scholarly journals Proposal for a Localization System for an IoT Ecosystem

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3016
Author(s):  
Juraj Machaj ◽  
Peter Brida ◽  
Slavomir Matuska
Keyword(s):  
Service Providers ◽  
Inertial Sensors ◽  
Multipath Propagation ◽  
Dead Reckoning ◽  
Global Navigation Satellite Systems ◽  
High Signal ◽  
Indoor Environments ◽  
Localization System ◽  
Battery Capacity ◽  
Iot Devices

In the last decade, positioning using wireless signals has gained a lot of attention since it could open new opportunities for service providers. Localization is important, especially in indoor environments, where the widely used global navigation satellite systems (GNSS) signals suffer from high signal attenuation and multipath propagation, resulting in poor accuracy or a loss of positioning service. Moreover, in an Internet of things (IoT) environment, the implementation of GNSS receivers into devices may result in higher demands on battery capacity, as well as increased cost of the hardware itself. Therefore, alternative localization systems that are based on wireless signals for the communication of IoT devices are gaining a lot of attention. In this paper, we provide a design of an IoT localization system, which consists of multiple localization modules that can be utilized for the positioning of IoT devices that are connected thru various wireless technologies. The proposed system can currently perform localization based on received signals from LoRaWAN, ZigBee, Wi-Fi, UWB and cellular technologies. The implemented pedestrian dead reckoning algorithm can process the data measured by a mobile device that is equipped with inertial sensors to construct a radio map and thus help with the deployment of the positioning services based on a fingerprinting approach.

scholarly journals Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Ying Guo ◽  
Qinghua Liu ◽  
Xianlei Ji ◽  
Shengli Wang ◽  
Mingyang Feng ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Distance Estimation ◽  
Dead Reckoning ◽  
Principal Component ◽  
Detection Algorithm ◽  
Estimation Accuracy ◽  
Indoor Environments ◽  
Using Data ◽  
The Time Domain ◽  
Pedestrian Dead Reckoning

Pedestrian dead reckoning (PDR) is an essential technology for positioning and navigation in complex indoor environments. In the process of PDR positioning and navigation using mobile phones, gait information acquired by inertial sensors under various carrying positions differs from noise contained in the heading information, resulting in excessive gait detection deviation and greatly reducing the positioning accuracy of PDR. Using data from mobile phone accelerometer and gyroscope signals, this paper examined various phone carrying positions and switching positions as the research objective and analysed the time domain characteristics of the three-axis accelerometer and gyroscope signals. A principal component analysis algorithm was used to reduce the dimension of the extracted multidimensional gait feature, and the extracted features were random forest modelled to distinguish the phone carrying positions. The results show that the step detection and distance estimation accuracy in the gait detection process greatly improved after recognition of the phone carrying position, which enhanced the robustness of the PDR algorithm.

scholarly journals Experimental Evaluation of Multipath Mitigation in TDOA-Based Indoor Passive Localization System Using A Beam Steering Broadband Circular Polarization Antenna

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 362 ◽  
Author(s):  
Changjiang Su ◽  
Yanqun Liu ◽  
Leilei Liu ◽  
Mei Yang ◽  
Hongxin Zhao ◽  
...  
Keyword(s):  
Circular Polarization ◽  
Experimental Evaluation ◽  
Multipath Propagation ◽  
Beam Steering ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Rf Switch ◽  
Multipath Mitigation ◽  
Localization System ◽  
Passive Localization

An experimental evaluation of multipath mitigation using a beam steering broadband circular polarization antenna (BSBCPA) in indoor passive localization system based on time differences of arrival (TDOA) is presented in this paper. The BSBCPA consists of a beam switch network, four identical hexagon patch elements and their respective feeding networks. By controlling the states of a radio frequency (RF) switch in the beam switch network, four steering circular polarization beams can be excited separately for azimuth omnidirectional coverage. Combining the spatial selectivity of steering beams and circular polarization in the BSBCPA, the positioning inaccuracy from indoor multipath propagation can be mitigated. In two different indoor environments with line of sight (LOS), complex multipath, when transmitting a 20 MHz bandwidth signal in WLAN, the 2D positioning mean error obtained is 0.7 m and 0.82 m, respectively. Compared with conventional omnidirectional linear polarization antenna (OLPA), the BSBCPA can at least improve positioning accuracy by 51%. The experimental results show that the proposed BSBCPA can significantly mitigate multipath propagation for TDOA-based indoor passive localization.

scholarly journals Combining a Modified Particle Filter Method and Indoor Magnetic Fingerprint Map to Assist Pedestrian Dead Reckoning for Indoor Positioning and Navigation

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 185
Author(s):  
Fang-Shii Ning ◽  
Yu-Chun Chen
Keyword(s):  
Magnetic Field ◽  
Particle Filter ◽  
Dead Reckoning ◽  
Step Length ◽  
Indoor Positioning ◽  
Global Navigation Satellite Systems ◽  
Filter Method ◽  
Indoor Environments ◽  
Positioning Accuracy ◽  
Pedestrian Dead Reckoning

Although advancement has been observed in global navigation satellite systems and these systems are widely used, they cannot provide effective navigation and positioning services in covered areas and areas that lack strong signals, such as indoor environments. Therefore, in recent years, indoor positioning technology has become the focus of research and development. The magnetic field of the Earth is quite stable in an open environment. Due to differences in building and internal structures, this type of three-dimensional vector magnetic field is widely available indoors for indoor positioning. A smartphone magnetometer was used in this study to collect magnetic field data for constructing indoor magnetic field maps. Moreover, an acceleration sensor and a gyroscope were used to identify the position of a mobile phone and detect the number of steps travelled by users with the phone. This study designed a procedure for measuring the step length of users. All obtained information was input into a pedestrian dead reckoning (PDR) algorithm for calculating the position of the device. The indoor positioning accuracy of the PDR algorithm was optimised using magnetic gradients of magnetic field maps with a modified particle filter algorithm. Experimental results reveal that the indoor positioning accuracy was between 0.6 and 0.8 m for a testing area that was 85 m long and 33 m wide. This study effectively improved the indoor positioning accuracy and efficiency by using the particle filter method in combination with the PDR algorithm with the magnetic fingerprint map.

scholarly journals RMLNet—A Reliable Wireless Network for a Multiarea TDOA-Based Localization System

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4374
Author(s):  
Yuan Xue ◽  
Wei Su ◽  
Dong Yang ◽  
Hongchao Wang ◽  
Weiting Zhang
Keyword(s):  
Multipath Propagation ◽  
High Rate ◽  
Target Area ◽  
Indoor Environments ◽  
Localization Algorithm ◽  
Mobile Nodes ◽  
Target Node ◽  
Position Information ◽  
Precise Position ◽  
Localization System

Ultrawideband (UWB) wireless communication is a promising spread-spectrum technology for accurate localization among devices characterized by a low transmission power, a high rate and immunity to multipath propagation. The accurately of the clock synchronization algorithm and the time-difference-of-arrival (TDOA) localization algorithm provide precise position information of mobile nodes with centimeter-level accuracy for the UWB localization system. However, the reliability of target node localization for multi-area localization remains a subject of research. Especially for dynamic and harsh indoor environments, an effective scheme among competing target nodes for localization due to the scarcity of radio resources remains a challenge. In this paper, we present RMLNet, an approach focus on the medium access control (MAC) layer, which guarantees general localization application reliability on multi-area localization. Specifically, the design requires specific and optimized solutions for managing and coordinating multiple anchor nodes. In addition, an approach for target area determination is proposed, which can approximately determine the region of the target node by the received signal strength indication (RSSI), to support RMLNet. Furthermore, we implement the system to estimate the localization of the target node and evaluate its performance in practice. Experiments and simulations show that RMLNet can achieve localization application reliability multi-area localization with a better localization performance of competing target nodes.

scholarly journals IMPROVED INDOOR POSITIONING USING BLE DIFFERENTIAL DISTANCE CORRECTION AND PEDESTRIAN DEAD RECKONING

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 193-198
Author(s):  
Y. T. Tang ◽  
Y. T. Kuo ◽  
J. K. Liao ◽  
K. W. Chiang
Keyword(s):  
Inertial Sensors ◽  
Distance Estimation ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Walking Distance ◽  
Indoor Environments ◽  
Alternative Scheme ◽  
Differential Distance ◽  
Pedestrian Dead Reckoning ◽  
Distance Correction

Abstract. Recently, indoor positioning becomes a popular issue because of its corresponding location-aware applications. Owing to the limits of the sheltered signal of satellites in indoor environments, one of the alternative scheme is Bluetooth Low Energy (BLE) technology. BLE device broadcasts Received Signal Strength Indicator (RSSI) for distance estimation and further positioning. However, in the complex indoor environment, the reflection, fading, and multipath effect of BLE make the variable RSSI and may lead to poor quality of RSSI. In this study, the concept called Differential Distance Correction (DDC) is similar to the Differential Global Navigation Satellite System (DGNSS). This method can eliminate some residuals and further improve the results with the corrected distance. On the other hand, Pedestrian Dead Reckoning (PDR) is another common indoor positioning method. PDR can propagate the next position from the current position by the implemented of inertial sensors. Despite that, the error of inertial sensors would accumulate with time and walking distance, which position update is required for restraining the drift. Accordingly, the two indoor positioning methods have their strong and weak point. BLE-based positioning is absolute positioning, while PDR is relative positioning. This study proposes a concept that combines the two methods. The pedestrian receives the RSSI and records the information from inertial sensors simultaneously. Through the complementary of two methods, the positioning results would be improved from 29% to 66% according to different travelled distance.

3D localization for subcentimeter-sized devices

2021 ◽  
Vol 64 (3) ◽  
pp. 117-125
Author(s):  
Rajalakshmi Nandakumar ◽  
Vikram Iyer ◽  
Shyamnath Gollakota
Keyword(s):  
Metropolitan Area ◽  
Ultra Wideband ◽  
Phase Information ◽  
Noise Floor ◽  
Localization System ◽  
Coin Cell ◽  
3D Localization ◽  
Button Cell ◽  
Iot Devices ◽  
5 Ghz

The vision of tracking small IoT devices runs into the reality of localization technologies---today it is difficult to continuously track objects through walls in homes and warehouses on a coin cell battery. Although Wi-Fi and ultra-wideband radios can provide tracking through walls, they do not last more than a month on small coin and button cell batteries because they consume tens of milliwatts of power. We present the first localization system that consumes microwatts of power at a mobile device and can be localized across multiple rooms in settings such as homes and hospitals. To this end, we introduce a multiband backscatter prototype that operates across 900 MHz, 2.4 GHz, and 5 GHz and can extract the backscatter phase information from signals that are below the noise floor. We build subcentimeter-sized prototypes that consume 93 μW and could last five to ten years on button cell batteries. We achieved ranges of up to 60 m away from the AP and accuracies of 2, 12, 50, and 145 cm at 1, 5, 30, and 60 m, respectively. To demonstrate the potential of our design, we deploy it in two real-world scenarios: five homes in a metropolitan area and the surgery wing of a hospital in patient pre-op and post-op rooms as well as storage facilities.

scholarly journals Development and Experimental Evaluation of a Low-Cost Cooperative UAV Localization Network Prototype

2018 ◽  
Vol 7 (4) ◽  
pp. 42 ◽  
Author(s):  
Salil Goel ◽  
Allison Kealy ◽  
Bharat Lohani
Keyword(s):  
Information Sharing ◽  
Inertial Sensors ◽  
Low Cost ◽  
Wide Band ◽  
Cooperative Networks ◽  
Global Navigation Satellite Systems ◽  
Cooperative Localization ◽  
Cooperative Network ◽  
Precise Positioning ◽  
Assisted Navigation

Precise localization is one of the key requirements in the deployment of UAVs (Unmanned Aerial Vehicles) for any application including precision mapping, surveillance, assisted navigation, search and rescue. The need for precise positioning is even more relevant with the increasing automation in UAVs and growing interest in commercial UAV applications such as transport and delivery. In the near future, the airspace is expected to be occupied with a large number of unmanned as well as manned aircraft, a majority of which are expected to be operating autonomously. This paper develops a new cooperative localization prototype that utilizes information sharing among UAVs and static anchor nodes for precise positioning of the UAVs. The UAVs are retrofitted with low-cost sensors including a camera, GPS receiver, UWB (Ultra Wide Band) radio and low-cost inertial sensors. The performance of the low-cost prototype is evaluated in real-world conditions in partially and obscured GNSS (Global Navigation Satellite Systems) environments. The performance is analyzed for both centralized and distributed cooperative network designs. It is demonstrated that the developed system is capable of achieving navigation grade (2–4 m) accuracy in partially GNSS denied environments, provided a consistent communication in the cooperative network is available. Furthermore, this paper provides experimental validation that information sharing is beneficial to improve positioning performance even in ideal GNSS environments. The experiments demonstrate that the major challenges for low-cost cooperative networks are consistent connectivity among UAV platforms and sensor synchronization.

scholarly journals Cognitive Interference Alignment Schemes for IoT Oriented Heterogeneous Two-Tier Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2548 ◽  
Author(s):  
Run Tian ◽  
Lin Ma ◽  
Zhe Wang ◽  
Xuezhi Tan
Keyword(s):  
Spectrum Sharing ◽  
Network Performance ◽  
Signal To Noise Ratio ◽  
Interference Management ◽  
Interference Alignment ◽  
Network Capacity ◽  
High Signal ◽  
Noise Power ◽  
Optimal Capacity ◽  
Iot Devices

This paper considers interference management and capacity improvement for Internet of Things (IoT) oriented two-tier networks by exploiting cognition between network tiers with interference alignment (IA). More specifically, we target our efforts on the next generation two-tier networks, where a tier of femtocell serving multiple IoT devices shares the licensed spectrum with a tier of pre-existing macrocell via a cognitive radio. Aiming to manage the cross-tier interference caused by cognitive spectrum sharing as well as ensure an optimal capacity of the femtocell, two novel self-organizing cognitive IA schemes are proposed. First, we propose an interference nulling based cognitive IA scheme. In such a scheme, both co-tier and cross-tier interferences are aligned into the orthogonal subspace at each IoT receiver, which means all the interference can be perfectly eliminated without causing any performance degradation on the macrocell. However, it is known that the interference nulling based IA algorithm achieves its optimum only in high signal to noise ratio (SNR) scenarios, where the noise power is negligible. Consequently, when the imposed interference-free constraint on the femtocell can be relaxed, we also present a partial cognitive IA scheme that further enhances the network performance under a low and intermediate SNR. Additionally, the feasibility conditions and capacity analyses of the proposed schemes are provided. Both theoretical and numerical results demonstrate that the proposed cognitive IA schemes outperform the traditional orthogonal precoding methods in terms of network capacity, while preserving for macrocell users the desired quality of service.

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