Characteristics of Angular Precision and Dilution of Precision for Optical Wireless Positioning

Dilution of precision (DOP) for time-of-arrival (TOA) or time-difference-of-arrival (TDOA) positioning systems has been thoroughly investigated. This is not the case for angle-of-arrival (AOA) positioning systems, especially three dimensional AOA systems. However, the recent increase in deployment of antenna arrays and multipath mitigation techniques make AOA systems more attractive. In this paper, the DOPs for position systems using range measurements are reviewed and an expression for 3D AOA DOP is derived. The average values of DOPs for different deployments of base station geometries are examined. It is found that for a 3D AOA system, unlike TOA or TDOA systems, vertical DOP (VDOP) is generally smaller than horizontal DOP (HDOP), and the best VDOP can be achieved when the base stations are at the same height as the user. Moving the base stations away from the plane of the user may decrease the HDOP and Geometric DOP (GDOP) slightly, but it also increases the VDOP. For applications that the height of the user changes frequently, the base stations should be deployed with height close to half the height of the area of interest.

Optical wireless (OW) technology has attracted significant interest for indoor positioning in the past decade. An emerging form of this technology makes use of angle-of-arrival (AOA) measurements to carry out positioning via triangulation off of an optical beacon grid. Such AOA-based OW positioning systems can yield accurate position estimates—but only given sufficient attention to the optical receiver. The design, operation, and implementation of such a receiver are presented in this work. The optical receiver is designed to have a sufficiently small AOA error, being σAOA = 1°, over a wide angular field-of-view (FOV), being 100°. The design allows the optical receiver to carry out positioning based off a 3 × 3 grid of optical beacons, where each optical beacon is uniquely identified using multiple frequency and color channels. The optical beacons are widely spaced to fully utilize the optical receiver's wide angular FOV. The overall AOA-based OW positioning system exhibits a position error of 1.7 cm, which is comparable to those obtained by more complex positioning systems. Thus, the presented AOA-based technologies can play a role in emerging indoor positioning systems.

Global Positioning System (GPS) satellites signal processing to obtain all in view satellite measurements and to use them to find a solution and to do integrity monitoring forms a major component of the load on the receiver's processing element. If processing capability is limited there is restriction on the number of measurements which can be obtained and processed. Alternatively, the number of measurements can be restricted and the resulting saving in load on the processor can be used to offer more spare processing time which can be used for other user specific requirements. Thus if m visible satellites can provide measurements only n measurements can be used (n < m). The arrangement and the number of GPS satellites influence measurement accuracy. Dilution of Precision (DOP) is an index evaluating the arrangement of satellites. Geometric DOP (GDOP) is, in effect, the amplification factor of pseudo-range measurement errors into user errors due to the effect of satellite geometry. The GDOP approximation is an essential feature in determining the performance of a positioning system. In this paper, knowledge-based methods such as neural networks and evolutionary adaptive filters are presented for optimum approximation of GDOP. Without matrix inversion required, the knowledge-based approaches are capable of evaluating all subsets of satellites and hence reduce the computational burden. This would enable the use of a high-integrity navigation solution without the delay required for many matrix inversions. Models validity is verified with test data. The results are highly effective techniques for GDOP approximation.

Geometric dilution of precision (GDOP) is defined as the ratio of the root-mean-square position determination error to the root-mean-square measurement error. Based on the Cramer-Rao lower bound (CRLB), new mathematical expressions of GDOP are presented in Time-of-Arrival (TOA) and Angle-of-Arrival (AOA) positioning systems in this paper. The expressions obviously reveal that the geometrical shape of the anchor nodes make a significant influence on GDOP. Then the influence of adding a new anchor node at different locations is analyzed. Simulations show that in both positioning systems, two optimal placement angles exist to make the GDOP smallest, when the original anchor nodes are no uniformly scattered. However, when uniformly scattered, the GDOP keeps constant no matter what angle the new anchor node is placed at. In AOA positioning systems, the GDOP is also affected by the distance between the newly added anchor node and the target, and increases when the distance increases. Meanwhile, the GDOP is always reduced when more anchor nodes are used.

Geometric Dilution Of Precision (GDOP) is a factor that describes the effect of geometry on the relationship between measurement error and position determination error. It is used to provide an indication of the quality of the solution. Conventional closed-form GDOP calculation formula applied to all possible combinations of visible satellites is rather time consuming, especially as the number of satellites grows. Approximations, such as the maximum volume method, are faster but optimum selection is not guaranteed. In this paper, a more concise but efficient solution for the calculation of GDOP value in the case of four Global Positioning System (GPS) satellites is firstly reviewed and then extended to cover the other forms of dilution of precision (DOP) values, including vertical DOP (VDOP) and horizontal DOP (HDOP). Secondly, a review and extension of the conventional solution is performed in the case of three GPS satellites aided by an altimeter. Based on the ideas gained from these two approaches, a simpler closed-form DOP formula for three GPS satellites aided by an altimeter is derived. The advantage of the proposed formulation is that it is simpler and thus reduces the computational load in comparison to the conventional one.

Positioning of User Equipment (UE) in 5G Ultra-Dense Networks (UDN) promises significant improvement in location accuracy estimation due to densification of Access Points (AP) infrastructure. For range and bearing primary measurements network geometry plays a significant role in the resultant positioning accuracy, regardless of time (TOA) and angle (AOA) of arrival secondary processing technique. Existing approaches for positioning system topology search in terrestrial cellular networks utilize geometric dilution of precision (GDOP) minimization under certain conditions, satisfying application requirements. Drawback of existing approaches, yielding tractable analytical results, is that they predominantly have assumption of 2-dimensional (2D) AP distribution according to regular hexagonal grid, square lattice or Poisson point process (PPP). If for previous 2G-4G cellular networks it is justified, for 5G UDN these assumptions do not retain. According to latest 3GPP specifications, enhanced positioning service area should provide sub-meter 3D UE location estimation in horizontal and vertical planes. The contribution of current research is a simulation model for 5G UDN positioning system topology search using well known in Global Navigation Satellite Systems (GNSS) horizontal (HDOP), vertical (VDOP) and position (PDOP) dilution of precision (DOP) criterion. Simulation results reveal, that fixed AP number topology, achieving DOP criterion in horizontal plane, does not provide satisfying DOP in vertical one.

The signal level in an optical wireless receiver is weakest at the front end of the receiver due to the photodetector capacitance. Most of the papers have been previously reported successfully in bandwidth enhancement using bootstrapping technique. This paper introduces a series-shunt bootstrapping circuit which is boosted up the bandwidth to GHz. The modeling of the circuit exploits a series-shunt positive capacitive feedback. Feedback is applied to a buffered differential pair to obtain a bootstrap action. The result is only based on the modeling using MATLAB. Utilizing the dissimilar values of photodetector capacitance, the bandwidth does not alter to a great extent. Therefore, this circuit is suitable to implement in high noise environment especially in optical wireless link.

Signals in global navigation satellite systems (GNSS) due to weak power are vulnerable to structural interferences which can lead to a significant deviation of the position solution from its true value. In aviation, UAV-controlling or some another life critical applications misleading coordinate information is a great threat so that procedures to detect such GNSS integrity failure are under a big concern. This paper is focused on decision-making algorithm for the failure detection applied to Angle-of-Arrival (A-o-A) integrity monitoring method in a case when the fixed decision threshold is preset in accordance with false alarm probability restricted for all possible observing satellite constellations. Decision threshold value was obtained for a different number of satellites by statistical simulations for quite a number of randomly generated satellite constellations with suitable geometric dilution of precision (GDOP) level. Minimum number of navigation signals was estimated for the situation when the simplest three elements antenna array implemented on compact UAV is used for a direction-finding procedure. As a result A-o-A integrity monitoring efficiency was estimated for real GPS satellite constellation under conditions when decision threshold was fixed as insensitive to satellite constellation geometry.

To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.

This study explores a data collection system using an optical wireless code-division multiple access (CDMA) scheme. The system's transmitters asynchronously send data to a base station receiver. In CDMA systems, communication performance may degrade because of the near-far problem caused by variations in propagation path length between each transmitter and the receiver. To solve this problem, this paper proposes a new base-station receiver structure that employs hard limiters to restrict the amplitude of strong signals and successive interference cancellers to eliminate the effects of residual signals, and shows the advantages of this new combination method over existing methods that use hard limiters or successive interference cancellers independently.

The new design and analysis presented in the paper are on an intelligent emergency location and response system that is specifically designed within the framework of university campuses, and one of the case studies is the deployment of the system on the Al-Ayen Iraqi University. The system network integrates a multi-sensor network with acoustic arrays, thermal cameras, smoke/ gas sensors, vibration sensors, and electrical fault chips, which work together with the extremely precise angle-of-arrival (AOA) research algorithms. The system is capable of working in a wireless ad-hoc sensor network and thus offers secure communication to ensure that the data integrity, confidentiality, and timely responsiveness can be reached, and avoid security problems like unauthorized access, data tampering, and signal interference. It is coded to identify, categorize, and locate any disaster, including fires, electrical outages, and collapses of the structure (among others), with the use of such techniques as the Multiple Signal Classification (MUSIC) algorithm and triangulation. Simulation and experimental findings were encouraging: the localization error of about 5 meters, detection latency of about 1 second, classification error of more than 97% and over 40% reduction in dispatch time. Security has also been put in place so that the system is not accessed accidentally and compromised, which is an aspect that renders the system a strong system in real-life situations. The system reduced the approximate dispatch time from between 120 seconds to approximately 75 seconds as opposed to the dependency on a printed circuit board (PCB) antenna. It has been demonstrated that the system has an availability of 99% over a 30-day period, and it has a high sensor failure resistance by Geometric Dilution of Precision (GDOP) testing and error confidence. An interface that offers real-time visualization of the events assists in the management of emergency response by providing the event that is taking place in the form of a graph to alert the responders.

With the continuous development and improvement of global navigation satellite systems (GNSS), over a hundred navigation satellites now provide precise and reliable positioning services to various types of users. Most existing satellite selection methods adopt geometric dilution of precision (GDOP) as the selection criterion, which considers only the satellite geometric configuration while neglecting the quality of satellite observations. Consequently, the selected satellite set does not always yield ideal positioning results. To address this issue, we propose a satellite selection criterion that combines the near real-time accuracy of satellite observations with geometric configuration. The near real-time accuracy is estimated based on recent short-term observation data. This method estimates the near real-time accuracy of satellite observations using the Melbourne-Wübbena (MW) combination observation and uses this accuracy to weight and compute the weighted geometric dilution of precision (WGDOP-NRT) for satellite selection. Preliminary experimental results demonstrate that, compared to other criteria, the satellite sets selected using WGDOP-NRT achieve shorter convergence times and higher convergence accuracy in the standard precise point positioning (PPP) model. However, the frequent changes in satellite sets between epochs may negatively affect the positioning performance. To mitigate this issue, we propose an improved satellite selection strategy. If the WGDOP-NRT of the satellite set selected in the previous epoch remains below a predefined threshold in the current epoch, the same satellite set is retained. The method for determining the threshold has also been further discussed. This strategy maintains the geometric configuration and observation quality of the satellite set while enhancing its time correlation in satellite selection. Further experimental results indicate that using WGDOP-NRT and the proposed strategy improves PPP performance in both static and dynamic scenarios.

The number of visible satellites has significantly increased, which provides a possibility for high-precision positioning of global navigation satellite systems (GNSSs). However, GNSS receivers with higher computing power will be required owing to the usage of a large number of visible satellites, and selection of partial satellites with better spatial geometry is required for obtaining high positioning precision schemes for a variety of applications. The geometric dilution of precision (GDOP) is related to the geometrical arrangement of the user and the satellites and computationally intensive, involving matrix multiplication and inversion operations. Various intelligent algorithms for satellite selection have been suggested recently, such as genetic algorithms (GAs). the computation number of GDOP was reduced, owing to the adoption and optimization of these algorithms. However, the algorithms suffer from two issues: 1) the computation process is complex, and significant parametric tuning is required. 2) the algorithms may fall into local optima, instead of the global optimum, owing to the stochasticity of the optimization process. In the paper, we have proposed a novel algorithm for satellite selection, based on chaotic particle swarm optimization (CPSO), which has the advantages of faster convergence, a smaller number of adjustable parameters, and stronger adaptability, compared with the existing algorithms. Firstly, the visible satellites received by the GNSS receiver are continuously encoded and randomly grouped, form the initial population. Afterward, the positions of the particles are updated by the PSO’s velocitydisplacement model. Finally, the CPSO-based algorithm for selection of satellites is designed to replace poor-performing particles with particles in the initial population, which helps to effectively avoid sub-optimal solutions. The proposed algorithm was compared with the traversal method. The simulation results demonstrated that if more than five satellites are selected, the satellite selection time amounts to 37.5% of the time required by the traversal method, and the GDOP error is in the 0.7 range. The proposed algorithm was further validated on the BDS/GPS integrated navigation satellite selection, suggesting the effectiveness of the application in the multiple GNSSs integrated navigation.

Our objective is the development of a navigation system which is used in indoor spaces and supports activities of the visually impaired without the help of others. The system is composed of optical beacons which are set on the ceiling and emit the position code as an infrared signal, an optical receiver which receives signals from beacons, and a navigator which guides a user by an artificial voice. Three subjects with low vision were tested in a hospital with our navigation system. 49 optical beacons were set on the ceiling, and the subject equipped with an optical receiver and a navigator. Each subject walked from the start point to the destination following the guidance voice. From these experiment, the following characteristics became clear. (1) On a pathway where a subject can feel the wall, every subject could follow the navigation voice. (2) Some subjects couldn't go across a wide pathway in a straight line, and then the system lost their position. Therefore, if the problem of crossing the pathway is improved, our navigation system will be a very valuable one to support activities of the visually impaired.

Autonomous navigation is a crucial aspect of the visually impaired community’s pursuit of independence and social equity. To achieve this goal, visually impaired people (VIP) require a navigation and wayfinding system that works both outdoors and indoors. While outdoor navigation can rely on ubiquitous signals such as global navigation satellite system (GNSS), indoor navigation presents a significant challenge, especially in unfamiliar environments. Despite over two decades of research and development, the issue of delivering a high performance and cost-effective indoor positioning solution for VIPs remains unresolved. Bluetooth-based angle of arrival (AOA) positioning is a cost-effective method that offers accuracy ranging from upper decimeters to meters. However, it still faces challenges in detecting and mitigating outliers caused by nonline-of-sight (NLOS) and multipath effects during signal propagation. In light of these challenges, this article proposes a novel dead reckoning aided AOA Bluetooth indoor positioning system that utilizes a smart cane. The developed model takes into account the swinging characteristic of the cane, which is integral to visually impaired individuals’ mobility. Furthermore, this article incorporates a novel outlier detection and exclusion layer to reduce the impact of NLOS and multipath effects. The proposed system’s performance was evaluated through a series of experiments, and the positioning error distribution was analyzed. The results showed that the accumulated probability of errors less than 0.5 m was 93.56%, and 99.64% of errors were within 0.7 m. With the demonstrated high level of accuracy, the proposed system presents a promising solution for indoor navigation for VIPs.