Beacon Location Research Articles

Localization in MR-based Indoor Navigation System using point cloud registration

Abstract. This paper addresses the pervasive challenge of localization within indoor navigation systems. Many existing systems grapple with this issue, relying on marker-based methods, Bluetooth beacon localization, and image processing. However, these solutions often necessitate the placement of predetermined markers within the environment, presenting limitations such as marker deterioration over time, spatial constraints, and associated costs. In response, we propose a novel point cloud registration-based approach. This method involves the creation of a comprehensive global point cloud representing the entire indoor environment, effectively serving as a three-dimensional virtual map. Concurrently, a mixed-reality device is utilized to generate a local point cloud specific to the device’s current location within the building. By aligning and registering the local cloud with the global counterpart, the device’s precise location within the virtual map can be determined. This approach enables seamless navigation within indoor environments without the reliance on physical markers, offering a versatile and cost-effective solution to the challenge of localization in indoor navigation systems. Finally, an error analysis was also done to test localization accuracy for different illumination conditions, demonstrating the effectiveness of this method.

Tourists’ Adoption of Context-Aware Applications: A Case Study, Using Personal Locator Beacons at the Mole National Park, Ghana

The use of technology to provide contextual information for decision-making has been a long-standing practice. The study aims to identify the antecedents influencing tourists’ use of context-aware applications. It employs the Unified Model of Electronic Government Adoption (UMEGA) and the Expectation Confirmation Model (ECM) to investigate tourists’ behaviors in the use of Personal Locator Beacons (PLBs) during the pre-adoption and post-adoption stages at the Mole National Park in Ghana. Data was analyzed using Smart PLS 3.0 software. The findings suggest that pre-adoption performance expectancy, motivational needs, and personal situation significantly affect tourists’ pre-adoption intentions to continue using context-aware applications. In addition, information recommendation, service quality, confirmation expectation, and satisfaction influenced continued use and recommendation. However, social influence and enjoyment experience did not significantly impact tourists’ behavioral intentions. The findings contribute to theory by integrating components of the two models (UMEGA & ECM) and delving into the antecedents of users’ decision-making processes.

Underwater Positioning Analysis and System Establishment of the Towed Underwater Hydrophone Array System

The aim of this study is to establish an underwater towed hydrophone array detection and positioning system, which serves as a rescue device for detecting flight recorders in the event of a maritime accident. By using Time Difference of Arrival (TDOA) to calculate the azimuth of the underwater locator beacon (ULB) which is located inside the black box, the position of the flight recorder can be obtained. The underwater towed hydrophone array detection and positioning system was tested for a three-day experiment in the waters off the southwest coast of Taiwan. The azimuth of the sound source was determined by using two frequencies generated by different types of underwater locator beacons (37.5 kHz and 8.8 kHz) and post-processing. The accuracy of the positioning was achieved by controlling the depth of the underwater hydrophone array. This study can deduce the location of the underwater locator beacon through subsequent positioning analysis, which can be used by search and rescue teams in the future to improve the efficiency of the rescue process.

Enhance signal of underwater locator beacon by adaptive filter and simulation received signal

Searching for and recovering a flight recorder at sea is a complex and demanding task. Once the flight recorder is submerged, the underwater locator beacon (ULB) mounted on it will activate. In this study, we developed an algorithm combining an adaptive filter and a simulated received signal to enhance the signal-to-noise ratio (SNR), thereby increasing the probability of detecting the ULB signal. The experiment was taken place off the coast of Kaohsiung, Taiwan, with a ship towing an array and circling a prepositioned ULB to collect underwater acoustic data. The ULB signal was significantly amplified using the proposed algorithm. This research offers a pre-processing technique for ULB signal enhancement, demonstrating its applicability in real-world scenarios.

Maritime search and rescue in canada and the use of emergency radio beacons

Successful and early distress communication at sea is critically important for improving the survivability of marine accidents. A wide range of communication methods is available for seafarers to make distress calls. In particular, emergency radio beacons (i.e. emergency position indicating radio beacons (EPIRBs) and personal locator beacons (PLBs)) provide a reliable, commercially available means by which distress notification and incident location can be provided, particularly if time is not available to establish communication by radio or telephone. Given the importance of these devices, the International Maritime Organization (IMO) provides guidance for flag states to incorporate radio distress beacons within legal and search and rescue (SAR) frameworks. National regulations in Canada stipulate additional performance requirements for radio frequency transmission, operation and use. The governance structure for emergency radio beacons in Canada is comprehensive and complex, and worldwide accident statistics show that when EPIRBs and PLBs are used, the rescue rate increases. Still, in Canada, a significant proportion of maritime activities (e.g., fish harvesting) do not require the use of these devices, and it is in these sectors where the greatest number of fatalities is occurring. Our paper explores the governance structure for the development and use of EPIRBs and PLBs in Canada, identifying where challenges and gaps exist and considering ways to close these gaps. Discussion is provided on the flexibility and adaptability of the governance system to incorporating new information and changes in technology.

Beacon v2 Reference Implementation: a toolkit to enable federated sharing of genomic and phenotypic data.

Beacon v2 is an API specification established by the Global Alliance for Genomics and Health initiative (GA4GH) that defines a standard for federated discovery of genomic and phenotypic data. Here, we present the Beacon v2 Reference Implementation (B2RI), a set of open-source software tools that allow lighting up a local Beacon instance 'out-of-the-box'. Along with the software, we have created detailed 'Read the Docs' documentation that includes information on deployment and installation. The B2RI is released under GNU General Public License v3.0 and Apache License v2.0. Documentation and source code is available at: https://b2ri-documentation.readthedocs.io. Supplementary data are available at Bioinformatics online.

GNSS Independent Position Fixing using Multiple Navigational Features Registration

Safe navigation at sea depends on reliable position information. The easy to use and readily available navigation satellite systems are providing round the clock position information for seafarers, but denial of these services by jamming or spoofing techniques have become frequent, and other means are needed to validate critical navigation information. This paper revisits traditional methods to estimate position and heading of a vessel and offers a framework for computerized calculation of these basic observables without the use of radio-borne external information. Using radar and sea chart information, the paper investigates the quality of navigation information based on observed location of beacons, landmarks, coastlines and buoys. The paper demonstrates convincing accuracy in both position and heading estimation.

Linear Track Underwater Carrier SINS Correction Method Based on Hydroacoustic Single Beacon

Precise positioning of underwater vehicles using only a single beacon for range measurement is one of the toughest challenges for underwater navigation, especially when the underwater vehicle travels along a straight path resulting in the system unobservable. In this paper, acoustic range measurements are combined with inertial navigation to determine the position of an underwater vehicle using two consecutive measurement points. The contributions of the work presented here are twofold: First, the underwater single beacon localization algorithm proposed in this paper is able to operate under a linear track, and give the solution of the method to reject multi-valuedness. Second, considering the actual work of underwater carriers, extending the strategy to any trajectory can be used. The results obtained by the algorithm are fed back to the inertial navigation system, which can suppress the continued dispersion of inertial navigation errors. The experimental results show that the proposed “Linear track underwater carrier Strapdown Inertial Navigation System (SINS) correction method based on hydroacoustic single beacon” can solve the positioning problem of underwater long-range carriers and suppress further dispersion of their inertial navigation system errors.

Selecting the Beacon Locations in a Radio Navigation System for Lunar Missions

Selecting the Beacon Locations in a Radio Navigation System for Lunar Missions

IoT Based Bus Tracking System

Tracking of public bus location requires a GPS device to be installed, and lots of bus operators in developing countries don't have such an answer in situ to supply an accurate estimation of bus time of arrival (ETA). Without ETA information, it's very difficult for the overall public to plan their journey effectively. In this paper, implementation of an innovative IOT solution to trace the real time location of buses without requiring the deployment of a GPS device is discussed. It uses Bluetooth Low Energy (BLE) proximity beacon to trace the journey of a bus by deploying an Estimate location beacon on the bus. BLE detection devices (Raspberry Pi 4) are installed at selected bus stops along the path to detect the arrival of buses. Once detected, the situation of the bus is submitted to a cloud server to compute the bus ETAs. A field trial is currently being conducted in Johor, Malaysia together with an area bus operator on one single path. Our test results showed that the detection of BLE beacons is extremely accurate and it's feasible to trace the situation of buses without employing a GPS device during a cost-effective way.

Using Bluetooth Low Energy for positioning systems within overcrowded environments: A real in-field evaluation

Bluetooth Low Energy (BLE) is a widely-used technology for short-range proximity and distance estimation. The existence of human bodies is proved to influence BLE signals. In this paper, the effect of overcrowdedness on the performance of BLE-based positioning systems is studied. Real experiments are conducted in places with large and small areas. Both proximity and location beacons are evaluated with different transmission powers. Compared to uncrowded environments, results show random, but often manageable, changes in the received signal strength and position estimation accuracy. The logarithmic path loss model is found unsuitable for small areas and its parameters are noticeably affected by the crowdedness. Location beacons are found more robust against the increase in crowdedness than proximity counterparts. For these location beacons, the overcrowdedness maximally changes the signal strength by 8.6 dBm, the coverage range by 24 m, the proximity estimation accuracy by 18%, and the distance estimation accuracy by 41%.

Calibration of Visible Light Positioning Systems with a Mobile Robot

Most indoor positioning systems require calibration before use. Fingerprinting requires the construction of a signal strength map, while ranging systems need the coordinates of the beacons. Calibration approaches exist for positioning systems that use Wi-Fi, radio frequency identification or ultrawideband. However, few examples are available for the calibration of visible light positioning systems. Most works focused on obtaining the channel model parameters or performed a calibration based on known receiver locations. In this paper, we describe an improved procedure that uses a mobile robot for data collection and is able to obtain a map of the environment with the beacon locations and their identities. Compared to previous work, the error is almost halved. Additionally, this approach does not require prior knowledge of the number of light sources or the receiver location. We demonstrate that the system performs well under a wide range of lighting conditions and investigate the influence of parameters such as the robot trajectory, camera resolution and field of view. Finally, we also close the loop between calibration and positioning and show that our approach has similar or better accuracy than manual calibration.

Precision location approach in deep-space optical communications.

A traditional beacon location method is difficult to apply to a deep space optical communications link due to the high laser power required for long distances. The use of natural celestial bodies as beacon images can solve this problem. The correct location of the beacon is critical to establish and maintain an optical communications link. Therefore, in this paper we propose an approach to determine the location of a natural celestial beacon. To identify a beacon in an uncertain region, the phase correlation between the detected and reference images is applied. The influence of an image translation is eliminated through a Fourier transform, and the scaling and rotation are converted into the translation and solved using a log-polar transformation and phase correlation, respectively. The availability of a new approach is verified by the experiment. A field-programmable gate array embedded processing system is designed to realize the proposed algorithm. When the image noise is considered, the success probability of the algorithm can reach more than 96%. We believe this work is beneficial for deep space optical communications system design.

Real-Time Navigation for Drogue-Type Autonomous Aerial Refueling Using Vision-Based Deep Learning Detection

This article develops a deep learning object detector to provide accurate six-degree-of-freedom (DoF) information of the drogue relative to a monocular camera onboard a flying unmanned aerial vehicle. An object detector helps to provide the needed information for an autonomous vehicle to dock and refuel without the need for human intervention. This object detector can detect eight different beacons by training on 8746 images of a mock drogue. Once these beacons were detected, a nonlinear least squares algorithm that uses the collinearity equations as a system model takes the beacon's location on the captured image to provide an accurate six-DoF navigation solution. These navigation solutions from the object detector were evaluated on multiple metrics and then compared to navigation solutions provided by a VICON motion tracking system. Finally, Monte Carlo analysis, using the collinearity equations as a system model, evaluates an object detector's performance with various noise levels.

Landmark Augmentation for Mobile Robot Localization Safety

As more robots, such as autonomous vehicles, are deployed in life-critical situations it is imperative to consider safety, and in particular, localization safety. While it would be ideal to guarantee localization safety without having to modify the environment, this is not always possible and one may have to add landmarks or active beacons for landmark-based localization. As such, this work introduces a method to identify the minimum places in an environment where landmarks can be added to ensure localization safety, as quantified using integrity risk, the probability of undetected sensor errors causing localization failure while accounting for measurement faults. The letter formulates the problem as a systematic minimization: given the robot's trajectory and the current landmark map, add the minimum number of new landmarks such that the integrity risk along the trajectory is below a given safety threshold. The letter proposes three algorithms: a naive approach, Integrity-based Landmark Generator (I-LaG), and Fast I-LaG. The computationally expensive naive algorithm serves as a reference to illustrate simple scenarios. I-LaG adds relatively fewer landmarks than the Fast I-Lag algorithm but is more computationally expensive. Simulation and experimental results validate the proposed algorithms.

A Distributed Radio Beacon/IMU/Altimeter Integrated Localization Scheme with Uncertain Initial Beacon Locations for Lunar Pinpoint Landing.

As a growing number of exploration missions have successfully landed on the Moon in recent decades, ground infrastructures, such as radio beacons, have attracted a great deal of attention in the design of navigation systems. None of the available studies regarding integrating beacon measurements for pinpoint landing have considered uncertain initial beacon locations, which are quite common in practice. In this paper, we propose a radio beacon/inertial measurement unit (IMU)/altimeter localization scheme that is sufficiently robust regarding uncertain initial beacon locations. This scheme was designed based on the sparse extended information filter (SEIF) to locate the lander and update the beacon configuration at the same time. Then, an adaptive iterated sparse extended hybrid filter (AISEHF) was devised by modifying the prediction and update stage of SEIF with a hybrid-form propagation and a damping iteration algorithm, respectively. The simulation results indicated that the proposed method effectively reduced the error in the position estimations caused by uncertain beacon locations and made an effective trade-off between the estimation accuracy and the computational efficiency. Thus, this method is a potential candidate for future lunar exploration activities.

Adaptive Context-Aware Design Using Context State Information for the Internet of Things Paradigm

In the Internet of Things (IoT) paradigm, context state information plays a critical role in advancing the development of adaptive pervasive applications. Pervasive services and context-aware computing are emerging as the next computing paradigms in which infrastructure and services are seamlessly available anywhere, anytime, and in any format. The IoT paradigm raises new opportunities and demands on the underlying systems, in particular, the need to have systems that are adaptive and context-aware using context state information. In this paper, we introduce a new adaptive context state design technique to model context-aware applications that are sensitive to context state information changes. Each context change event is captured, interpreted and reacted to so that applications and users use only the functionality and adaptability needs that are solutions to their needs. The solution is modeled using Finite State Machine (FSM) and semantic localization so that context state information within the IoT paradigm is aligned to events. The semantic localization process precisely estimates the proximity location of the user along with the quality of context (QoC) attributes using the Bluetooth cell-based approach. This semantic information is useful in determining and inferring the user activities in a location. The QoC attributes are used to determine the confidence of the user location and range of the Bluetooth beacons within the IoT domain. This will, in turn, be used to determine whether the user is in the location or not. The alignment technique in our model represents the proper and new solution concerning functionality and adaptability needs expressed by other user applications in the IoT environment. The experimental scenario results indicate that a user can continue to enjoy their daily activities while the IoT application adapts continuously to their changing needs and notifying service providers of the changes according to the events of the user.

Foldable All‐Textile Cavity‐Backed Slot Antennas for Personal UWB Localization

AbstractAn all‐textile multimoded cavity‐backed slot antenna has been designed and fabricated for body‐worn impulse radio ultra‐wideband (IR‐UWB) operation in the 3,744–4,742.4 MHz frequency band, thereby covering Channels 2 and 3 of the IEEE 802.15.4a standard. Its light weight, mechanical flexibility, and small footprint of 35 mm 56 mm facilitate integration into textile for radio communication equipment for first aid responders, personal locator beacons, and equipment for localization and medical monitoring of children or the elderly. The antenna features a stable radiation pattern and reflection coefficient in diverse operating conditions such as in free space, when subject to diverse bending radii and when deployed on the torso or upper right arm of a test person. The high isolation toward the wearer's body originates from the antenna's hemispherical radiation pattern with a 3 dB beamwidth of and a front‐to‐back ratio higher than 11 dB over the entire band. Moreover, the antenna exhibits a measured maximum gain higher than 6.3 dBi and a radiation efficiency over %. In addition, orientation‐specific pulse distortion introduced by the antenna element is analyzed by means of the System Fidelity Factor (SFF). The SFF of the communication link between two instances of this antenna is higher than 94% for all directions within the antenna's 3 dB beamwidth. This easily wearable and deployable antenna is suitable to support IR‐UWB localization with an accuracy in the order of 5 cm.

A Novel Underwater Location Beacon Signal Detection Method Based on Mixing and Normalizing Stochastic Resonance.

A flight data recorder (FDR) is an electronic recording device placed in an aircraft for the purpose of facilitating the investigation of aviation accidents. If an aircraft crashes into water, an underwater locator beacon (ULB), which is installed on the FDR, is triggered by water immersion, and emits an ultrasonic 10 ms pulse signal once per second at 37.5 kHz. This pulse signal can be detected by sonar equipment. However, the ULB signal only can be detectable 1–2 kilometers from the surface in normal conditions. Stochastic resonance (SR) is a rising theory in the field of weak signal detection. The classical stochastic resonance limits state that the input must be small-parameter and the sampling frequency must be 50 times higher than the signal frequency. It cannot be applied to the ULB signal detection. To resolve this problem, this paper presents a novel approach named mixing and normalizing stochastic resonance (MNSR). By mixing the ULB signal and normalizing SR system parameters, MNSR provides a new way to detect weak ULB signal. Meanwhile, we propose the parameters adjustment method of MNSR. We prove the effectiveness through numerical simulation. An experiment in a tank is employed to verify the practicability of this method.

Low energy ultrasonic single beacon localization for testing of scaled model vehicle

Tracking the location (position) of a surface or underwater marine vehicle is important as part of guidance and navigation. While the Global Positioning System (GPS) works well in an open sea environment but its use is limited whenever testing scaled-down models of such vehicles in the laboratory environment. This paper presents the design, development and implementation of a low energy ultrasonic augmented single beacon-based localization technique suitable for such requirements. The strategy consists of applying Extended Kalman Filter (EKF) to achieve location tracking from basic dynamic distance measurements of the moving model from a fixed beacon, while on-board motion sensor measures heading angle and velocity. Iterative application of the Extended Kalman Filter yields x and y co-ordinate positions of the moving model. Tests performed on a free-running ship model in a wave basin facility of dimension 30 m by 30 m by 3 m water depth validate the proposed model. The test results show quick convergence with an error of few centimeters in the estimated position of the ship model. The proposed technique has application in the real field scenario by replacing the ultrasonic sensor with industrial grade long range acoustic modem. As compared with the existing systems such as LBL, SBL, USBL and others localization techniques, the proposed technique can save deployment cost and also cut the cost on number of acoustic modems involved.