Global Positioning System Navigation Research Articles

Indoor Positioning and Navigating System Application Using Wi-Fi with Fingerprinting Method and Weighted K-Nearest Neighbor Algorithm

The need for accurate indoor location determination, object tracking, digital maps and indoor travel routes is increasing along with the construction of buildings that have complex and spacious layouts. The current Global Positioning System navigation system is only effective for outdoor use. However, when used indoors it becomes inaccurate due to factors such as signal attenuation and multipath caused by wall obstructions in the building. This study designed an application of Indoor Positioning and Navigating System Using Wi-Fi with Fingerprinting method and Weighted K-Nearest Neighbor algorithm. In the design process, it is necessary to create a fingerprinting database by considering the number of Access points and environmental conditions. Based on the results of the study, the location results of the application show that from floors 1,2, and 3. Floor 1 has a room accuracy result of 89% and a point accuracy of 86% with an average deviation of 1.42 px or 0.9 m, floor 2 has room accuracy results. of 65% and a point accuracy of 70% with an average deviation of 2.43 px or 1.7 m, and the 3rd floor has a room accuracy of 86% and a point accuracy of 68% with an average deviation of 2.27 or 1.5 m. Based on the data above, this application is proven to be able to detect the position of someone in the room with a success percentage on the 1st floor by 90%, the 2nd floor by 55%, and the 3rd floor by 80%.

SAVE ME EMERGENCY DETECTION IN MOBILE APPLICATION FOR TEENAGERS

The smartphone comes with many advanced features such as Wi-Fi, Global Positioning System (GPS) navigation, high-resolution cameras, and a touchscreen with broadband access that help users stay connected worldwide. This study focused on the development of a system framework for mobile application in emergency services that triggered fall detection. The mobile application is named Save Me! Application (app), where it can provide a simple medium to provide safety awareness to public people, especially among teenagers. The app can pinpoint the victim’s exact location when the device triggers fall detection. Subsequently, the message can be distributed to relatives, parents, or friends who have been pre-registered in the app to help the victim. The app also offers additional protection to parents or families who are busy working so that they can keep track of their children.

Travel-Time Estimation by Cubic Hermite Curve

Travel time is a measure of time taken to travel from one place to another. Global Positioning System (GPS) navigation applications such as Waze and Google Maps are easily accessible presently and allow users to plan a route based on travel time from one place to another. However, these applications can only estimate general travel time based on a vehicle’s total distance and average safe speed without considering route curvature. A parametric cubic curve has shown a potential result in travel-time estimation through geometric properties. In this paper, travel time has been estimated using the curvature value obtained from the Hermite Interpolation curve fitted to each section of the selected road. Design speed is determined from the curvature value, and thus an algorithm for travel-time estimation incorporating initial driving information is developed. The proposed method’s accuracy was compared to the existing method’s accuracy using a real-life driving test. This comparison demonstrated that the proposed method estimates travel time more accurately than Google Maps and Waze. Future study can further improve the estimation by embedding traffic data into the algorithm.

Comparison of COSMIC and COSMIC-2 Radio Occultation Refractivity and Bending Angle Uncertainties in August 2006 and 2021

We compare the random error statistics (uncertainties) of COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate, C1) and COSMIC-2 (C2) radio occultation (RO) bending angles and refractivities for the months of August 2006 and 2021 over the tropics and subtropics using the three-cornered hat method. The uncertainty profiles are similar for the two RO missions in the troposphere. However, a higher percentage of C2 profiles reach close to the surface in the moisture-rich tropics, an advantage of the higher signal-to-noise ratio (SNR) in C2. C2 uses signals from both GPS (Global Positioning System) and GLONASS Global Navigation System Satellites (GNSS). The GPS occultations show smaller uncertainties in the stratosphere and lower mesosphere (30–60 km) than the GLONASS occultations, a result of more accurate GPS clocks. Therefore, C2 (GPS) uncertainties are smaller than C1 uncertainties between 30–60 km while the C2 (GLONASS) uncertainties are larger than those of C1. The uncertainty profiles vary with latitude at all levels. We find that horizontal gradients in temperature and water vapor, and therefore refractivity, are the major cause of uncertainties in the tropopause region and troposphere through the violation of the assumption of spherical symmetry in the retrieval of bending angles and refractivity.

Automated execution of a pest bird deterrence system using a programmable unmanned aerial vehicle (UAV)

Crop damage caused by pest birds is a big problem around the world. As many studies have shown, existing bird control methods have not met growers' expectations regarding efficacy, reliability, and cost. Researchers are investigating the potential of using unmanned aerial vehicles (UAVs) as a tool for bird deterrence in agricultural fields to address this challenge. UAV-based bird deterrence techniques investigated in the past needed human operators to locate bird flocks and fly UAVs to desired trajectories. This study focused on automating a UAV-based bird deterrence system to operate it in real-time. Specifically, we focused on; i) optimizing the existing machine vision system to detect and locate birds-like movement in a real-time; ii) dynamically creating and launching two intelligent UAV missions in real-time to scare incoming birds (target intercept mission) or birds that are already inside the field (field patrol mission); and iii) executing these missions independently (short duration mission) as well as jointly (longer missions with more variation) in a vineyard using a programmable UAV. Outdoor experiment was conducted to evaluate the mission execution efficiency of the proposed system using a programmable UAV without a built-in global positioning system (GPS). Simulated bird movements generated using waving human hands were used for evaluating the target intercept mission. Results show that the algorithms developed for automated operation completed ∼92% of the assigned tasks successfully during shorter mission and 90% of the task during longer mission. Despite, successful execution of algorithms, the automated system experienced major shortcomings due to the lack of GPS for navigation of the UAV, which can be improved using a GPS-enabled programmable UAV. Future work also includes full scale field evaluation using machine vision system to identify actual incoming birds to determine the efficiency in deterring birds in commercial operations.

Gravitational Perturbation Influence on High Altitude Satellite for different Inclination

Satellites have become such a vital part of our daily lives that we take for granted many of their functions, such as global positioning system (GPS) navigation and images of weather systems collected from orbit. In this work, The analytical method for third body perturbation on high Earth orbit satellites was investigated in this study for different inclinations (𝑖 = 1.71, 𝑖 = 5, 𝑖 = 10, 𝑖 = 23, 𝑖 = 25) across two revolution periods computed for short and long periods, Using the program celestial mechanics version 1 module (Beutler 2005) with input data given by the Two-Line Elements (TLE) created at the University of Bern's Institute of Astronomy. To determine the third body perturbation on Earth satellite using the collocation method. By analyzing the variation in the orbital elements, geocentric Coordinates and acceleration components by Matlab 2018, There was no discernible change in the coordinate system or acceleration components, which appeared to be secular in both results, change, and effect of perturbation has greatest point at Geocentric equatorial coordinates combinations. The conclusion indicates that the Moon perturbation has the most significant impact on orbital elements; furthermore, the satellite with increasing altitude has increasing the amount of perturbation.

Principle and performance of multi-frequency and multi-GNSS PPP-RTK

PPP-RTK which takes full advantages of both Real-Time Kinematic (RTK) and Precise Point Positioning (PPP), is able to provide centimeter-level positioning accuracy with rapid integer Ambiguity Resolution (AR). In recent years, with the development of BeiDou Navigation Satellite System (BDS) and Galileo navigation satellite system (Galileo) as well as the modernization of Global Positioning System (GPS) and GLObal NAvigation Satellite System (GLONASS), more than 140 Global Navigation Satellite System (GNSS) satellites are available. Particularly, the new-generation GNSS satellites are capable of transmitting signals on three or more frequencies. Multi-GNSS and multi-frequency observations become available and can be used to enhance the performance of PPP-RTK. In this contribution, we develop a multi-GNSS and multi-frequency PPP-RTK model, which uses all the available GNSS observations, and comprehensively evaluate its performance in urban environments from the perspectives of positioning accuracy, convergence and fixing percentage. In this method, the precise atmospheric corrections are derived from the multi-frequency and multi-GNSS observations of a regional network, and then disseminated to users to achieve PPP rapid AR. Furthermore, a cascade ambiguity fixing strategy using Extra‐Wide‐Lane (EWL), Wide-Lane (WL) and L1 ambiguities is employed to improve the performance of ambiguity fixing in the urban environments. Vehicle experiments in different scenarios such as suburbs, overpasses, and tunnels are conducted to validate the proposed method. In suburbs, an accuracy of within 2 cm in the horizontal direction and 4 cm in the vertical direction, with the fixing percentage of 93.7% can be achieved. Compared to the GPS-only solution, the positioning accuracy is improved by 87.6%. In urban environments where signals are interrupted frequently, a fast ambiguity re-fixing can be achieved within 5 s. Moreover, multi-frequency GNSS signals can further improve the positioning performance of PPP-RTK, particularly in the case of small amount of observations. These results demonstrate that the multi-frequency and multi-GNSS PPP-RTK is a promising tool for supporting precise vehicle navigation.

Women Well-being Application

Abstract: Safety and security of girls is one of the most serious issues of our time; the crime rate is rapidly rising, and female wellbeing has become a greater concern than ever before in today's world. Many studies show that the majority of crimes occur late at night, but women are unable to shut themselves in from twilight till dawn. Women can't expect to work exclusively the day shift in metropolitan places, where offices, convenience stores, gas stations, and other businesses are open 24 hours a day, seven days a week. In the last five years, the use of smart phones with GPS navigation systems has risen significantly. So, if mobile phones are used for so many other purposes, why not women's security? As a result, a smart phone can be effectively employed for personal safety or a variety of other protection objectives, particularly for women. This application alerts the guardians with just a single click. SMS with the user's live location is sent to the preconfigured contact. An alarming siren goes on when the user activates the app. This application also enlists the nearby hospitals and police stations. As a result, this app has the potential to significantly assist in the rescue of women from dangerous situations. Keywords: Smartphone, Android, GPS (Global Positioning System), Alert Message, Panic Button, Safety Tips, Women Security

Assessment of the performance of GPS/Galileo PPP-RTK convergence using ionospheric corrections from networks with different scales

The rapid convergence of precise point positioning real-time kinematics (PPP-RTK) with centimeter-level accuracy is of utmost importance for many applications. One way of accelerating this convergence is to explore the use of ionospheric models and multiple global navigation satellite system (GNSS) observations, e.g., Global Positioning System (GPS) and Galileo Satellite Navigation System (Galileo) observations. Because the temporal and spatial variations of the ionosphere are significant, convergence analysis of PPP-RTK should be investigated in networks with different scales, especially networks with large differences in their scales. This study describes the convergence performance of PPP-RTK using GPS/Galileo observations derived from networks with different scales under medium ionospheric conditions. Slant ionospheric corrections were first estimated from the reference network and then imported as virtual observations to enhance the convergence performance of PPP-RTK at the user interface. The results show that for the 165-km reference site spacing, the portions of single-differenced (SD) ionospheric residuals within 0.3 total electron content units (TECU) were 85.2% and 81.7% for the GPS and Galileo observations, respectively. Considering the 90th percentile of horizontal position errors, the PPP-RTK convergence time within the network with 165-km spacing was shortened from 2.5 min for GPS-only observations to 2.0 min for integrated GPS + Galileo observations. For the network of about 50 km, the proportions of the SD ionospheric residuals of the GPS and Galileo constellation within 0.3 TECU were 95.9% and 82.8%, respectively. The PPP-RTK convergence time of the 90th percentile horizontal positioning errors based on GPS-only observations was 2.0 min but 1.5 min based on integrated GPS + Galileo observations. Using GPS and Galileo observations, the convergence time could be reduced by 25% for the network with 50-km spacing. Our results suggest that the convergence time of PPP-RTK depends on the scale of the reference network and becomes shorter as the scale of the network decreases. Compared with the GPS-only PPP-RTK, the GPS/Galileo PPP-RTK could shorten the convergence time further.Graphical

A novel approach of efficient 3D reconstruction for real scene using unmanned aerial vehicle oblique photogrammetry with five cameras

In recent years, unmanned aerial vehicle (UAV) oblique photogrammetry is a new and advanced technology in the field of surveying and mapping. In this paper, an oblique photogrammeter with five high-precise measuring cameras is developed, which can be controlled by a microcontroller, positioned by Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS), and accessed through narrowband internet of things (NB-IoT) module interface. Meanwhile, distributed parallel computing and graphics processing unit (GPU) are used to improve the efficiency of 3D modeling for the real scene. Finally, the urban spatial information collected by UAV oblique photogrammetry and the real scene 3D modeling results are verified by experiments. The experiment results demonstrate that the method proposed in this paper can efficiently complete the collection of urban spatial information and improve the efficiency 3D modeling for the real scene. The proposed method has about 30% improved efficiency compared to the conventional methods.

Use of dynamic navigation system in endodontics: A literature review

Over the years, traditional endodontic approaches performed have caused significant loss of healthy tooth structure. Clinical approach became relatively predictable following the introduction of cone-beam computed tomography, Digital Imaging and Communications files, and dental operating microscopes. Despite these advances, mishaps such as excessive dentin loss and/or perforations may still occur during freehand preparations affecting the tooth's prognosis. Following the developments in surface scanning and three-dimensional printing, static guidance systems were introduced. However, they too had multiple drawbacks. Dynamic navigation systems (DNSs) were introduced following to overcome them. DNS is based on computer-aided navigation technology analogous to the Global Positioning System (GPS) navigation. New minimally invasive preparations have been put forward claiming to be the future of endodontics which can be achieved with the help of DNS. The review thus aims at evaluating the possible use of DNS in planning and executing these minimally invasive preparations without unnecessary loss of healthy tooth structure.

Accounting for Signal Distortion Biases for Wide-Lane and Narrow-Lane Phase Bias Estimation with Inhomogeneous Networks

Due to different designs of receiver correlators and front ends, receiver-related pseudorange biases, called signal distortion biases (SDBs), exist. Ignoring SDBs that can reach up to 0.66 cycles and 10 ns in Melbourne-Wübbena (MW) and ionosphere-free (IF) combinations can negatively affect phase bias estimation. In this contribution, we investigate the SDBs and evaluate the impacts on wide-lane (WL) and narrow-lane (NL) phase bias estimations, and further propose an approach to eliminating these SDBs to improve phase bias estimation. Based on a large data set of 302 multi-global navigation satellite system (GNSS) experiment (MGEX) stations, including 5 receiver brands, we analyze the characteristics of these SDBs The SDB characteristics of different receiver types for different GNSS systems differ from each other. Compared to the global positioning system (GPS) and BeiDou navigation satellite system (BDS), SDBs of Galileo are not significant; those of BDS-3 are significantly superior to BDS-2; Septentrio (SEPT) receivers show the most excellent consistency among all receiver types. Then, we apply the corresponding corrections to phase bias estimation for GPS, Galileo and BDS. The experimental results reveal that the calibration can greatly improve the performance of phase bias estimation. For WL phase biases estimation, the consistencies of WL phase biases among different networks for GPS, Galileo, BDS-2 and BDS-3 improve by 89%, 77%, 76% and 78%, respectively. There are scarcely any improvements of the fixing rates for Galileo due to its significantly small SDBs, while for GPS, BDS-2 and BDS-3, the WL ambiguity fixing rates can improve greatly by 13%, 27% and 14% after SDB calibrations with improvements of WL ambiguity fixing rates, the corresponding NL ambiguity fixing rates can further increase greatly, which can reach approximately 16%, 27% and 22%, respectively. Additionally, after the calibration, both WL and NL phase bias series become more stable. The standard deviations (STDs) of WL phase bias series for GPS and BDS can improve by more than 46%, while those of NL phase bias series can yield improvements of more than 13%. Ultimately, the calibration can make more WL and NL ambiguity residuals concentrated in ranges within ±0.02 cycles. All these results demonstrate that SDBs for phase bias estimation cannot be ignored and must be considered when inhomogeneous receivers are used.

Sweeping Robot Based on Laser SLAM

Path planning and positioning are the key problems of the navigation for robot. Traditional global positioning and navigation systems, such as the Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS), can not exactly collect information nearby, which makes it difficult to complete accurate positioning and navigation indoor. SLAM algorithm allows the robot to sense the environment through its own sensors, build a map of the environment, and calibrate its position, so that it can move in an unknown environment. The SLAM algorithm based on laser has stable ranging performance in small static scenes, which is less affected by the light intensity. Therefore, in order to achieve precise positioning and navigation, the laser SLAM algorithm is applied to the sweeping robot indoor in this paper. The tests show that in the ROS operating system, the sweeping robot achieves precise positioning and plans the optimal path based on the laser SLAM algorithm, which better realizes the automatic control for the robot.

A Tomographic Method for the Reconstruction of the Plasmasphere Based on COSMIC/ FORMOSAT-3 Data

A tomographic method has been developed for reconstructing the topside ionospheric and plasmaspheric electron density distribution using total electron content (TEC) measurements from global positioning system (GPS) receivers aboard the constellation observing system for meteorology, ionosphere, and climate&#x002F;Formosa Satellite Mission 3 (COSMIC&#x002F;FORMOSAT-3). Since the COSMIC&#x002F;FORMOSAT-3 constellation has an orbit altitude of about 800 km, the integral TEC measurements obtained from the topside GPS navigation data are rather small and imposed relevant challenges to obtaining stable electron density reconstructions. However, the developed method can represent the natural variability of the plasma ambient in terms of latitude, altitude, solar activity, season, and local time when analyzing electron density reconstructions during 2008&#x2013;2013. The method employs independent spatial grids for satellite rising and setting geometries and imposes a set of constraints to stabilize the solution in the presence of noise and ill-conditioned geometry. We further consider background ionosphere and plasmasphere models for electron density initialization and filling data gaps. The quality assessment using TEC and <i>in-situ</i> electron density measurements has shown that the proposed method performs better than the background model, with improvements of about 26&#x0025; in TEC and 20&#x0025; in terms of electron density. Our investigation also reveals the necessity of more accurate background electron density representations and precise TEC measurements in order to have better plasmaspheric specifications at high altitudes.

Variational Bayesian Based IMM Robust GPS Navigation Filter

This paper investigates the navigational performance of Global Positioning System (GPS) using the variational Bayesian (VB) based robust filter with interacting multiple model (IMM) adaptation as the navigation processor. The performance of the state estimation for GPS navigation processing using the family of Kalman filter (KF) may be degraded due to the fact that in practical situations the statistics of measurement noise might change. In the proposed algorithm, the adaptivity is achieved by estimating the time-varying noise covariance matrices based on VB learning using the probabilistic approach, where in each update step, both the system state and time-varying measurement noise were recognized as random variables to be estimated. The estimation is iterated recursively at each time to approximate the real joint posterior distribution of state using the VB learning. One of the two major classical adaptive Kalman filter (AKF) approaches that have been proposed for tuning the noise covariance matrices is the multiple model adaptive estimate (MMAE). The IMM algorithm uses two or more filters to process in parallel, where each filter corresponds to a different dynamic or measurement model. The robust Huber's M-estimation-based extended Kalman filter (HEKF) algorithm integrates both merits of the Huber M-estimation methodology and EKF. The robustness is enhanced by modifying the filter update based on Huber's M-estimation method in the filtering framework. The proposed algorithm, referred to as the interactive multi-model based variational Bayesian HEKF (IMM-VBHEKF), provides an effective way for effectively handling the errors with time-varying and outlying property of non-Gaussian interference errors, such as the multipath effect. Illustrative examples are given to demonstrate the navigation performance enhancement in terms of adaptivity and robustness at the expense of acceptable additional execution time.

Performance analysis and validation of precision multisatellite RF measurement scheme for microsatellite formations

Almost all existing studies on inter-satellite radio-frequency (RF) measurement have focused on two-satellite formations. Although some frequency division multiple access and code division multiple access multisatellite RF measurement schemes have been proposed, their poor scalability does not satisfy the inter-satellite measurement requirements of multisatellite formations, especially large-scale formations. Two-way ranging (TWR), which is based on a time division mechanism, is an effective solution that has been used for inter-satellite links in the global positioning system and Beidou navigation constellations. However, the high measurement accuracy achieved with TWR in these navigation constellations is heavily reliant on high-performance atomic clocks and the assistance of navigation ephemeris, which are not available on microsatellite platforms. This work focuses on a scalable multisatellite measurement scheme that adopts a distributed broadcast-based time division multiple access mechanism as the media access control layer and uses an asymmetric double-side TWR method as the physical layer. The measurement performance of the proposed scheme is evaluated through in-depth theoretical modeling, simulation verification, and experimental validation, along with a comprehensive comparison with the conventional TWR method. The experimental results show that centimeter-level measurement accuracy can be achieved with the proposed scheme when only a common miniaturized frequency source is used. This accuracy level is two orders of magnitude better than that of the TWR method, and thus satisfies the application requirements of general large-scale microsatellite formations.

Testing of Software for the Planning of a Linear Object GNSS Measurement Campaign under Simulated Conditions

The precision of a linear object measurement using satellite techniques is determined by the number and the relative position of the visible satellites by the receiver. The status of the visible constellation is described by the Dilution Of Precision (DOP). The obtained geometric coefficient values are dependent on many variables. When determining these values, field obstacles at the receiver location and satellite positions changing with time must be taken into account. Carrying out a series of surveys as part of a linear object Global Navigation Satellite System (GNSS) measurement campaign requires the optimisation problem to be solved. The manner of the inspection vehicle’s movement should be determined in such a way that the surveys are taken only within the pre-defined time frames and that the geometric coefficient values obtained at subsequent points of the route are as low as possible. The purpose of this article is to develop a software for the planning of a linear object GNSS measurement campaign to implemented in motion and taking into account the terrain model and its coverage. Additionally, it was determined how much the developed program improves DOP values on the planned route under simulated conditions. This software has no equivalent elsewhere in the world, as the current solutions for the planning of a GNSS measurement campaign, e.g., Trimble GNSS Planning, GNSS Mission Planning, or GPS Navigation Toolbox, allow the satellite constellation geometry to be analysed exclusively for specific coordinates and at a specific time. Analysis of the obtained simulation test results indicates that the campaign implementation in accordance with the pre-determined schedule significantly improves the quality of the recorded GNSS data. This is particularly noticeable when determining the position using the Global Positioning System (GPS) and GLObal NAvigation Satellite System (GLONASS) satellite constellations at the same time. During the tests conducted on the road along a three-kilometre-long route (tram loop) in Gdańsk Brzeźno, the average value of the obtained Position Dilution Of Precision (PDOP) decreased by 22.17% thanks to using the software to plan a linear object GNSS measurement campaign. The largest drop in the geometric coefficient values was noted for an area characterised by a very large number of field obstacles (trees with crowns and high buildings). Under these conditions, the PDOP value decreased by approx. 25%. In areas characterised by a small number of field obstacles (single trees in the vicinity of the track, clusters of trees and buildings located along the track), the changes in the PDOP were slightly smaller and amounted to several percent.

Implementation of Feldspar as a partial replacement material in cement mortar (exploration and application)

This paper aims to explore and evaluate the use of Jordanian Feldspar as a natural resource partial replacement material for cement and sand in cement mortar. First, Al-Jaishia area was explored through a global positioning system (GPS) navigation to gather site samples of Feldspar raw material. Then, cement and sand were partially replaced by Feldspar with substitution ratios of 5%, 10%, 15%, 20%, and 25% for each. The study included the effect of cement replacement on normal consistency and setting time for cement paste. The water content along with initial and final setting times increased with the increment of cement replacement ratio. Moreover, mechanical properties (compressive, flexural, and residual compressive strengths) of cement mortar with cement and sand replacement were evaluated. The compressive and flexural strengths after 3, 7, and 28 days of curing were examined for both cement and sand replacement. While, residual compressive strength for cement replacement after 28 days was measured at elevated temperatures of 400°C, 600°C, and 800°C. The compressive and flexural strengths decreased by increasing the Feldspar replacement ratio for both cement and sand at all specimen ages. Whereas, heat resistance properties were improved by cement/Feldspar replacement. The best result for residual compressive strength was obtained at 15% replacement ratio and 400°C temperature.

Spoofing Attack Detection Method for UAV Navigation System

An implementation of methods for protecting unmanned aerial vehicles (UAVs) from spoofing attacks of the global positioning system (GPS) to ensure safe navigation is discussed in this paper. The Global Navigation Satellite System (GNSS) is widely used to locate UAVs and is by far the most popular navigation solution. This is due to the simplicity and relatively low cost of this technology, as well as the accuracy of the transmitted coordinates. However, there are many security threats to GPS navigation. Primarily this is due to the nature of the GPS signal, the signal is transmitted in the clear, so an attacker can block or tamper with it. This study analyzes the existing GPS protection methods. As part of the study, an experimental stand and scenarios of attacks on the UAV GPS system were developed. Data from the UAV flight logbook was collected and an analysis of cyber-physical parameters was carried out to see an effect of the attack on the on-board sensors readings. Based on this, a new method for detecting UAV anomalies was proposed, based on an analysis of changes in UAV internal parameters. This self-diagnosis method allows the UAV to independently assess the presence of changes in its subsystems and identify signs of a cyberattack. To detect an attack, the UAV collects data on changes in cyber-physical parameters over a certain period of time, then updates this data. As a result it is necessary for the UAV to determine the degree of difference between the two time series of the collected data. The greater the degree of difference between the updated data and the previous ones, the more likely the UAV is under attack.

Robust hierarchical structure from motion for large-scale unstructured image sets

Structure from Motion (SfM) is key to mixed computer vision and photogrammetry applications. However, the fast-growing needs for large-scale SfM bring challenges to current SfM solutions. Unlike traditional global and incremental SfM solutions, hierarchical SfM approaches demonstrate promising potential in effectively reconstructing large-scale image sets by dividing the image set into multiple image clusters, reconstructing each cluster separately, and gradually merging partial models into a complete model. However, current hierarchical SfM approaches still suffer from the following problems: accurate image clustering without ancillary information; automatic quality evaluation of each reconstruction unit and unreliable partial reconstruction removal; effective and efficient reconstruction of each image cluster; robust and accurate cluster merging considering the merging order and the handling of images taken with the same camera but divided into different clusters. These unstable factors limit the robustness and accuracy of hierarchical SfM approaches on different unstructured image sets.To systematically improve the performance of hierarchical SfM, we propose a novel robust hierarchical structure from motion (RHSfM) method for large-scale image sets, which does not rely on any additional information, such as Global Positioning System (GPS) and Inertial Navigation System (INS). (1) We develop an automatic image clustering method based on image correlation and present a dynamic adjustment strategy, obtaining reliable image clustering results. (2) We remove the poor reconstructions by introducing multiple quality evaluation standards. (3) We put forward a fast incremental SfM algorithm that optimizes the image adding mode with an image pre-screening strategy and gets rid of the dependence by the proposed dynamic adjustment strategy. (4) We achieve accurate cluster merging by creating an optimal merging list and employing a stepwise global optimization strategy that merges structures first and then cameras. Significantly, the entire process is fully automated with only a few input parameters, and the final result is not sensitive to these parameters.We verify our method on various real image sets that cover different image conditions, different scenes, and different image scales, especially two large-scale image sets with 121,506 and 153,396 images, respectively. The experimental results reveal that our approach outperforms the state-of-the-art SfM systems Colmap, 3DF Samantha, and Metashape in terms of robustness, accuracy, and efficiency. In particular, only our method successfully reconstructed all the seven challenging datasets. For the five datasets that the other systems can also reconstruct, our method obtains the highest accuracy, which is 25 percent better than the best result of the comparable methods on average; for the remaining two datasets, the accuracy of our method is higher than 0.75 pixels. Moreover, the efficiency of our method is about 18, 4.85, and 0.25 times faster than Colmap, 3DF Samantha, and Metashape averagely on the experimental image sets, respectively. After all, our contribution provides a comprehensive and practical solution for large-scale SfM.