89 research outputs found

    Development and Validation of an IMU/GPS/Galileo Integration Navigation System for UAV

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    Several and distinct Unmanned Aircraft Vehicle (UAV) applications are emerging, demanding steps to be taken in order to allow those platforms to operate in an un-segregated airspace. The key risk component, hindering the widespread integration of UAV in an un-segregated airspace, is the autonomous component: the need for a high level of autonomy in the UAV that guarantees a safe and secure integration in an un-segregated airspace. At this point, the UAV accurate state estimation plays a fundamental role for autonomous UAV, being one of the main responsibilities of the onboard autopilot. Given the 21st century global economic paradigm, academic projects based on inexpensive UAV platforms but on expensive commercial autopilots start to become a non-economic solution. Consequently, there is a pressing need to overcome this problem through, on one hand, the development of navigation systems using the high availability of low cost, low power consumption, and small size navigation sensors offered in the market, and, on the other hand, using Global Navigation Satellite Systems Software Receivers (GNSS SR). Since the performance that is required for several applications in order to allow UAV to fly in an un-segregated airspace is not yet defined, for most UAV academic applications, the navigation system accuracy required should be at least the same as the one provided by the available commercial autopilots. This research focuses on the investigation of the performance of an integrated navigation system composed by a low performance inertial measurement unit (IMU) and a GNSS SR. A strapdown mechanization algorithm, to transform raw inertial data into navigation solution, was developed, implemented and evaluated. To fuse the data provided by the strapdown algorithm with the one provided by the GNSS SR, an Extended Kalman Filter (EKF) was implemented in loose coupled closed-loop architecture, and then evaluated. Moreover, in order to improve the performance of the IMU raw data, the Allan variance and denoise techniques were considered for both studying the IMU error model and improving inertial sensors raw measurements. In order to carry out the study, a starting question was made and then, based on it, eight questions were derived. These eight secondary questions led to five hypotheses, which have been successfully tested along the thesis. This research provides a deliverable to the Project of Research and Technologies on Unmanned Air Vehicles (PITVANT) Group, consisting of a well-documented UAV Development and Validation of an IMU/GPS/Galileo Integration Navigation System for UAV II navigation algorithm, an implemented and evaluated navigation algorithm in the MatLab environment, and Allan variance and denoising algorithms to improve inertial raw data, enabling its full implementation in the existent Portuguese Air Force Academy (PAFA) UAV. The derivable provided by this thesis is the answer to the main research question, in such a way that it implements a step by step procedure on how the Strapdown IMU (SIMU)/GNSS SR should be developed and implemented in order to replace the commercial autopilot. The developed integrated SIMU/GNSS SR solution evaluated, in post-processing mode, through van-test scenario, using real data signals, at the Galileo Test and Development Environment (GATE) test area in Berchtesgaden, Germany, when confronted with the solution provided by the commercial autopilot, proved to be of better quality. Although no centimetre-level of accuracy was obtained for the position and velocity, the results confirm that the integration strategy outperforms the Piccolo system performance, being this the ultimate goal of this research work

    Contributions to Positioning Methods on Low-Cost Devices

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    Global Navigation Satellite System (GNSS) receivers are common in modern consumer devices that make use of position information, e.g., smartphones and personal navigation assistants. With a GNSS receiver, a position solution with an accuracy in the order of five meters is usually available if the reception conditions are benign, but the performance degrades rapidly in less favorable environments and, on the other hand, a better accuracy would be beneficial in some applications. This thesis studies advanced methods for processing the measurements of low-cost devices that can be used for improving the positioning performance. The focus is on GNSS receivers and microelectromechanical (MEMS) inertial sensors which have become common in mobile devices such as smartphones. First, methods to compensate for the additive bias of a MEMS gyroscope are investigated. Both physical slewing of the sensor and mathematical modeling of the bias instability process are considered. The use of MEMS inertial sensors for pedestrian navigation indoors is studied in the context of map matching using a particle filter. A high-sensitivity GNSS receiver is used to produce coarse initialization information for the filter to decrease the computational burden without the need to exploit local building infrastructure. Finally, a cycle slip detection scheme for stand-alone single-frequency GNSS receivers is proposed. Experimental results show that even a MEMS gyroscope can reach an accuracy suitable for North seeking if the measurement errors are carefully modeled and eliminated. Furthermore, it is seen that even a relatively coarse initialization can be adequate for long-term indoor navigation without an excessive computational burden if a detailed map is available. The cycle slip detection results suggest that even small cycle slips can be detected with mass-market GNSS receivers, but the detection rate needs to be improved

    Localization Precise in Urban Area

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    Nowadays, stand-alone Global Navigation Satellite System (GNSS) positioning accuracy is not sufficient for a growing number of land users. Sub-meter or even centimeter accuracy is becoming more and more crucial in many applications. Especially for navigating rovers in the urban environment, final positioning accuracy can be worse as the dramatically lack and contaminations of GNSS measurements. To achieve a more accurate positioning, the GNSS carrier phase measurements appear mandatory. These measurements have a tracking error more precise by a factor of a hundred than the usual code pseudorange measurements. However, they are also less robust and include a so-called integer ambiguity that prevents them to be used directly for positioning. While carrier phase measurements are widely used in applications located in open environments, this thesis focuses on trying to use them in a much more challenging urban environment. To do so, Real Time-Kinematic (RTK) methodology is used, which is taking advantage on the spatially correlated property of most code and carrier phase measurements errors. Besides, the thesis also tries to take advantage of a dual GNSS constellation, GPS and GLONASS, to strengthen the position solution and the reliable use of carrier phase measurements. Finally, to make up the disadvantages of GNSS in urban areas, a low-cost MEMS is also integrated to the final solution. Regarding the use of carrier phase measurements, a modified version of Partial Integer Ambiguity Resolution (Partial-IAR) is proposed to convert as reliably as possible carrier phase measurements into absolute pseudoranges. Moreover, carrier phase Cycle Slip (CS) being quite frequent in urban areas, thus creating discontinuities of the measured carrier phases, a new detection and repair mechanism of CSs is proposed to continuously benefit from the high precision of carrier phases. Finally, tests based on real data collected around Toulouse are used to test the performance of the whole methodology

    Accurate navigation applied to landing maneuvers on mobile platforms for unmanned aerial vehicles

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    Drones are quickly developing worldwide and in Europe in particular. They represent the future of a high percentage of operations that are currently carried out by manned aviation or satellites. Compared to fixed-wing UAVs, rotary wing UAVs have as advantages the hovering, agile maneuvering and vertical take-off and landing capabilities, so that they are currently the most used aerial robotic platforms. In operations from ships and boats, the final approach and the landing maneuver are the phases of the operation that involves a higher risk and where it is required a higher level of precision in the position and velocity estimation, along with a high level of robustness in the operation. In the framework of the EC-SAFEMOBIL and the REAL projects, this thesis is devoted to the development of a guidance and navigation system that allows completing an autonomous mission from the take-off to the landing phase of a rotary-wing UAV (RUAV). More specifically, this thesis is focused on the development of new strategies and algorithms that provide sufficiently accurate motion estimation during the autonomous landing on mobile platforms without using the GNSS constellations. In one hand, for the phases of the flights where it is not required a centimetric accuracy solution, here it is proposed a new navigation approach that extends the current estimation techniques by using the EGNOS integrity information in the sensor fusion filter. This approach allows improving the accuracy of the estimation solution and the safety of the overall system, and also helps the remote pilot to have a more complete awareness of the operation status while flying the UAV In the other hand, for those flight phases where the accuracy is a critical factor in the safety of the operation, this thesis presents a precise navigation system that allows rotary-wing UAVs to approach and land safely on moving platforms, without using GNSS at any stage of the landing maneuver, and with a centimeter-level accuracy and high level of robustness. This system implements a novel concept where the relative position and velocity between the aerial vehicle and the landing platform can be calculated from a radio-beacon system installed in both the UAV and the landing platform or through the angles of a cable that physically connects the UAV and the landing platform. The use of a cable also incorporates several extra benefits, like increasing the precision in the control of the UAV altitude. It also facilitates to center the UAV right on top of the expected landing position and increases the stability of the UAV just after contacting the landing platform. The proposed guidance and navigation systems have been implemented in an unmanned rotorcraft and a large number of tests have been carried out under different conditions for measuring the accuracy and the robustness of the proposed solution. Results showed that the developed system allows landing with centimeter accuracy by using only local sensors and that the UAV is able to follow a mobile landing platform in multiple trajectories at different velocities

    Using Random Sampling Consensus (RANSAC) to Detect Errors in Global Navigation Satellite Systems (GNSS) Signals and Data

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    A positioning, navigation, and timing (PNT) signal can be used to estimate a user’s position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10^−6 within minutes, while biases with slopes on the order of 10^−7 were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources

    Utilization of IGS Information for Improved Real-time GPS Positioning

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    The estimation of a precise user\u27s position is a difficult and complex problem. In addition, the use of geodetic grade position instruments is often not possible for Small Unmanned Aerial Vehicle (SUAV) systems. However, the availability of the global navigation satellite system (GNSS) and International GNSS Service (IGS) predicted product data allows an attempt to increase the precision of a navigation algorithm, which is the aim in this thesis.;The utilization of this information within an algorithm work environment is a complex problem, requiring the development of multiple tools in order to use and access the IGS raw and product data. Therefore, the overall goal of this research project was the development of these tools using MATLAB RTM. The IGS information provided by these tools allows access to a particular set of product and raw data files. The available predicted product data is used to increase the precision of the position estimate for a real-time application. Within this, the conversion from a long time interval to a fast update rate was determined. The use of this information requires these tools to also include important orbit determinations of the GPS satellites.;The use of only precise satellite position information from the developed MATLAB tools is evaluated by a comparison of a position estimation algorithm using recorded satellite position information and the developed satellite position information from the IGS predicted data. The results show an increase in performance of position estimation with the use of the created MATLAB tools. A discussion in how the use of the created tools could further be expanded to increase the accuracy and precision of a position estimation algorithm is presented

    GNSS-Based Navigation for Lunar Missions

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    Numerous applications, not only Earth-based, but also space-based, have strengthened the interest of the international scientific community in using Global Navigation Satellite Systems (GNSSs) as navigation systems for space missions that require good accuracy and low operating costs. Indeed, already used in Low Earth Orbits (LEOs), GNSS based-navigation GNSS-based navigation systems can maximize the autonomy of a spacecraft while reducing the costs of ground operations, allowing for budget-limited missions of micro- and nanosatellites. This is why GNSS is also very attractive for applications in higher Earth orbits up to the Moon, such as in Moon Transfer Orbits (MTOs). However, while GNSS receivers have already been exploited with success for LEOs, their use in higher Earth orbits above the GNSS constellation is extremely challenging, particularly on the way from the Earth to the Moon, characterized by weaker signals with wider gain variability, larger dynamic ranges resulting in higher Doppler and Doppler rates, critically lower satellite signal availability, and poorer satellite-to-user geometry. In this context, the first research objective and achievement of this PhD research is a feasibility study of GNSS as an autonomous navigation system to reach the Moon, and the determination of the requirements for the design of a code-based GNSS receiver for such a mission. The most efficient combinations of signals transmitted by the GPS, Galileo, and combined GPS-Galileo constellations have been identified by analyzing the theoretical achievable signal acquisition and tracking sensitivities, the resultant constellation availability, the pseudorange error factors, and the geometry error factor and accordingly the achievable navigation performance The results show that GNSS signals can be tracked up to Moon altitude, but not with the current GNSS receiver technology for terrestrial use. The second research objective and achievement is the design and implementation of a GNSS receiver proof-of-concept capable of providing GNSS observations onboard a space vehicle orbiting up to Moon altitude. This research work describes the hardware architecture, the high-sensitivity acquisition and tracking modules and the standalone single-epoch navigation performance of the developed GPS L1 C/A hard-ware receiver, named the WeakHEO receiver. Although they can still be collected, GNSS observations at Moon altitude, if not filtered, but simply used to compute a single-epoch least-squares solution, lead to a very coarse navigation accuracy, on the order of 1 to 10 km, depending on the number and type of signals successfully processed. Therefore, the third and main research objective and achievement is the design and implementation of a GNSS-based orbital filter (OF) determination unit, based on an extended Kalman filter (EKF) and an orbital forces model, able to significantly improve the achievable navigation performance and also to aid acquisition and tracking modules of the GNSS receiver. Simulation results of the OF performance when processing simulated GPS and Galileo observations, but also real GPS L1 C/A observations provided by the WeakHEO receiver (when connected in a hardware in the loop configuration to a full constellation GNSS radio frequency signal simulator), show a positioning accuracy at Moon altitude of a few hundred meters

    Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

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    The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

    Methods of navigation: An introduction to technological navigation

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    Ihminen on historian aikana aina navigoinut. Teknologinen navigointi syntyi merenkulussa, koska avomerellä tarvittiin mittauksia oman sijainnin määrittämiseksi. Lentokoneet, ohjukset ja avaruusalukset sekä kuivalla maalla liikkuvat kulkuneuvot ja jopa jalankulkijat kaikki ”navigoivat” nykyteknologioiden avulla. Kehitys on pääosin kahden teknologian ansiota: satelliittipaikannuksen, kuten GPS:n (Global Positioning System), ja inertianavigoinnin. Myös tieto- ja viestintätekniikka on kehittynyt, erityisesti rekursiivinen lineaarinen suodatus eli Kalmanin suodin. Lisäksi pienet ja hinnaltaan huokeat digitaaliset anturit ovat mullistamassa jokapäiväisen navigoinnin. Tässä kirjassa käsiteltäviä aiheita ovat navigoinnin perusteet, stokastiset prosessit, Kalmanin suodin, inertianavigoinnin teknologiat ja menetelmät, GNSS-signaalien rakenne, kantoaallon vaihemittaukset ja kokonaistuntemattomat, tosiaikainen GNSSpaikannus ja navigointi, differentiaalikorjausten viestintäratkaisut ja standardit, GNSStukiasemat ja -verkot, satelliittipohjaiset parannusjärjestelmät, ilmagravimetria sekä anturifuusio ja sattuman anturit.Historically, humankind has always navigated. Technological navigation originated in seafaring, because on the open ocean, measurements are needed in order to determine one’s own location as a part of navigation. Aircraft, rockets and spacecraft as well as vehicles moving on dry land, and even pedestrians, all ”navigate” by means of modern technologies. This development is mainly due to two technologies: satellite positioning, such as GPS (the Global Positioning System) and inertial navigation. Also information and communication technologiy has evolved: especially recursive linear filtering or the Kalman filter. Furthermore, small and inexpensive digital sensors are revolutionising everyday navigation. Subjects explained in this book are the fundamentals of navigation, stochastic processes, the Kalman filter, inertial navigation technology and methods, GNSS signal structure, carrier-phase measurement and ambiguities, real-time GNSS positioning and navigation, communication solutions and standards for differential corrections, GNSS base stations and networks, satellite-based augmentation systems, airborne gravimetry, sensor fusion and sensors of opportunity
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