GNSSs, Signals, and Receivers

This chapter describes Global Navigation Satellite Systems (GNSSs) and their signal characteristics, beginning with an overview of Global Positioning System (GPS) architecture and describing its three primary segments: control, space, and user segments. After that, it addresses the GPS modernization program including the new civilian and military signals and their significance. It continues by outlining the GPS signal characteristics and the sources of GPS measurement error. GPS receivers as well are briefly described. Then, it gives an overview of the GLONASS and describes its modernization program. Additionally, it delves into many aspects the GLONASS, including GLONASS signal characteristics, the GLONASS radio frequency (RF) plan, pseudorandom (PR) ranging codes, and the intra-system interference navigation message. Finally, GPS and GLONASS are compared to highlight the advantages of combined GPS and GLONASS measurements over the GPS-only measurements

GNSS Error Sources

This chapter discusses the most serious sources of error affecting global navigation satellite systems (GNSS) signals, classifying these in a new way, according to their nature and/or effects. For instance, errors due to clock bias or drift are grouped together. Errors related to the signal propagation medium, too, are treated in the same way. GNSS errors need to be corrected to achieve accepted positioning and navigational accuracy. We provide a theoretical description for each source, supporting these with diagrams and analytical figures where possible. Some common metrics to measure the magnitude of GNSS errors, including the user equivalent range error (UERE) and the dilution of precision (DOP), are also presented. The chapter concludes with remarks on the significance of the sources of error

Demonstrating the Merits of Integrating Multipath Signals into 5G LoS-Based Positioning Systems for Navigation in Challenging Environments

Constrained environments, such as indoor and urban settings, present a significant challenge for accurate moving object positioning due to the diminished line-of-sight (LoS)communication with the wireless anchor used for positioning. The 5th generation new radio (5G NR) millimeter wave (mmWave) spectrum promises high multipath resolvability in the time and angle domain, enabling the utilization of multipath signals for such problems rather than mitigating their effects. This paper investigates the benefits of integrating multipath signals into 5G LoS-based positioning systems with onboard motion sensors (OBMS). We provide a comprehensive analysis of the positioning system's performance in various conditions of erroneous 5G measurements and outage scenarios, which offers insights into the system's behavior in challenging environments. To validate our approach, we conducted a road test in downtown Toronto, utilizing actual OBMS measurements gathered from sensors installed in the test vehicle. The results indicate that utilization of multipath signals for wireless positioning operating in multipath-rich environments (e.g. urban and indoor) can bridge 5G LoS signal outages, thus enhancing the reliability and accuracy of the positioning solution. The redundant measurements obtained from the multipath signals can enhance the system's robustness, particularly when low-cost 5G receivers with a limited resolution for angle or range measurements are present. This holds true even when only considering the utilization of single-bounce reflections (SBRs)

Personalized Quantification of Facial Normality using Artificial Intelligence

While congenital facial deformities are not rare, and surgeons typically perform operations to improve these deformities, currently the success of the surgical reconstruction operations can only be “measured” subjectively by surgeons and specialists. No efficient objective mechanisms of comparing the outcomes of plastic reconstruction surgeries or the progress of different surgery techniques exist presently. The aim of this research project is to develop an efficient software application that can be used by plastic surgeons as an objective measurement tool for the success of an operation. The long-term vision is to develop a software application that is user-friendly and can be downloaded on a regular laptop and used by doctors and patients to assess the progress of their surgical reconstruction procedures. The application would work by first scanning a face before and after an operation and providing the surgeon with a normality score of the face from 0 to 3 where 3 represents normal and 0 represents extreme abnormality. A score will be given when the face is scanned before and after surgery. The difference between those scores is what we will call the delta. A high delta value would point to a high improvement in the normality of a face post-surgery, and a low delta value would indicate a small improvement. The first chapter of the thesis represents the introduction which describes the general aspects of the project. The second chapter presents the methodology employed for building the application and the existing solutions and proposed functional model structure. The results chapter presents the process behind collecting and labeling the image database and analyzes the scores produced by the program when fed with new images from the database. Finally, the last chapter of this thesis presents the conclusions. The list of references completes this work

Effect of Bioptron Light Therapy on post-menopausal low back pain: A randomized controlled study

Women's bodies undergo numerous changes throughout the post-menopausal period, many of which result in uncomfortable symptoms, including skeletal problems such as low back pain (LBP). The aim of this study was to evaluate the impact of Bioptron Light Therapy (BLT) on post-menopausal LBP in women. This study employed a pretest-posttest randomized experimental trial design. Forty post-menopausal women with LBP, aged 50 to 60 years, were randomized into two groups (study and control group). The control group (Group A, n=20) received abdominal and back isometric exercises only, whereas the study group (Group B, n=20) received BLT in addition to the same isometric exercises, three sessions per week for six weeks. Pain severity using the Visual Analogue Scale (VAS), Pain Pressure Threshold (PPT) using a pressure algometer, and functional disability using the Modified Oswestry Disability Questionnaire (MODQ) were measured for all patients in both groups before and after the treatment program. The Statistical Package of Social Sciences (SPSS) (version 19) was used for data analysis. Based on the results of our study, PPT significantly increased in both groups after treatment (p = 0.0001), with the study group showing a greater increase than the control group (p = 0.001). Pain intensity decreased significantly in both groups (p = 0.0001), with a statistically significant difference favoring the study group (p = 0.0001). MODQ scores also significantly decreased in both groups (p = 0.0001), again favoring the study group (p = 0.0001). BLT can be included as a valuable, effective, and non-invasive method for decreasing pain and improving function for women with post-menopausal LBP

An enhanced error model for EKF-based tightly-coupled integration of GPS and land vehicle’s motion sensors

Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers’ measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer’s errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories’ data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance

INS/GPS/LiDAR integrated navigation system for urban and indoor environments using hybrid scan matching algorithm

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory

Adaptive covariance estimation method for LiDAR-Aided multi-sensor integrated navigation systems

The accurate estimation of measurements covariance is a fundamental problem in sensors fusion algorithms and is crucial for the proper operation of filtering algorithms. This paper provides an innovative solution for this problem and realizes the proposed solution on a 2D indoor navigation system for unmanned ground vehicles (UGVs) that fuses measurements from a MEMS-grade gyroscope, speed measurements and a light detection and ranging (LiDAR) sensor. A computationally efficient weighted line extraction method is introduced, where the LiDAR intensity measurements are used, such that the random range errors and systematic errors due to surface reflectivity in LiDAR measurements are considered. The vehicle pose change is obtained from LiDAR line feature matching, and the corresponding pose change covariance is also estimated by a weighted least squares-based technique. The estimated LiDAR-based pose changes are applied as periodic updates to the Inertial Navigation System (INS) in an innovative extended Kalman filter (EKF) design. Besides, the influences of the environment geometry layout and line estimation error are discussed. Real experiments in indoor environment are performed to evaluate the proposed algorithm. The results showed the great consistency between the LiDAR-estimated pose chan

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication