogeneous Feature Fusion Machine Learning Models and Algorithms for Improving Indoor Localization

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 125 ◽  
Author(s):  
Lingwen Zhang ◽  
Ning Xiao ◽  
Wenkao Yang ◽  
Jun Li
Keyword(s):  
Machine Learning ◽  
Feature Fusion ◽  
Indoor Positioning ◽  
Time Of Arrival ◽  
Learning Models ◽  
Fusion Model ◽  
Features Fusion ◽  
Single Feature ◽  
Heterogeneous Features ◽  
Machine Learning Models

In the era of the Internet of Things and Artificial Intelligence, the Wi-Fi fingerprinting-based indoor positioning system (IPS) has been recognized as the most promising IPS for various applications. Fingerprinting-based algorithms critically rely on a fingerprint database built from machine learning methods. However, currently methods are based on single-feature Received Signal Strength (RSS), which is extremely unstable in performance in terms of precision and robustness. The reason for this is that single feature machines cannot capture the complete channel characteristics and are susceptible to interference. The objective of this paper is to exploit the Time of Arrival (TOA) feature and propose a heterogeneous features fusion model to enhance the precision and robustness of indoor positioning. Several challenges are addressed: (1) machine learning models based on heterogeneous features, (2) the optimization of algorithms for high precision and robustness, and (3) computational complexity. This paper provides several heterogeneous features fusion-based localization models. Their effectiveness and efficiency are thoroughly compared with state-of-the-art methods.

Time of arrival and power delay profile estimation for IR-UWB systems

2013 ◽  
Vol 93 (5) ◽  
pp. 1317-1327 ◽  
Author(s):  
Fang Shang ◽  
Benoit Champagne ◽  
Ioannis Psaromiligkos
Keyword(s):  
Time Of Arrival ◽  
Power Delay Profile ◽  
Profile Estimation
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