Accurate GPS Research Articles

First Record of the Red-Footed Falcon’s Nocturnal Flight Activity during the Nestling Period Using GPS Data

The red-footed falcon (Falco vespertinus) is a species that is of great interest to conservation. Because of this, understanding the red-footed falcon’s flight behavior is important for the conservation of this species. In this context, by using accurate GPS data-loggers, in 2019 and 2020, we analyzed its flight activity at the two largest colonies in Italy, and we collected 5840 GPS points. At night, all of the surveyed individuals were active during all of the hourly intervals, and they were in flight for about 10% of the time (40% in the daytime). The nocturnal flight activity showed a dual pattern: frequent and long-distance flights before sunrise (22.22% of time in flight; maximum distance from nest > 3 km) and after sundown (32.14% of time in flight; maximum distance from nest > 12 km), and limited and short-distance flights late at night (10 p.m.–5 a.m.; <5% of time in flight; maximum distance from nest < 100 m). Our study suggests that an increase in alfalfa crops and fallow land (in place of maize and soy crops) in the surroundings (i.e., 50–100 m) of the nests would considerably help this species to avoid, or at least to minimize, nocturnal flight activity, with expected improvements in its reproductive success. Our results are a step forward in advancing the knowledge of this important red-footed falcon population, which has been largely unknown so far. We provide here the first evidence ever of the red-footed falcon’s regular nocturnal flight activity during the nestling period (June–July).

Performance of GPS/GPRS tracking devices improves with increased fix interval and is not affected by animal deployment.

The use of GPS tracking technologies has revolutionized the study of animal movement providing unprecedentedly detailed information. The characterization of GPS accuracy and precision under different conditions is essential to correctly identify the spatial and temporal resolution at which studies can be conducted. Here, we examined the influence of fix acquisition interval and device deployment on the performance of a new GPS/GSM solar powered device. Horizontal and vertical accuracy and precision of locations were obtained under different GPS fix acquisition intervals (1min, 20 min and 60 min) in a stationary test. The test devices were deployed on pre-fledgling white storks (Ciconia ciconia) and we quantified accuracy and precision after deployment while controlling for bias caused by variation in habitat, topography, and animal movement. We also assessed the performance of GPS-Error, a metric provided by the device, at identifying inaccurate locations (> 10 m). Average horizontal accuracy varied between 3.4 to 6.5 m, and vertical accuracy varied between 4.9 to 9.7 m, in high (1 min) and low frequency (60 min) GPS fix intervals. These values were similar after the deployment on white storks. Over 84% of GPS horizontal positions and 71% of vertical positions had less than 10m error in accuracy. Removing 3% of data with highest GPS-Error eliminated over 99% of inaccurate positions in high GPS frequency intervals, but this metric was not effective in the low frequency intervals. We confirmed the suitability of these devices for studies requiring horizontal and vertical accuracies of 5-10m. For higher accuracy data, intensive GPS fix intervals should be used, but this requires more sophisticated battery management, or larger batteries and devices.

Simulation research on PPP-RTK performance based on BDS GEO satellite

Precise point positioning (PPP) is one of the seven planning public services of the new generation global Beidou Navigation Satellite System (BDS), i.e. BDS-3. Up to now, the PPP service signal has already been broadcast through I channel of PPP-B2b to support decimeter level positioning within 30 min for users over China and the surrounding areas for free. Concerning the potential application of PPP real-time kinematic (PPP-RTK) in the BDS positioning service development, this paper carried out analysis and experiment of the design and evaluation of PPP-RTK through Q channel based on the existing PPP-B2b I channel signal. First, we presented the algorithm of PPP-RTK based on the undifferenced and uncombined model. Then, the format and broadcast strategy of phase delay and atmospheric delay products were discussed in detail. Finally, based on the simulation data, we analyzed the performance of PPP-RTK with different broadcast bandwidths. The results suggested that the positioning accuracy of GPS + BDS + Galileo PPP-RTK under 95% quantile were 2.3 cm and 3.3 cm in horizontal and vertical, respectively. In order to evaluate the BDS PPP-RTK service, we set the convergence thresholds as 6 cm in horizontal and 12 cm in vertical, which is given by Centimeter Level Augmentation Service of Japanese Quasi-Zenith Satellite System, and the time to converge to such thresholds were 0.5 min and 1.0 min in horizontal and vertical, respectively. Finally, the experiment considering ‘correction latency’ suggested that there was only a litter effect on the convergence speed, the positioning accuracy after convergence is roughly the same.

GNSS Timing Performance Assessment and Results Analysis.

Global Navigation Satellite System (GNSS) timing is a main service function. Each GNSS has its own time performance specification. However, a uniform timing performance assessment methodology and its outcomes do not exist. Firstly, the timing performance specifications of each GNSS are analyzed. Then, time transfer accuracy is considered as the key GNSS timing performance indicator. Secondly, an assessment method for the Coordinated Universal Time (UTC) published by the Bureau International des Poids et Mesures (BIPM) and UTC kept by the National Time Service Center of China (UTC(NTSC)) is proposed. Thirdly, the uncertainty budget of the assessment method is given. The timing performances of BDS, GPS, GLONASS, and Galileo are assessed and compared. The results show that the time transfer accuracy of BDS, GPS, GLONASS, and Galileo was 13.8 ns, 4.5 ns, 16.8 ns, and 4.2 ns, respectively, in 2021, meeting their performance requirements specified by GNSS (30 ns or 40 ns). Meanwhile, the assessment results of GPS and Galileo are much better than requirements, while the assessment results of BDS and GLONASS show fixed time offset and can still be improved further. If the local reference time of GNSS users can be connected with UTC, this assessment method can be used.

Anti-spoofing Kalman filter for GPS/rotational INS integration

The navigation and positioning accuracy of the carrier can be effectively improved through the integrated navigation of GPS and Inertial navigation system (INS). However, signals from GPS satellites are affected by the external environment, which may reduce the positioning accuracy of GPS. More seriously, the GPS receiver may receive spoofing signals, resulting in positioning errors in the integrated navigation. Therefore, an anti-spoofing integrated navigation method is proposed in this paper. The error propagation characteristics of inertial navigation and the prediction estimation value in Kalman filter are used to detect the spoofing. After spoofing detection, credible GPS positioning results are used for Kalman filter as measurements. The method proposed in this paper can effectively improve the accuracy and robustness of integrated navigation. At the same time, it does not need to modify the existing GPS equipment or additional equipment. The effectiveness of the method is verified by simulation and vehicular experiments.

Evaluation of earth rotation parameters from modernized GNSS navigation messages

Modernized navigation messages of global navigation satellite systems like GPS CNAV include earth rotation parameters (ERPs), namely the pole coordinates and UT1-UTC (∆UT1) as well as their rates. Broadcast ERPs are primarily needed for space-borne GNSS applications that require transformations between earth-fixed and inertial reference frames like navigation in earth orbit as well as to the moon. Based on a global tracking network of 23 stations, broadcast ERP values are obtained for the global systems GPS and BeiDou as well as the regional QZSS and IRNSS. Subsequent data sets at daily intervals show polar motion discontinuities of 0.4 to 0.7 mas for GPS, QZSS, and IRNSS, whereas BDS is worse by a factor of about two. Discontinuities in ∆UT1 range from 0.17 to 0.45 ms. External comparison with the C04 series of the International Earth Rotation and Reference Systems Service results in polar motion RMS differences of 0.3 to 1.0 mas and ∆UT1 differences of about 0.13 ms for GPS, QZSS, and IRNSS. Due to less frequent update intervals, BDS performs worse by a factor of 2 – 4. In view of the current GNSS-based positioning errors at geostationary or even lunar distances, the accuracy of GPS, QZSS, and IRNSS broadcast ERPs is sufficient to support autonomous spacecraft navigation without the need for external data.

High-Resolution Canopy Height Model Generation and Validation Using USGS 3DEP LiDAR Data in Indiana, USA

Forest canopy height model (CHM) is useful for analyzing forest stocking and its spatiotemporal variations. However, high-resolution CHM with regional coverage is commonly unavailable due to the high cost of LiDAR data acquisition and computational cost associated with data processing. We present a CHM generation method using U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) LiDAR data for tree height measurement capabilities for entire state of Indiana, USA. The accuracy of height measurement was investigated in relation to LiDAR point density, inventory height, and the timing of data collection. A simple data exploratory analysis (DEA) was conducted to identify problematic input data. Our CHM model has high accuracy compared to field-based height measurement (R2 = 0.85) on plots with relatively accurate GPS locations. Our study provides an easy-to-follow workflow for 3DEP LiDAR based CHM generation in a parallel processing environment for a large geographic area. In addition, the resulting CHM can serve as critical baseline information for monitoring and management decisions, as well as the calculation of other key forest metrics such as biomass and carbon storage.

Curating maternal, neonatal and child health (MNCH) datasets for spatiotemporal data analytics

We provide in this Data Note the details of maternal, neonatal and child health (MNCH) datasets curated directly from patients’ medical records; comprising 538 maternal, 720 neonatal and 425 child records, captured at St Luke’s General Hospital, Anua, Uyo, Nigeria, from 2014 to 2019. Variables included in the datasets are gender, age, class of patient (mother/infant/child), LGA (local government area), diagnosis, symptoms, prescription, blood pressure (mm Hg), temperature (degree centigrade), and weight (Kg). The purpose of this publication is to describe the datasets for researchers who may be interested in its reuse (for analysis, research, quality assurance, policy formulation/decision, patient safety, and more). The curated datasets also involved the capturing of location information (GPS: global positioning system data) from the study area, to aid spatiotemporal and informed demographic analysis. We detail the methods used to curate the datasets and describe the protocol of variables selection and processing. For reasons of data privacy, some patients’ personal information such as names were replaced with patient numbers (a sequence generated using Microsoft Excel). Furthermore, the addresses/locations of the patients, date of visit, latitude, longitude, elevation, and GPS accuracy are restricted. Restricted data can be made available to readers after a formal request to the corresponding author (see data restriction statement). The curated datasets are available at the Open Science Framework.

ОЦЕНКА ЗАПАСОВ ОРГАНИЧЕСКОГО УГЛЕРОДА В ПОЧВЕННОМ ПОКРОВЕ ОСТРОВНЫХ ЭКОСИСТЕМ КУЙБЫШЕВСКОГО ВОДОХРАНИЛИЩА

Assessment of organic carbon stocks in soils and other components of ecosystems are becoming increasingly important as a necessary reference point for a reliable determination of the amount of greenhouse gas removals at country scale. The gradual tightening of carbon balance requirements dictates the urgency of the problem under consideration. The aim of the work was to assess the stocks of organic carbon in the soils of the islands of the Kazan region of the variable backwater of the Kuibyshev reservoir in the 0–20 cm layer, and also to determine which type of soils makes the greatest contribution to the sequestration of carbon. The reserves of organic carbon in the soils of the islands of the Kuibyshev water reservoir were determined in the area from the Zelenodolsk – Nizhnie Vyazovye bridge (55°49’27.1 «N; 48°31’05.6″E) to the islands in front of the Teteyevo village (55°24’11.8 «N; 49°07’59.6» E). Surveys of the islands’ soil cover and selection of the soil samples were carried out in 2018-2019. The calculation of the organic carbon content was carried out for the 0–20 cm layer. The calculations took into account the total carbon content in the organogenic, organic-mineral and mineral horizons. It was found that the highest carbon content in the upper soil layer was observed in the profile of marsh-podzolic soils – 51.7 t / ha. The lowest organic carbon content was noted in sod-alluvial soils (12.0 t / ha) and artificial sandy deposits (3.8 t / ha). Carbon stocks in soil profiles and proportion of carbon in organogenic horizons increased with increasing of hydromorphic properties in the following row: 1) sod-podzolic soil < marsh-podzolic soil; 2) light gray forest soil < gray forest gley soil; 3) sod-alluvial soil < alluvial meadow-marsh soil < marsh-alluvial soil. The total reserves of organic carbon in the islands’ soils were calculated taking into account the areas occupied by individual soil contours. The total stock of organic carbon in the 0–20 cm layer of the studied area of the water reservoir was 49,190.9 tons. About 83 % of the total stock of organic carbon stored in the form of humus of accumulative mineral horizons and only 17 % in the organogenic and organic-mineral horizons. It was shown that alluvial meadow-marsh (23,125.9 t) and sod-podzolic soils (8,957.5 t), occupying the largest areas on the territory of the islands, make the largest contribution to the organic carbon reserves. An interesting point is that on the islands of floodplain origin, a greater contribution to the total humus reserves was made by soils with pronounced hydromorphic properties – alluvial meadow-marsh soils and alluvial meadow soils. On the islands of terrace origin, the bulk of carbon was concentrated in automorphic soils. A possible reason is the features of the islands’ relief of different origins. Reasonable data on the rate of organic carbon accumulation were obtained only for alluvial marsh soils, the organogenic horizon of which was formed after the creation of the reservoir – 390 kg / ha annually. Flooded soils are the most promising reservoirs for organic carbon deposition from greenhouse gases. Thanks to the research carried out using accurate GPS referencing of soil profiles, the islands’ soils are becoming a very valuable object for monitoring the rate of organic carbon accumulation, the volume of absorption of greenhouse gases and the increase in total organic carbon stocks.

Investigation of GPS Positioning Accuracy Near a Deciduous Forest Area

This article evaluates the accuracy and performance of GPS positioning near a forest area. In such cases, positions are calculated from weak signals that tend to be less accurate. Moreover, the results show that there were significant differences depending on season (May vs. October) regarding the accuracy and precision of the measured coordinates; also, accuracies were different depending on the seasonal forest characteristics. Therefore, practical recommendations for each case were established in order to help foresters select the most suitable situation. The results indicated that the season was a significant factor for the GPS surveys.

Research on the method of travel area clustering of urban public transport based on Sage-Husa adaptive filter and improved DBSCAN algorithm.

The travel trajectory data of mobile intelligent terminal users are characterized by clutter, incompleteness, noise, fuzzy randomness. The accuracy of original data is an essential prerequisite for better results of trajectory data mining. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is one of the most effective trajectory data mining methods, but the selection of input parameters often limits it. The Sage-Husa adaptive filtering algorithm effectively controls the error range of mobile phone GPS data, which can meet the positioning accuracy requirements for DBSCAN spatial clustering having the advantages of low cost and convenient use. Then, a novel cluster validity index was proposed based on the internal and external duty cycle to balance the influence of the distance within-cluster, the distance between clusters, and the number of coordinate points in the process of clustering. The index can automatically choose input parameters of density clustering, and the effective clustering can be formed on different data sets. The optimized clustering method can be applied to the in-depth analysis and mining of traveler behavior trajectories. Experiments show that the Sage -Husa adaptive filtering algorithm proposed further improves the positioning accuracy of GPS, which is 17.34% and 15.24% higher eastward and northward, 14.25%, and 18.17% higher in 2D and 3D dimensions, respectively. The number of noise points is significantly reduced. At the same time, compared with the traditional validity index, the evaluation index based on the duty cycle proposed can optimize the input parameters and obtain better clustering results of traveler location information.

Unified model involving genomics, magnetic resonance imaging and prostate-specific antigen density outperforms individual co-variables at predicting biopsy upgrading in patients on active surveillance for low risk prostate cancer.

BackgroundActive surveillance (AS) is the reference standard treatment for the management of low risk prostate cancer (PCa). Accurate assessment of tumor aggressiveness guides recruitment to AS programs to avoid conservative treatment of intermediate and higher risk patients. Nevertheless, underestimating the disease risk may occur in some patients recruited, with biopsy upgrading and the concomitant potential for delayed treatment.AimTo evaluate the accuracy of mpMRI and GPS for the prediction of biopsy upgrading during active surveillance (AS) management of prostate cancer (PCa).MethodA retrospective analysis was performed on 144 patients recruited to AS from October 2013 to December 2020. Median follow was 4.8 (IQR 3.6, 6.3) years. Upgrading was defined as upgrading to biopsy grade group ≥2 on follow up biopsies. Cox proportional hazard regression was used to investigate the effect of PSA density (PSAD), baseline Prostate Imaging‐Reporting and Data System (PI‐RADS) v2.1 score and GPS on upgrading. Time‐to‐event outcome, defined as upgrading, was estimated using the Kaplan–Meier method with log‐rank test.ResultsOverall rate of upgrading was 31.9% (n = 46). PSAD was higher in the patients who were upgraded (0.12 vs. 0.08 ng/ml2, p = .005), while no significant difference was present for median GPS in the overall cohort (overall median GPS 21; 22 upgrading vs. 20 no upgrading, p = .2044). On univariable cox proportional hazard regression analysis, the factors associated with increased risk of biopsy upgrading were PSA (HR = 1.30, CI 1.16–1.47, p = <.0001), PSAD (HR = 1.08, CI 1.05–1.12, p = <.0001) and higher PI‐RADS score (HR = 3.51, CI 1.56–7.91, p = .0024). On multivariable cox proportional hazard regression analysis, only PSAD (HR = 1.10, CI 1.06–1.14, p = <.001) and high PI‐RADS score (HR = 4.11, CI 1.79–9.44, p = .0009) were associated with upgrading. A cox regression model combining these three clinical features (PSAD ≥0.15 ng/ml2 at baseline, PI‐RADS Score and GPS) yielded a concordance index of 0.71 for the prediction of upgrading.ConclusionIn this study PSAD has higher accuracy over baseline PI‐RADS score and GPS score for the prediction of PCa upgrading during AS. However, combined use of PSAD, GPS and PI‐RADS Score yielded the highest predictive ability with a concordance index of 0.71.

Large-Scale Reality Modeling of a University Campus Using Combined UAV and Terrestrial Photogrammetry for Historical Preservation and Practical Use

Unmanned aerial vehicles (UAV) enable detailed historical preservation of large-scale infrastructure and contribute to cultural heritage preservation, improved maintenance, public relations, and development planning. Aerial and terrestrial photo data coupled with high accuracy GPS create hyper-realistic mesh and texture models, high resolution point clouds, orthophotos, and digital elevation models (DEMs) that preserve a snapshot of history. A case study is presented of the development of a hyper-realistic 3D model that spans the complex 1.7 km2 area of the Brigham Young University campus in Provo, Utah, USA and includes over 75 significant structures. The model leverages photos obtained during the historic COVID-19 pandemic during a mandatory and rare campus closure and details a large scale modeling workflow and best practice data acquisition and processing techniques. The model utilizes 80,384 images and high accuracy GPS surveying points to create a 1.65 trillion-pixel textured structure-from-motion (SfM) model with an average ground sampling distance (GSD) near structures of 0.5 cm and maximum of 4 cm. Separate model segments (31) taken from data gathered between April and August 2020 are combined into one cohesive final model with an average absolute error of 3.3 cm and a full model absolute error of &lt;1 cm (relative accuracies from 0.25 cm to 1.03 cm). Optimized and automated UAV techniques complement the data acquisition of the large-scale model, and opportunities are explored to archive as-is building and campus information to enable historical building preservation, facility maintenance, campus planning, public outreach, 3D-printed miniatures, and the possibility of education through virtual reality (VR) and augmented reality (AR) tours.

Modeling and assessment of multi-frequency GPS/BDS-2/BDS-3 kinematic precise point positioning based on vehicle-borne data

BeiDou Navigation Satellite System (BDS) has got the global service capability after the launch of the 55th BDS-3 satellite on June 23, 2020. Currently, BDS is operated based on both the second generation BDS (BDS-2, with 15 satellites transmitting triple frequency signals) and the third generation BDS (BDS-3, with 30 satellites providing services from five frequency signals). To make full use of BDS-2 + BDS-3 signals (B1I, B2I, B3I, B1C, and B2a), this paper introduces an undifferenced and uncombined Precise Point Positioning (PPP) model by using single/dual/triple frequencies BDS-2/BDS-3 data. Results illustrate that the Root Mean Square (RMS) values of BDS-3 PPP based on new signals are better than BDS-2 (B1I + B3I), but worse than BDS-3 (B1I + B3I). Generally, triple-frequency PPP is close to that of dual-frequency PPP, but it is improved significantly in the north, east and vertical components comparing with single-frequency PPP. Compared to the positioning accuracy of GPS + BDS-2 PPP, those of GPS + BDS-3 PPP are improved obviously, especially in the horizontal components. While using BDS-2 and BDS-3 together, the positioning performance of GPS + BDS-2 + BDS-3 is upgraded significantly in both horizontal and vertical directions. Moreover, the convergence time of BDS-3 (especially B1C + B2a) and BDS-2 + BDS-3 PPP are accelerated visibly comparing with that of BDS-2 PPP.

LIDAR Self Driving Car

Abstract: Increasing population is the major issue of transportation nowadays. People who live and work in the major cities of the world are faced with increasing levels of congestion, delays, total travel time, costs, frustration, accidents and loss of life. The objective of this project is to help prevent traffic accidents and save people’s time by fundamentally changing car use. The system would have sensors to detect the obstacles and to be able to react according to their position. In this project we have developed an automated driving system which drives the car automatically. We have developed a technology for cars that drives it automatically using LIDAR. This car is capable of sensing the surroundings, navigating and fulfilling the human transportation capabilities without any human input. It continuously tracks the surrounding and if any obstacle is detected vehicle senses and moves around and avoids the obstacle. An autonomous car navigation system based on Global Positioning System (GPS) is a new and promising technology, which uses real time geographical data received from several GPS satellites to calculate longitude, latitude, speed and course to help navigate a car. As we know the development of gps is more improved now the accuracy of gps we can see centimetre also so Like for our car to go at specific inputted location we use this gps technology.Lidar is used for sensing the surroundings. Like radar, lidar is an active remote sensing technology but instead of using radio or microwaves it uses electromagnetic waves. Keywords: Congestion, Traffic Accident, LIDAR sensor, Global Positioning System, Electromagnetic waves

Rancang Bangun Low-Budget Autonomous Quadcopter

Quadcopter is an unstable flying vehicle. The flight controller regulates the rotational speed of the four motors, so that each propeller produces the lift required for the quadcopter to fly stable. It is interesting to know whether the use of generic quadcopter components obtained in the market can be mutually compatible. A stable and controllable quadcopter is a requirement for a quadcopter to fly autonomously. This research focusses on design a low-budget autonomous quadcopter. The research method consists of three main stages. First, the design and build phase of the quadcopter. The main frame and quadcopter arms are designed with a diagonal distance between the rotors of 45 cm. The basic components of the quadcopter are selected which are mutually compatible and assembled on the frame and arms. The flight controller is connected to the GPS, transmitter, and receiver. The autonomous system also involves a ground control system in the form of a Mission Planner. Second, the flight test stage is setting the PID constant so that the quadcopter can fly stable. PID tuning produces proportional constants of 0.088, integrals of 0.016, and derivatives of 0.008. Third, the autonomous flight test stage. The success of autonomous flying is known by analyzing the difference in input waypoint coordinates through the Mission Planner against the results of low-budget GPS receiver readings on autonomous flying missions. GPS accuracy was analyzed by calculating the 2DRMS and CEP values. The best value of 2DRMS = 1.56 meters and CEP = 0.64 meter occurred at Waypoint #2.

A Cooperative Localization Method based on V2I Communication and Distance Information in Vehicular Networks

Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment. Vehicle positions obtained using V2I communication are more accurate because the known roadside unit (RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends more on the number of RSUs; however, the high installation cost limits the use of this approach. It also depends on nonlinear localization nature. They were neglected in several research papers. In these studies, the accumulated errors increased with time due to the linearity localization problem. In the present study, a cooperative localization method based on V2I communication and distance information in vehicular networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem, but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the proposed method has superior accuracy than existing methods, giving a root mean square error of approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in fault environments.

Simulation and Synchronous Generation of Radar Signals at Geographically Distributed Sensors for Testing Emitter Location Systems

Location Fixing (LF) of Radar Emitters is carried out in an Electronic Warfare scenario by Sensors with Direction-of-Arrival and signal parameter measurement capabilities, geographically distributed over few tens of kilometres. The present paper brings out the Scenario Simulation and Synchronous generation of Radar Signal at Geographically distributed locations for comprehensive testing of the Emitter Location Systems (ELS). This test facility permits exhaustive testing of the ELS against various parameters since the performance of the ELS depends on factors such as Sensors’ geometry with respect to the location of the Emitter of interest, signal parameter measurement accuracies, LF algorithms used, time synchronization accuracy achievable among the Sensors, etc. The Radar signals are synthesized synchronously, locally, at each of the distributed Sensors by replicating the Emitter Signal characteristics as received at the Sensors. The Simulator System uses a High Accuracy GPS Receiver as the Global Clock against which the signals are timed and a Field Programmable Gate Array for generating controls triggered on the absolute time of the Global Clock.

Measurement campaign and mathematical model construction for the ship Zodiak magnetic signature reproduction

The paper presents the partial work done within the framework of the EDA Siramis II project focused on magnetic signature reproduction of ships. Reproduction is understood here as the ability to determine the magnetic anomaly of the local Earth magnetic field in any direction and at any measurement depth due to the presence of the analysed object. The B-91 type hydrographic ship Zodiak was selected as the real case study. The work was divided into two main stages: the development of a measurement campaign taking into account physical measurements, and the development of a mathematical model on the basis of the measured values. The measurement campaign included: preparation of the measuring range, selection of equipment for the measurement of magnetic quantities and geographical location, and data recording while the ship passes the measuring point according to the designated course. As a result of the measurement campaign, magnetic flux density components were collected in different positions in relation to the measuring instruments and the ship's heading. A multi-dipole model was used to build the mathematical model in accordance with the idea of inverse modelling. The effectiveness of this model was previously checked on synthetic data of virtual ships generated using the finite element method. Experiments performed with simulation models were helpful in determining the structure of the model, the nature of the data, and the number of samples needed to properly determine the multi-dipole model parameters. The parameters were determined using the nonlinear least squares method according to the idea of data fitting. The classical Ridge and Lasso regularization methods were applied to prevent the developed multi-dipole model from overfitting. Other regularization methods based on GPS accuracy marks and modification of fitness functions were also considered. The verification was done using real data: the data generated by the model was compared with patterns recorded during the Zodiak measurement campaign. High degree of conformity of the shape of characteristics was obtained. Moreover, the correctness of model execution was confirmed by low values of quantitative indices such as RMSE and MAE representing modelling errors. The methodology presented in the paper is quite universal and can be used to determine the signatures of other ferromagnetic objects.

Research on Roadside Unit-Assisted Cooperative Positioning Method for a Connected Vehicle Environment

With the rapid development of intelligent transportation systems and connected vehicle (CV) technology, vehicle-to-infrastructure communication technologies have provided new solutions to traditional traffic safety and efficiency issues. However, the current intelligent CVs often provide positioning services only through a single GPS. These modules’ positioning accuracy can be insufficient to support the safety and reliability of security applications. The question arises of how to enhance GPS positioning accuracy in a CV environment without adding additional equipment and using only the information that existing CV devices can access. This paper proposes a roadside unit (RSU)-assisted GPS-RSS (received signal strength) cooperative positioning method for a CV environment. The rough position information from GPS is combined with RSS ranging and dead reckoning to obtain preliminary position estimated coordinates of the CV. Bayesian filtering is performed to obtain a more accurate preliminary position estimate. The final position estimated coordinates, obtained after data fusion, are combined with the high-precision map data (MAP) sent by the RSU to match the lane where the vehicle is located. Simulation and field tests verify each other, and the results show that the lane positioning accuracy of GPS can be improved by 21% within the range from the RSU to the CV’s on-board unit.