编队飞行GPS/INS相对导航的分布滤波算法

在对编队飞行GPS/INS相对导航当前的主要滤波算法进行总结和分析的基础上,提出了分布滤波的算法,并建立了GPS/INS相对导航仿真系统,对该算法进行验证。仿真结果表明该算法能够适应大型、紧密编队飞行的需求,在减小计算量、降低通讯数据量、允许编队做大的机动飞行的同时,能得到较高的估计精度。

Tecniche GPS/INS per l'anilisi dinamica di un ciclomotore

Nel seguente elaborato si espone l’utilizzo del sistema GPS/INS per la valutazione del moto di un ciclomotore. Tale sistema è composto da sensori GPS ( Global Navigation System ) per la misurazione della posizione, e da sensori INS ( Inertial Navigation System) per la misurazione dell’accelerazione e delle velocità angolari rispetto a tre assi coordinati. Chiaramente le misure di accelerazioni e di velocità angolari da parte dei sensori, presentano dei minimi errori, che però si ripercuotono sul posizionamento finale. Per limitare questo fenomeno e rendere la misura di velocità e posizione utilizzabile, un filtro di Kalman viene impiegato per correggere il risultato dell'integrazione usando le misurazioni del GPS. Il connubio tra il sistema INS e il sistema GPS è molto efficacie anche quando si ha una assenza di ricezione satellitare o perdita parziale dei satelliti (cycle slip). Infine è stato utilizzato uno smartphone sfruttando i sensori in esso presenti : accelerometri, giroscopi, GPS, per analizzare la dinamica di un ciclomotore, concentrandosi sull’assetto in particolar modo l’angolo di rollio. Tale prova è stata affrontata non tanto per validare il sistema GPS/INS, ma per provare una soluzione comoda e di basso costo per analizzare il moto di un ciclomotore.

Study of robust H(infinity) filtering application in loosely coupled INS/GPS system

Since a celebrate linear minimum mean square (MMS) Kalman filter in integration GPS/INS system cannot guarantee the robustness performance, a H(infinity) filtering with respect to polytopic uncertainty is designed. The purpose of this paper is to give an illustration of this application and a contrast with traditional Kalman filter. A game theory H(infinity) filter is first reviewed; next we utilize linear matrix inequalities (LMI) approach to design the robust H(infinity) filter. For the special INS/GPS model, unstable model case is considered. We give an explanation for Kalman filter divergence under uncertain dynamic system and simultaneously investigate the relationship between H(infinity) filter and Kalman filter. A loosely coupled INS/GPS simulation system is given here to verify this application. Result shows that the robust H(infinity) filter has a better performance when system suffers uncertainty; also it is more robust compared to the conventional Kalman filter.

便携式移动机器人INS/GPS组合导航系统研究

基于捷联惯导系统（INS）与全球定位系统（GPS）定位技术的发展以及机器人导航的需要，本文对INS与GPS的组合导航系统进行了研究。捷联惯导系统与GPS导航各有优缺点，具有互补性，文中将两者结合形成了更加准确可靠的定位系统。本文首先介绍了捷联惯导系统和全球定位系统，并对捷联惯导和GPS的误差作了详细的分析，建立了误差模型。文中应用动力学误差方程建立了九状态INS/GPS综合卡尔曼滤波方程。提出了一种以位置、速度、姿态DCM的误差为状态量，以GPS和INS的位置差作为观测量的INS/GPS组合导航系统的滤波算法，并将该技术应用于机器人的定位导航。仿真实验表明，该算法可有效提高系统导航参数的估计精度。本文分五章对该课题进行了研究。第一章是引言，介绍了课题的研究背景、意义，国内外的研究现状和本文的主要工作；第二章介绍了惯性传感器和GPS接收器的原理和特性；第三章介绍了捷联惯导系统相关的理论知识，包括姿态角的解算，算法具体内容和误差分析，并对捷联惯导系统进行了仿真试验；第四章介绍了Kalman滤波的相关知识并详细介绍了INS/GPS组合导航系统；第五章对INS/GPS组合导航系统的九状态卡尔曼滤波算法进行了仿真，并对试验结果进行了详细的分析。从仿真结果可知，组合导航系统大大的提高了系统的精度，克服了纯惯导系统的缺点。

Attitude observability of a loosely-coupled GPS/Visual Odometry Integrated Navigation Filter

We present a novel method for integrating GPS position estimates with position and attitude estimates derived from visual odometry using a scheme similar to a classic loosely-coupled GPS/INS integration. Under such an arrangement, we derive the error dynamics of the system and develop a Kalman Filter for estimating the errors in position and attitude. Using a control-based approach to observability, we show that the errors in both position and attitude (including yaw) are fully observable when there is a component of acceleration perpendicular to the velocity vector in the navigation frame. Numerical simulations are performed to confirm the observability analysis.

Error analysis and attitude observability of a monocular GPS/visual odometry integrated navigation filter

In this paper, we present a method for the recovery of position and absolute attitude (including pitch, roll and yaw) using a novel fusion of monocular Visual Odometry and GPS measurements in a similar manner to a classic loosely-coupled GPS/INS error state navigation filter. The proposed filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. An observability analysis of the proposed filter is performed, showing that the scale factor, position and attitude errors are fully observable under acceleration that is non-parallel to velocity vector in the navigation frame. The observability properties of the proposed filter are demonstrated using numerical simulations. We conclude the article with an implementation of the proposed filter using real flight data collected from a Cessna 172 equipped with a downwards-looking camera and GPS, showing the feasibility of the algorithm in real-world conditions.

Integrated vision-based attitude estimation

For many years, computer vision has lured researchers with promises of a low-cost, passive, lightweight and information-rich sensor suitable for navigation purposes. The prime difficulty in vision-based navigation is that the navigation solution will continually drift with time unless external information is available, whether it be cues from the appearance of the scene, a map of features (whether built online or known a priori), or from an externally-referenced sensor. It is not merely position that is of interest in the navigation problem. Attitude (i.e. the angular orientation of a body with respect to a reference frame) is integral to a visionbased navigation solution and is often of interest in its own right (e.g. flight control). This thesis examines vision-based attitude estimation in an aerospace environment, and two methods are proposed for constraining drift in the attitude solution; one through a novel integration of optical flow and the detection of the sky horizon, and the other through a loosely-coupled integration of Visual Odometry and GPS position measurements. In the first method, roll angle, pitch angle and the three aircraft body rates are recovered though a novel method of tracking the horizon over time and integrating the horizonderived attitude information with optical flow. An image processing front-end is used to select several candidate lines in a image that may or may not correspond to the true horizon, and the optical flow is calculated for each candidate line. Using an Extended Kalman Filter (EKF), the previously estimated aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and location of the horizon in the image. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To evaluate the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42° and 0.71° respectively when compared with a truth attitude source. The Cessna 172 flight resulted in pitch and roll error standard deviations of 1.79° and 1.75° respectively. In the second method for estimating attitude, a novel integrated GPS/Visual Odometry (GPS/VO) navigation filter is proposed, using a structure similar to a classic looselycoupled GPS/INS error-state navigation filter. Under such an arrangement, the error dynamics of the system are derived and a Kalman Filter is developed for estimating the errors in position and attitude. Through similar analysis to the GPS/INS problem, it is shown that the proposed filter is capable of recovering the complete attitude (i.e. pitch, roll and yaw) of the platform when subjected to acceleration not parallel to velocity for both the monocular and stereo variants of the filter. Furthermore, it is shown that under general straight line motion (e.g. constant velocity), only the component of attitude in the direction of motion is unobservable. Numerical simulations are performed to demonstrate the observability properties of the GPS/VO filter in both the monocular and stereo camera configurations. Furthermore, the proposed filter is tested on imagery collected using a Cessna 172 to demonstrate the observability properties on real-world data. The proposed GPS/VO filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. Since no platformspecific dynamics are required, the proposed filter is not limited to the aerospace domain and has the potential to be deployed in other platforms such as ground robots or mobile phones.

Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Aircraft dynamic navigation for unmanned aerial vehicles

This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

Geração automática de estereomodelos a partir de imagens digitais georreferenciadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geomatica in ambito forense

La geomatica è la disciplina che si occupa di acquisire, modellizzare, interpretare, elaborare, archiviare e divulgare informazioni georeferenziate, ovvero informazioni caratterizzate da una posizione in un prescelto sistema di riferimento. La geomatica ha i suoi fondamenti metodologici nelle discipline che si sono occupate di risolvere i problemi di posizionamento sulla superficie terrestre e nelle sue immediate vicinanze (geodesia, astronomia, matematica, statistica). Alla geomatica afferiscono pertanto le tecniche di posizionamento terrestri (storicamente ricomprese nella topografia) e spaziali (GPS), la fotogrammetria digitale, le tecniche di scansione laser da terra e da velivolo, il telerilevamento da aereo e da satellite, la cartografia numerica, la geostatica. Applicare la geomatica in ambito forense significa descrivere le metodologie e le tecniche che vengono utilizzate in presenza di indagini giudiziarie, quali ricostruzioni di scene del crimine o ricostruzioni di incidenti stradali a partire proprio da rilievi geomatici. Le argomentazioni della tesi si suddividono in tre parti. La prima in cui descrivo le principali tecniche di misura e strumenti utilizzati dalla geomatica in ambito forense; la seconda e la terza parte descrivono in particolare le metodologie e le tecniche che un perito forense può applicare in presenza di due contesti abbastanza frequenti: la ricostruzione di scene del crimine e la ricostruzione di incidenti stradali.

Medium-Coupled Bus-Based INS-GPS Sensor Fusion for Accurate and Reliable Positioning

A scheme for integration of stand-alone INS and GPS sensors is presented, with data interchange over an external bus. This ensures modularity and sensor interchangeability. Use of a medium-coupled scheme reduces data flow and computation, facilitating use in surface vehicles. Results show that the hybrid navigation system is capable of delivering high positioning accuracy.

Sistemi navigazionali multi sensore per il posizionamento in presenza di brevi periodi di GPS outage

Il posizionamento terrestre negli ultimi anni è stato sempre più facilitato dallo sviluppo delle tecniche satellitari, che permettono di localizzare un punto sulla superficie terrestre con precisioni superiori a quelle richieste per la pura navigazione, tramite la comunicazione tra ricevitore e satelliti. Per la disponibilità del sistema satellitare è indispensabile l’intervisibilità ottica satellite - ricevitore, condizione che viene a mancare nel caso ad esempio di trekking sottobosco, a causa della copertura data da manto vegetale e chiome arboree che non permettono una corretta triangolazione geometrica satellitare. Rientrano nei sistemi navigazionali anche le piattaforme inerziali, sistemi che rilevano le accelerazioni impresse e l’orientamento della piattaforma stessa. Se montati su un veicolo possono fungere da ausilio alla determinazione dell’ “attitude”, cioè dell’atteggiamento del veicolo durante il suo movimento in uno spazio tridimensionale. In questo lavoro ci si propone di unire i benefici delle due tecnologie, satellitari e inerziali, grazie alla complementarietà delle loro caratteristiche sugli errori, unendone le potenzialità e verificando i benefici prodotti dal loro uso integrato. In particolare si utilizzeranno dispositivi di costo relativamente contenuto.