scholarly journals Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

2021 ◽  
Author(s):  
Huthaifa A. Obeidatat ◽  
Imran Ahmad ◽  
Mohammad R. Rawashdeh ◽  
Ali A. Abdullah ◽  
Wafa S. Shuaieb ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Wide Band ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Localization Accuracy ◽  
Access Points ◽  
Simulated Model ◽  
Toa Estimation ◽  
Localization Errors ◽  
Wide Band Transmission

AbstractThis paper presents the advantages of using a wideband spectrum adopting multi-carrier to improve targets localization within a simulated indoor environment using the Time of Arrival (TOA) technique. The study investigates the effect of using various spectrum bandwidths and a different number of carriers on localization accuracy. Also, the paper considers the influence of the transmitters’ positions in line-of-sight (LOS) and non-LOS propagation scenarios. It was found that the accuracy of the proposed method depends on the number of sub-carriers, the allocated bandwidth (BW), and the number of access points (AP). In the case of using large BW with a large number of subcarriers, the algorithm was effective to reduce localization errors compared to the conventional TOA technique. The performance degrades and becomes similar to the conventional TOA technique while using a small BW and a low number of subcarriers.

scholarly journals Correction to: Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

2021 ◽  
Author(s):  
Huthaifa A. Obeidat ◽  
Imran Ahmad ◽  
Mohammad R. Rawashdeh ◽  
Ali A. Abdullah ◽  
Wafa S. Shuaieb ◽  
...  
Keyword(s):  
Wide Band ◽  
Simulated Model ◽  
Toa Estimation ◽  
Wide Band Transmission

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 UWB Indoor Localization Using Deep Learning LSTM Networks

2020 ◽  
Vol 10 (18) ◽  
pp. 6290 ◽  
Author(s):  
Alwin Poulose ◽  
Dong Seog Han
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Indoor Localization ◽  
Distance Estimation ◽  
Wide Band ◽  
Batch Size ◽  
Estimation Accuracy ◽  
Time Of Arrival ◽  
Localization Error ◽  
Localization Accuracy

Localization using ultra-wide band (UWB) signals gives accurate position results for indoor localization. The penetrating characteristics of UWB pulses reduce the multipath effects and identify the user position with precise accuracy. In UWB-based localization, the localization accuracy depends on the distance estimation between anchor nodes (ANs) and the UWB tag based on the time of arrival (TOA) of UWB pulses. The TOA errors in the UWB system, reduce the distance estimation accuracy from ANs to the UWB tag and adds the localization error to the system. The position accuracy of a UWB system also depends on the line of sight (LOS) conditions between the UWB anchors and tag, and the computational complexity of localization algorithms used in the UWB system. To overcome these UWB system challenges for indoor localization, we propose a deep learning approach for UWB localization. The proposed deep learning model uses a long short-term memory (LSTM) network for predicting the user position. The proposed LSTM model receives the distance values from TOA-distance model of the UWB system and predicts the current user position. The performance of the proposed LSTM model-based UWB localization system is analyzed in terms of learning rate, optimizer, loss function, batch size, number of hidden nodes, timesteps, and we also compared the mean localization accuracy of the system with different deep learning models and conventional UWB localization approaches. The simulation results show that the proposed UWB localization approach achieved a 7 cm mean localization error as compared to conventional UWB localization approaches.

scholarly journals A Hybrid RSS/TOA Method for 3D Positioning in an Indoor Environment

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Smita Tiwari ◽  
Donglin Wang ◽  
Michel Fattouche ◽  
Fadhel Ghannouchi
Keyword(s):  
Indoor Environment ◽  
Signal Strength ◽  
Least Square ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Nakagami Distribution ◽  
University Of Calgary ◽  
Multipath Effects ◽  
3D Positioning ◽  
The University

This paper investigates 3D positioning in an indoor line of sight (LOS) and nonline of sight (NLOS) combined environment. It is a known fact that time-of-arrival-(TOA-) based positioning outperforms other techniques in LOS environments; however, multipath in an indoor environment, especially NLOS multipath, significantly decreases the accuracy of TOA positioning. On the other hand, received-signal-strength-(RSS-) based positioning is not affected so much by NLOS multipath as long as the propagation attenuation can be correctly estimated and the multipath effects have been compensated for. Based on this fact, a hybrid weighted least square (HWLS) RSS/TOA method is proposed for target positioning in an indoor LOS/NLOS environment. The identification of LOS/NLOS path is implemented by using Nakagami distribution. An experiment is conducted in the iRadio lab, in the ICT building at the University of Calgary, in order to (i) demonstrate the availability of Nakagami distribution for the identification of LOS and NLOS path, (ii) estimate the pass loss exponent for RSS technique, and (iii) verify our proposed scheme.

scholarly journals An Indoor Localization System Using Residual Learning with Channel State Information

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 574
Author(s):  
Chendong Xu ◽  
Weigang Wang ◽  
Yunwei Zhang ◽  
Jie Qin ◽  
Shujuan Yu ◽  
...  
Keyword(s):  
Channel State Information ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Location Based Services ◽  
Channel State ◽  
State Information ◽  
Localization Accuracy ◽  
Localization System ◽  
Increasing Demand ◽  
Degradation Problem

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.

scholarly journals Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 230 ◽  
Author(s):  
Slavisa Tomic ◽  
Marko Beko
Keyword(s):  
State Of The Art ◽  
Hybrid Approach ◽  
Critical Distance ◽  
Heuristic Approach ◽  
Target Localization ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Individual Measurement ◽  
New Approach ◽  
Non Line Of Sight

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.

A Localization Algorithm Research to Eliminate the Indoor NLOS Error

2014 ◽  
Vol 989-994 ◽  
pp. 2232-2236 ◽  
Author(s):  
Jia Zhi Dong ◽  
Yu Wen Wang ◽  
Feng Wei ◽  
Jiang Yu
Keyword(s):  
Indoor Environment ◽  
Arrival Time ◽  
Channel Model ◽  
Indoor Positioning ◽  
Superior Performance ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Software Simulation ◽  
Positioning Algorithm

Currently, there is an urgent need for indoor positioning technology. Considering the complexity of indoor environment, this paper proposes a new positioning algorithm (N-CHAN) via the analysis of the error of arrival time positioning (TOA) and the channels of S-V model. It overcomes an obvious shortcoming that the accuracy of traditional CHAN algorithm effected by no-line-of-sight (NLOS). Finally, though MATLAB software simulation, we prove that N-CHAN’s superior performance in NLOS in the S-V channel model, which has a positioning accuracy of centimeter-level and can effectively eliminate the influence of NLOS error on positioning accuracy. Moreover, the N-CHAN can effectively improve the positioning accuracy of the system, especially in the conditions of larger NLOS error.

Precise Ranging Technology Application Research Based on IEEE802.15.4a

2014 ◽  
Vol 631-632 ◽  
pp. 558-562
Author(s):  
Zi Hui Wei ◽  
Zheng He Feng ◽  
Zhi Feng Wang ◽  
Duan Bo Cai
Keyword(s):  
Spread Spectrum ◽  
Wide Band ◽  
Impulse Radio ◽  
Line Of Sight ◽  
Test Results ◽  
Application Research ◽  
Technology Application ◽  
Accuracy Test ◽  
Chirp Spread Spectrum ◽  
Received Signal Strength Indication

To solve the poor location accuracy of wireless sensor networks using Received Signal Strength Indication (RSSI) ranging. Time Of Flight (TOF) ranging is used to ensure the accuracy based on two optional physical layer of Impulse Radio-Ultra Wide-Band (IR-UWB) and Chirp Spread Spectrum (CSS) in IEEE802.15.4a. In this paper, we designed ranging module utilizing CSS and UWB. In the Line Of Sight (LOS) and None Line Of Sight (NLOS) environments ranging accuracy test is implemented, the test results show that the IR-UWB ranging technology can achieve higher ranging accuracy and better multipath resistance compared to CSS.

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