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Applying the principle of integrated navigation systems to estimating the motion of large vehicles
Abstract
Combining inertial sensors and GPS has led to integrated navigation systems of a performance surpassing classical navigation requirements. A utilisation of this technology suggests itself which considers not only the classical movement of a small, rigid body but expands the application range also to large aircraft, space stations and suchlike. The signals generated on this basis are usable both for vehicle guidance and for structural control. The key element of such a generalisation is the kinematical model describing the vehicle motion: Until now, the mentioned restriction to rigid bodies is regular and considers only inertial sensors referring to a single vehicle point. A more general navigation system design considers, however, a specific model comprising additional degrees of freedom from structural distortions as well as spatially distributed sensors. This model is employed within an extended Kalman filter estimating the vehicle motion state of high resolution regarding time. In addition, the filter uses the signals of gyros, accelerometers, satellite navigation receivers, and structural sensors. For this purpose, the paper discusses firstly different variants of integrated navigation systems followed by a presentation of the advantage of spatially distributing satellite navigation antennas over the vehicle structure. Finally, the integrated system for a simple flexible aircraft structure is introduced.
... In this case, it is preferable to model the mounting angles as random walks or first order Gauss-Markov process. Furthermore, higher order colored noise may be considered when taking into account the structural deformation for the large scale land vehicles [28]. In practice, for the railway track trolley case, the mounting angles can also be modeled as random walks with intentionally added small noise. ...
... • A trajectory in a fully open sky environment is suggested to ensure that the carrier phase differential GNSS is available. • Dual-antennas or multi-antenna arrays can be used if possible to improve observability and accuracy of the GNSS/INS heading [28], especially for the low-cost MEMS systems. ...
Nonholonomic constraint (NHC) and odometer speed have been proven to significantly improve the navigation accuracy of a global navigation satellite system (GNSS)-aided inertial navigation system (INS) for land vehicular applications. Exploiting the full potential of the NHC and odometer aids requires the inertial measurement unit (IMU) mounting angles, i.e., angular misalignment with respect to the host vehicle, to be precisely known. We address the accurate estimation of the IMU mounting angles through an aided dead reckoning (DR) approach. In this method, DR using the GNSS/INS integrated attitude and distance traveled is fused with the GNSS/INS integrated position through a straightforward Kalman filter. Simulation and field tests are carried out to validate the proposed algorithm for different grade IMUs, including typical navigation-grade, tactical-grade and low-cost IMUs. The results demonstrate that the pitch and heading mounting angles can be estimated with a comparable accuracy with the GNSS/INS attitude solution, for example, 0.001° accuracy can be achieved for a navigation-grade GNSS/INS integrated system. The roll mounting angle can not be estimated due to lack of observability in this approach, and the heading mounting angle estimation may be influenced by the GNSS/INS heading accuracy drift to some extent for the low-cost IMUs.
... One of the emerging applications of ACs is in the development of an inertial measuring unit (IMU) to compute the linear and angular motion of a rigid body using gyroscopes. The IMUs have a multitude of uses including (i) navigation [1][2][3], (ii) biomechanics [4][5][6][7][8][9] and (iii) robotics and automation [10][11][12]; the cited references represent a few of the numerous works available in the literature. In general, high precision gyroscopes, prior to the recently available MEMS sensors, had many drawbacks, including high cost, high power consumption, large volume and large weight, etc. ...
... Position matrix R is obtained by applying equation (12) at each AC of the cluster. Once S, N and R are obtained, matrix M * can be calculated by using equation (2), and the GF-IMU is fully calibrated. ...
This paper presents a novel calibration algorithm to be used with a gyro-free inertial measurement unit (GF-IMU) based on the use of linear accelerometers (AC). The analytical approach can be implemented in two calibration procedures. The first procedure (P-I) is articulated in the conduction of a static trial, to compute the sensitivity and the direction of the sensing axis of each AC, followed by a dynamic trial, to determine the AC locations. By contrast, the latter procedure (P-II) consists in the calculation of the previously indicated calibration parameters by means of a dynamic trial only. The feasibility of the two calibration procedures has been investigated by testing two GF-IMUs, equipped with ten and six bi-axial linear ACs, with an ad hoc instrumented double-pendulum apparatus. P-I and P-II were compared to a calibration procedure used as a reference (P-REF), which incorporates the AC positions measured with an optoelectronic system. The experimental results we present in this paper demonstrate that (i) P-I is able to determine the calibration parameters of the AC array with a higher accuracy than P-II; (ii) consequently, the errors associated with translational (a0 − g) and rotational () acceleration components for the two GF-IMUs are significantly greater using P-II than P-I and (iii) the errors in (a0 − g) and obtained with P-I are comparable with the ones obtainable by using P-REF. Thus, the proposed novel algorithm used in P-I, in conjunction with the double-pendulum apparatus, can be globally considered a viable tool in GF-IMU calibration.
... Due to the good complementary characteristics, the integration of the inertial navigation system (INS) and the global navigation satellite system (GNSS) can achieve superior performance to either of them operating alone [1,2], and is widely applied on unmanned aerial vehicles (UAVs). The GNSS/INS integration can obtain the optimal estimates of the navigation parameters by using a Kalman filter with correct state and observation models. ...
For the integration of global navigation satellite system (GNSS) and inertial navigation system (INS), real-time and accurate fault detection is essential to enhance the reliability and precision of the system. Among the existing methods, the residual chi-square detection is still widely used due to its good real-time performance and sensibility of fault detection. However, further investigation on the performance of fault detection for different observational conditions and fault models is still required. In this paper, the principle of chi-square detection based on the predicted residual and least-squares residual is analyzed and the equivalence between them is deduced. Then, choosing the chi-square detection based on the predicted residual as the research object, the influence of satellite configuration and fault duration time on the performance of fault detection is analyzed in theory. The influence of satellite configuration is analyzed from the number and geometry of visible satellites. Several numerical simulations are conducted to verify the theoretical analysis. The results show that, for a single-epoch fault, the location of faulty measurement and the geometry have little effect on the performance of fault detection, while the number of visible satellites has greater influence on the fault detection performance than the geometry. For a continuous fault, the fault detection performance will decrease with the increase of fault duration time when the value of the fault is near the minimal detectable bias (MDB), and faults occurring on different satellite’s measurement will result in different detection results.
... In the transfer alignment of airborne distributed position and orientation systems (DPOS), Gong et al. [9] utilized an unscented Kalman filter (UKF) to estimate the flexural angles and flexural lever arm variations. Moreover, to deal with structural flexibilities between M-SINS and S-SINS when conducting transfer alignment, an extended Kalman filter (EKF) is often used in large vehicles [12] and flexible aircrafts [13] to estimate the motion states. With the purpose of realizing rapid and accurate transfer alignment for an airborne weapon's SINS, a mixed H2/H∞ filtering algorithm was designed to deal with the observation noise, which contains both Gaussian white noise and energy limited noise [3]. ...
Transfer alignment on a moving base under a complex dynamic environment is one of the toughest challenges in a strapdown inertial navigation system (SINS). With the aim of improving rapidity and accuracy, velocity plus attitude matching is applied in the transfer alignment model. Meanwhile, the error compensation model is established to calibrate and compensate the errors of inertial sensors online. To suppress the filtering divergence during the process of transfer alignment, this paper proposes an improved adaptive compensation H∞ filtering method. The cause of filtering divergence has been analyzed carefully and the corresponding adjustment and optimization have been made in the proposed adaptive compensation H∞ filter. In order to balance accuracy and robustness of the transfer alignment system, the robustness factor of the adaptive compensation H∞ filter can be dynamically adjusted according to the complex external environment. The aerial transfer alignment experiments illustrate that the adaptive compensation H∞ filter can effectively improve the transfer alignment accuracy and the pure inertial navigation accuracy under a complex dynamic environment, which verifies the advantage of the proposed method.
... Hence, the idea of integrated navigation was further expanded for large aerospace structures, by means of additional Degrees Of Freedom (DOF) and the sensor redundancy to increase the stability of the navigation algorithm in phases of low structural dynamics as well as to facilitate structural control. Wagner and Kasties [76] introduced a more general navigation system design, which presents the advantage of spatially distributing satellite navigation receivers over the vehicle structure and considers a specific model comprising of additional DOF from structural distortions. ...
Complex lightweight structures tend to be significantly flexible and lightly damped,
where structural vibrations are often the source of performance degradation. Vibration
based real-time tasks like active damping or health monitoring of such
structures typically rely on an estimation of the disturbance response of the structure,
using only few number of sensor signals available. An appropriate method for
realizing this estimate is through measuring structural motions using distributed
sensors deployed in the structure of interest.
Combining different type of sensors to take advantage of the positive characteristics
of each instrument is often called sensor fusion and is the basis of an integrated
navigation system. A classical integrated navigation system can be established in
general as a state observer design and usually determines the spatial rigid body
motion of the structure or vehicle considered. However, extending such integrated
systems to flexible structures using distributed structural sensors is possible, which
was already attempted effectively for one dimensional continua, i.e., a flexible
beam. The theory needs to be extended to three-dimensional lightweight structures
to estimate the modal states of vibration. All such systems can be generalized
as integrated motion measurement systems.
In the scope of this thesis, an observer based on integrated motion measurement
method will be developed and simulated for the Stratospheric Observatory for
Infrared Astronomy (SOFIA). The performance of the large airborne telescope
structure of SOFIA is affected by vibrations induced mainly by aeroacoustic disturbances.
Distributed inertial sensors are used to obtain such motion signals with a
good time resolution, which are aided by strain gauges as long term reliable signals.
The sensor fusion approach to be developed here consists of a continuous-discrete
extended Kalman filter. Besides the sensor signals to be fused, the filter requires a
suitable kinematical model, which in turn determines the mechanical meaning of
ix
x
the measurements. The kinematic model will be reduced using a modal approach,
i.e., the kinematical model of SOFIA includes only vibration modes having high
contribution to the image jitter at the focal plane of the telescope.
There are no mass and stiffness properties needed directly in this approach. However,
the approximate knowledge of the modal properties of the structure is necessary
for the implementation of this method. A finite element model is chosen as
a basis to extract such modal properties.
This work also addresses several variations of distributed sensor systems depending
on the type of inertial sensors (accelerometers, gyros) and also the number of
target modes. Simulation results demonstrate the potential of the approach and
its feasibility in complex lightweight structures.
... It leads to integrated motion measurement systems being particularly designed for the individual multibody kinematics considered. An equivalent theory exists also for flexible vehicles (Wagner & Kasties 2004). It is outlined in the remaining part of the paper including an illustration for long antenna lever arms. ...
Comparing the previous ‘International Symposia on Precision Approach and Automatic Landing’, a considerable change of the significance of integrated landing systems is noticeable: At the first conference in 1995 the combination of inertial sensors and GNSS receivers was thoroughly discussed and seemed to be a very promising concept, especially with respect to ‘Integrity’ and ‘Continuity’. However, since then it received little attention. Similarly, the ‘Boeing/Industry GPS Landing System Flight Test Experiments’ in 1995, which involved GPS landing systems of several well-known companies, mirror this development: Despite encouraging results, none of those systems which included inertial sensors became marketable.
A comprehensive discussion about the technical background of this setback for integrated landing systems did interestingly not take place (although it became evident during the last years that pure satellite based systems are not ideal as ‘sole-means’ for demanding tasks of navigation). Mainly the popular opinion exists that the Kalman filter algorithm being the system integration kernel does not perform sufficiently stable. However, this appears only to be so. In reality, it is merely a consequence of the true reason, which was meanwhile identified: The aiding of an inertial navigation system by only one GNSS antenna is not enough in phases of low aircraft dynamics just like during the final approach. Instead, a multi antenna system is required, which should be widely distributed over the aircraft structure. This last approach, though, causes problems due to structural flexibilities.
To show that nonetheless an integrated system based on inertial sensors and widely distributed GNSS antennas is technically feasible, the paper discusses the following topics according to the statements above.
a) Unstable system performance during the final approach for 1-antenna-aiding.
b) Improving the system performance prior to using additional antennas.
c) Effect of the antenna distribution.
d) Integrated systems for distributed sensors and flexible aircraft structures.
The paper includes results from simulated and from real flight test data. In addition, it shows that integrated systems are still an attractive candidate for automatic landing equipment preserving the advantages with respect to ‘Integrity’ and ‘Continuity’.
... With better knowledge about current position and orientation of unmanned aerial vehicle it is possible to perform more complicated, more precise and faster maneuvers (Chen and Xu, 2010). Therefore, the improvement of the quality of measurement systems is at almost all times desirable (Wagner and Kasties, 2004). Application of higher grade measurement devices can be far too expensive (Shojaei and Mohammad Shahri, 2011), while using the dose computation power does not increase the costs of the whole system (Haid and Breitenbach, 2004). ...
This paper presents Kalman filter design which has been programmed and evaluated in dedicated STM32 platform. The main aim of the work performed was to achieve proper estimation of attitude and position signals which could be further used in unmanned aerial vehicle autopilots. Inertial measurement unit and GPS receiver have been used as measurement devices in order to achieve needed raw sensor data. Results of Kalman filter estimation were recorded for signals measurements and compared with raw data. Position actualization frequency was increased from 1 Hz which is characteristic to GPS receivers, to values close to 50 Hz. Furthermore it is shown how Kalman filter deals with GPS accuracy decreases and magnetometer measurement noise.
... Many approaches have been taken to the development of an accurate dynamic model for flexible manipulators [1][2][3][4][5]. Most of the researchers, however, assume small deflection and use a linear strain-displacement relationship [6,7]. When high speed, light weight, accuracy and large payload robots are considered, nonlinear elastic deflection in structures may have to be considered. ...
... Integration can also exploit advantages of the two systems, such as the uniform high accuracy trajectory information of GPS and the short term stability of INS. There are two kinds of approaches to integrate GPS and INS: loosely coupled and tightly coupled3456789. The tightly coupled approach has better performance than the loosely coupled one because the raw GPS measurements are used to form the measurement equation and hence avoid the problems of the loss of information and cross correlations among the position estimates existing in the loosely coupled approach. However, the GPS pseudorange equations are nonlinear, thus linearization techniques such as Extended Kalman Filter (EKF) are commonly used. ...
GPS/INS integration system has been widely applied for navigation due to their complementary characteristics. And the tightly coupled inte-gration approach has the advantage over the loosely coupled approach by using the raw GPS measurements, but hence introduces the nonlinearity into the measurement equation of the Kalman filter. So the typical method for navigation using measurements of range or pseudorange is by linearizing the measurements in an extended Kalman filter (EKF). However, the modeling errors of the EKF will cause the bias and divergence problems especially under the situation that the low quality inertial devices are included. To solve this problem, a quadratic EKF approach by adding the second-order derivative information to retain some nonlinearities is proposed in this paper. Simulation results indicate that the nonlinear terms included in the filtering process have the great influence on the performance of integration, especially in the case that the low quality INS is used in the integrated system. Furthermore, a two-stage cascaded estimation method is used, which circumvents the difficulty of solving nonlinear equations and greatly decreases the computational complexity of the proposed approach, so the quadratic EKF approach proposed in this paper is of great value in practice. © 2006 Published by Elsevier Masson SAS.
... It leads to integrated motion measurement systems being particularly designed for specific individual multibody kinematics. An equivalent theory exists also for flexible vehicles (Wagner and Kasties 2004). It is outlined in the remaining part of the paper including an illustration for long antenna lever arms. ...
During the last years, the International Symposia on Precision Approach and Automatic Landing (ISPA) have shown a considerable change in the significance of integrated landing systems. At the first ISPA conference in 1995, the combination of inertial sensors and GNSS receivers was thoroughly discussed and appeared to be a very promising concept, especially with respect to ‘Integrity’ and ‘Continuity’. Ever since, this particular combination of sensors has received little attention. A comprehensive discussion of the technical background of this setback for integrated landing systems did not take place, primarily because of the popular opinion that the Kalman filter algorithm, which is the system integration kernel, is not sufficiently stable. The true reason has meanwhile been identified. The aiding of an inertial navigation system by only one GNSS antenna is insufficient in phases of low aircraft dynamics such as in the case of final approach. Instead, a multi-antenna system is required with antennas widely distributed over the aircraft structure. This latter approach, however, causes problems due to structural flexibilities. To show that an integrated system based on inertial sensors and widely distributed GNSS antennas is technically feasible, the paper discusses the following topics. (1) Unstable system performance during final approach for 1-antenna-aiding. (2) Improving the system performance prior to using additional antennas. (3) Effect of the antenna distribution. (4) Integrated systems for distributed sensors and flexible aircraft structures. The paper shows that integrated systems are still an attractive candidate for automatic landing equipment preserving the advantages with respect to ‘Integrity’ and ‘Continuity’.
... The algebraic equations contain the geometric formulation of the range between the GPS receiver antenna and GPS satellites. The design of f and h is nontrivial, but it allows a replication of the specific body kinematics even if a nonrigid structure is on hand (Wagner and Kasties 2004). ...
The satellite navigation system GPS has gradually gained a usability that was never expected during ist design 30 years ago. Similar statements can also be made for other central elements of modern navigation technology like gyroscopes and accelerometers as well as microprocessors for synchronizing and processing sensor signals. GPS receivers and other navigation sensors are in principle devices that detect single motion components. To obtain a more complete and plainer description of the Motion considered, a suitable tight combination of several sensors of different kind should be employed. This leads to integrated
navigation or motion measurement which can simultaneously provide a good long-term accuracy and a high resolution with respect to time. In ship, aireraft, and spacecraft navigation the use of such integrated systems is well established. The technological progress as mentioned above suggests now also the utilization for sports science: Indeed, interesting approaches do already exist (at least partially) and show a promising potential for biomechanical analyses, for documentation of training units, and for competition diagnosis. Together with theoretical basics for integrated motion measurement. the paper gives a Survey of some realized systems.
To address the difficulty of high uncertainty priori information in nonlinear filtering that occurs in tightly coupled navigation and positioning systems, a novel adaptive fuzzy neural network-aided progressive Gaussian filter is proposed in this paper to further improve the robustness and accuracy of the filter. A joint estimation of the step size and measurement noise covariance matrix is performed by a variational Bayesian approach. The estimation accuracy of the progressive Gaussian approximation filter is thereby enhanced. In particular, the measurement noise covariance matrix is adjusted using an adaptive fuzzy algorithm, and the state estimation error covariance matrix is optimized exploiting a neural network model. The proposed filter is experimentally verified to have higher accuracy than the existing state-of-the-art filters.
In this paper, we focus on addressing the nonlinear filtering problem with large prior uncertainty but high measurement accuracy, which may be encountered in the application of tightly coupled GNSS/INS integration. Although the existing methods such as progressive Gaussian approximate filter (PGAF) can address this problem, it has poor estimation accuracy. To improve the estimation accuracy of PGAF, the step sizes as well as the measurement noise covariance matrix (MNCM) are jointly estimated based on the variational Bayesian approach, from which a novel PGAF with variable step size is developed. Tightly coupled GNSS/INS integration simulations illustrate that the proposed filter outperforms the existing methods both in estimation accuracy and rate of convergence.
In this paper, an INS compensation algorithm is proposed using the accelerometer from IMU. First, we denote the basic INS algorithm and show that how to compensate the position error when low cost IMU is used. Second, considering the ship's characteristic and ocean environments, we consider with a drift as a periodic external environment change which is affected with exact position. To develop the compensation algorithm, we use a repetitive method to reduce the external environment changes. Lastly, we verify the proposed algorithm through the experiments, where the acceleration sensor is used to acquire real data.
An integrated navigation algorithm-"GPS-improved correlation matching" is proposed. Based on the combination of GPS sensor and image information, it can greatly increase matching speed and guide the micro aerial vehicle to the right destination quickly. A layered matching control strategy from coarse to precise is used to improve matching efficiency without the loss of matching accuracy. Simulation results show that the algorithm keeps higher matching probability and improves matching speed, thus meeting the real-time requirement of the system while working on the 4-DSP system.
The alignment of missile-borne Platform initial navigation, requires higher alignment accuracy and shorter alignment time. The accuracy of traditional alignment technique is low and the alignment time of it is long, because the influence of the east gyro drift and the slow speed of the azimuth misalignment angle's convergence. In order to meet the missile-borne inertial navigation requirements of alignment accuracy and rapidity, this paper proposes the alignment technique of missile-borne platform inertial navigation under arbitrary azimuth misalignment angle. Using platform translocation and three times traditional level alignment to find the north (complete azimuth alignment), this technique eliminates the influence of east gyro drift which leads to a serious decline in the accuracy of the alignment, and shorten the alignment time. The simulation results show that the technique can guarantee the accuracy and the speed of the alignment system.
In this paper we will look at the effectiveness of a non-invasive means of measuring key dynamic characteristics of a tug and tow system for complete voyages. Thereafter, we will use this information to drive a numerical simulation of the towline. A prototype, compact, and rugged test sensor suite was installed on both a tug and barge for an inshore waters tow on the West Coast UK. This data was post-processed and fed into a lumped mass numerical model of the system. Initially only GPS position data is used and the effects and importance of processing higher resolution surge, heave, and sway data will be checked. Conclusions are drawn which will be used to guide further research in this area. Copyright © 2011 by the International Society of Offshore and Polar Engineers (ISOPE).
In this work several unconventional navigation systems are presented that include redundancy of traditional navigation sensors. Main focus is on sensor architectures, while sensor fusion algorithms will be treated as a secondary aspect. Specifically, an analysis of systems with multiple IMUs, Gyro-free INS and GPS derived attitude has been performed. Several reasons justify the application of architectures with redundant navigation sensors; the most relevant obviously concerns the capability to detect and identify some faults. Anyway, sensor redundancy also allows increasing the accuracy of some measurements (as for example in multiple IMU's systems) or avoiding the use of some sensors, which may have disadvantages in terms of costs or accuracy, without renounce to their measurements (as for example in Gyro-free INS). In fact these systems are based on the application of pseudomeasurements. Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
The tightly coupled INS/GPS integration introduces nonlinearity to the measurement equation of the Kalman filter due to the use of raw GPS pseudorange measurements. The extended Kalman filter (EKF) is a typical method to address the nonlinearity by linearizing the pseudorange measurements. However, the linearization may cause large modeling error or even degraded navigation solution. To solve this problem, this paper constructs a nonlinear measurement equation by including the second-order term in the Taylor series of the pseudorange measurements. Nevertheless, when using the unscented Kalman filter (UKF) to the INS/GPS integration for navigation estimation, it causes a great amount of redundant computation in the prediction process due to the linear feature of system state equation, especially for the case with system state vector in much higher dimension than measurement vector. To overcome this drawback in computational burden, this paper further develops a derivative UKF based on the constructed nonlinear measurement equation. The derivative UKF adopts the concise form of the original Kalman filter (KF) to the prediction process and employs the unscented transformation technique to the update process. Theoretical analysis and simulation results demonstrate that the derivative UKF can achieve higher accuracy with a much smaller computational cost in comparison with the traditional UKF.
The Stratospheric Observatory for Infrared Astronomy SOFIA consists of a B747-SP aircraft, which carries aloft a 2.7-meter reflecting telescope. The image stability goal for SOFIA is 0.2 arc-seconds rms. The performance of the telescope structure is affected by elastic vibrations induced by aeroacoustic and suspension disturbances. Active compensation of such disturbances requires a fast way of estimating the structural motion. Integrated navigation systems are examples of such estimation systems. However they employ a rigid body assumption. A possible extension of these systems to an elastic structure is shown by different authors for one dimensional beam structures taking into account the eigenmodes of the structural system. The rigid body motion as well as the flexible modes of the telescope assembly, however, are coupled among the three axes. Extending a special mathematical approach to three dimensional structures, the aspect of a modal observer based on integrated motion measurement is simulated for SOFIA. It is in general a fusion of different measurement methods by using their benefits and blinding out their disadvantages. There are no mass and stiffness properties needed directly in this approach. However, the knowledge of modal properties of the structure is necessary for the implementation of this method. A finite-element model is chosen as a basis to extract the modal properties of the structure. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Micro aerial vehicle (MAV) describes a category of aircraft with dimensions roughly comparable to small birds. As the smallest, powered aircraft, MAVs can carry various sensors as payload to support such civil and military missions as traffic monitoring, weather observation, and enemy surveillance during military conflicts. In order to carry out more sophisticated missions and to improve the flight performance of the aircraft, a reliable navigation solution, especially of the attitude, is of significant importance. For this, an inertial measurement unit (IMU) based on micro-electromechanical systems (MEMS) were tightly- coupled (usage of GPS raw data) with GPS. Subject of this paper is the influence of the distance between IMU and GPS antenna, the position of the GPS antenna relative to the IMU and the number of GPS antennas used on the navigation accuracy (position, velocity, attitude). The results presented are based on Monte Carlo simulations. They are not limited to small unmanned aerial vehicles (UAV).
This paper presents an algorithm for estimating the rigid and elastic motions of aircrafts showing significant elastic displacements, based on an EKF (Extended Kalman Filter) technique. The proposed algorithm can be applied to HALE (High Attitude Long Endurance Vehicle) unmanned vehicles, which typically show a configuration with high aspect ratios wings, fuselages with high length to diameter ratios and, above all, lightweight structures. The knowledge of their actual structure shape is fundamental essentially for three reasons: health monitoring of the structure, control purposes (Active Control Technologies) and finally for the determination of onboard sensors exact position and attitude, relative to a specified reference frame, to improve the accuracy of their measurements. Filter equations have been developed considering the coupling between rigid and elastic motions. The elastic motions are modeled in the assumptions of modal decomposition. Sensors budget of the presented algorithm, consists in two GPS Antennas/Receivers for speed/position measurements, an Inertial Measurement Unit with tri-axial accelerometers, gyros and magnetometers, and at least one auxiliary tri-axial accelerometer. The matrix formulation of the algorithm allows using the desired number of auxiliary accelerometers without changes to its implementation or its mathematical structure. Filter implementation also allows defining a numerical criterion to determine the better allocation of auxiliary accelerometers. The observability of the filter error state vector is also exhaustively analyzed, considering different scenarios concerning the elastic features of the structure. Finally simulation test results are reported, which demonstrate effectiveness of the proposed algorithm.
In this paper, The Kalman filter (KF) has been implemented as the primary integration scheme of the global positioning system (GPS) and inertial navigation systems (INS) for many land vehicle navigation and positioning applications. However, it has been reported that KF-based techniques have certain limitations, which reflect on the position error accumulation during GPS signal outages. Therefore, this article exploits the idea of incorporating artificial intelligence to develop an alternative INS/Differential-GPS (DGPS) integration scheme, the intelligent navigator, for next generation land vehicle navigation and positioning applications.
This paper investigates observability properties of strapdown inertial navigation system (INS) aided by the Global Positioning System (GPS). Observability analysis is made on a linear error dynamics model of navigation equations in the Earth-centered Earth-fixed (ECEF) frame for both loosely-coupled and tightly-coupled integrations. Position and velocity measurements are given from multiple GPS antennas mounted on the vehicle. The motivation to consider multiple GPS antennas is that the lever-arms of them play an important role in observing vehicle attitude and biases of inertial motion unit (IMU) during navigation. Biases of IMU are assumed to be constant. Necessary and sufficient conditions for the instantaneous observability on the GPS/INS integrations are given. A numerical simulation is given to show the effectiveness of multiple GPS antennas in estimating vehicle attitude and biases of IMU when IMU has considerable magnitude of biases.
The combination of inertial sensors and satellite navigation receivers has led to versatile low-cost integrated navigation systems. They are generally based on the assumption of a rigid vehicle, and on the assumption that all motion sensors are close together. The potential of modern microprocessors and the availability of inexpensive sensors suggest giving up this limitation. Accordingly, the range of application of integrated navigation systems enlarges considerably. However, such a step requires the generalization of the theoretical basis of the corresponding system design. The thesis deals with this subject.
Initially, the principle of integrated navigation systems is introduced by means of simple examples. In addition, the essential attribute is presented that serves as feature to tell apart different classes of application. It consists of two kinematical models adapted to the motion cases considered. Using real flight test data, a comparison between classical and newer approaches for the data fusion of inertial sensors and satellite navigation receivers follows. Purpose of this assessment is the selection of the basis for the intended generalization.
The generalization procedure is performed in two steps: At first the assumption of a rigid body remains, the sensors however are now partly distributed over the whole vehicle structure. The extension of the kinematical models, which have not to be restricted to vehicles but can also consider for example robots, forms the following second step. It is based on the description of vehicle structures with rigid and elastic areas. By means of simulation, the functioning of such generalized integrated systems is demonstrated.
--- Die Kombination von Inertialsensorik und Satellitennavigationsempfängern hat zu flexiblen und kostengünstigen integrierten Navigationssystemen geführt. Hierbei wird generell von der Vorstellung eines starren Fahrzeugs ausgegangen, dessen Bewegungssensoren zudem räumlich eng benachbart sind. Moderne, leistungsfähige Methoden der Datenverarbeitung und die Verfügbarkeit kostengünstiger Messgeber legen nahe, diese Einschränkung fallen zu lassen und damit den Anwendungsbereich integrierter Navigationssysteme erheblich zu erweitern. Dazu ist allerdings eine Verallgemeinerung der theoretischen Grundlage zur Auslegung derartiger Systeme erforderlich, womit sich die vorliegende Abhandlung befasst.
Zunächst wird an einfachen Beispielen das Grundprinzip integrierter Navigationssysteme vorgestellt und auf das wesentliche Unterscheidungsmerkmal verschiedener Anwendungsklassen hingewiesen, das in zwei jeweils verwendeten, angepassten kinematischen Modellen besteht. Anschließend folgt mit Hilfe von Flugversuchsdaten eine Bestandsaufnahme zu klassischen und neueren Varianten der Kopplung von Inertial- und Satellitennavigation, um diejenige auszuwählen, die sich für die beabsichtigte Generalisierung am besten eignet.
Die Verallgemeinerung wird in zwei Stufen durchgeführt: Zunächst bleibt die Annahme des starren Fahrzeugs noch bestehen, ein Teil der Sensoren wird jedoch so weit über die Struktur verteilt, wie es die Abmessungen zulassen. Die Erweiterung der kinematischen Modelle, das sich nicht nur auf Fahrzeuge beschränken müssen, sondern auch zum Beispiel Roboter berücksichtigen können, stellt dann den zweiten Schritt dar. Als Ausgangspunkt hierzu dient die Beschreibung von Strukturen mit starren und mit elastischen Teilbereichen. Mit Hilfe von Simulationsrechnungen wird die Funktionsfähigkeit derartiger integrierter Systeme gezeigt.
Kalman filtering theoretically makes possible a relative exact common evaluation of measurement data which occur simultaneously using different navigation procedures. A coupling of inertial navigation and Doppler speed-measuring is described. An attempt is made to explain error divergence, which is often mentioned in literature using this application, by lack of complete observability of the chosen models.
Die Kaimanfiliertechnik ermöglicht theoretisch eine relativ genaue gemeinsame Auswertung von Meßdaten, die nach verschiedenen Navigationsverfahren gleichzeitig anfallen. Beschrieben wird eine Kopplung von Trägheitsnavigation und Doppler-Geschwindigkeitsmessung. Es wird versucht, die in der Literatur häufig dafür erwähnten Divergenzen in den Fehlern durch fehlende vollständige Beobachtbarkeit der gewählten Modelle zu erklären.
This paper presents an integrated flight and aeroelastic control law for a flexible transport aircraft. An integrated model for flight mechanics and aeroelastics, including coupling between rigid body and structural dynamics is used to describe the aircraft motion. Integrated stability augmentation and aeroelastic inner loop control laws for both longitudinal and lateral motion are designed using H^ - control synthesis. The outer loop control law is based on point-mass dynamics and provides a general manual and automatic control interface. With the control law, flight manoeuvres do not excite elastic reactions. Damping of low-frequency aeroelastic modes is considerably increased and sensitivity to gusts is reduced.
Today integrated navigation systems based on a low-cost inertial measurement unit (IMU) and a single antenna GPS receiver are a powerful navigation means. However, during certain phases of operation, such a configuration shows significant performance degradations and stability problems. This behavior results from an incomplete observability of the system state describing the vehicle motion and additional inertial sensor errors. The rigorous observability analysis of Hong et al. (2000) led to the mathematical conditions for such critical circumstances: These situations appear if the vehicle dynamics is too low; additionally, one insight was that a vanishing distance between IMU and GPS antenna should be avoided at all. Considering besides numerical aspects leads to two consequences: - The probability of entering the state of too low dynamics decreases if the antenna lever-arm increases. - A 3-antenna-array, which theoretically ensures a full observability, requires distinct antenna distances. Thus, the intention of the paper is to illustrate the effect of extending the distances between IMU and GPS antenna(s) on the system performance. This is done using simulated measurements to avoid, in a first step, disturbances caused by different satellite signal errors and by vehicle distortions. Yet, the employed Kalman filter was previously tested and its parameters were tuned by means of real flight test data. In addition, the filter is based on a total state formulation and uses an earth fixed Cartesian navigation frame, as this approach shows a better estimation quality compared with the classical error state description (Wagner and Wieneke, 2001). It turns out that increasing the lever-arm of one single antenna effects slightly better estimates for the inertial sensor errors. Employing instead a 3-antenna-array with usually short lever-arms and GPS range measurements of classical DGPS accuracy generates similar results. Combining both measures, however, leads to clear improvements of the attitude accuracy and filter stability. Assuming additionally the precision of carrier phase measurements amplifies those enhancements. A generalization of the GDOP that includes also the antenna configuration makes this plausible. Therefore, using GPS antenna arrays with long leverarms can greatly improve the accuracy and stability of GPS/INS integrated systems. On the other hand, as such an approach imposes questions on structural flexibility, the paper concludes with outlining a concept of integrated systems for nonrigid vehicles.
The backbone of aiding inertial navigation systems by satellite navigation receivers is the data fusion of the subsystem outputs. Its conventional mechanization emerged from the classical, necessary aiding of inertial navigation systems and is based on linearized error models. Recent approaches therefore use directly the nonlinear kinematical equations of the rigid body motion. These methods lead to a simpler system structure as well as to smaller estimation error variances. To verify this statement, the paper presents a systematization of the different fusion schemes and a comparison between results of postprocessed flight test data.
During the last years integrated navigation systems based on gyros,accelerometers, and satellite navigation receivers became powerful,favourably priced devices for the guidance of aircraft and ships.Comparable equipment using especially wheel sensors exists for cars. Thekernel of such systems is a Kalman filter estimating the relevantvehicle motion. The filter design in turn requires a kinematical modelto settle on the motion components considered and to describe themechanical meaning of the measurements employed. Up to now, usual modelsrepresent a single rigid body with two, three or six degrees of freedom.
The assumption of a solitary rigid body reflects mainly classicalnavigation requirements, it is not a consequence of the basic concept ofintegrated navigation systems. In principle, determining the motion ofmechanical systems with other or with additional degrees of freedom ispossible if appropriate kinematical models and suitable sensorarrangements are available.
Based on the theory of integrated navigation systems, the paperdescribes the fundamentals of the design of integrated motionmeasurement systems for multibody structures. The approach isfurthermore illustrated by the example of a double pendulum with amovable inertial support and equipped with microelectromechanical gyrosand accelerometers as well as with radar units. The attachment of thesensors demonstrates that a measurement system layout does typically notrequire considerable modifications of already existing mechanicalassemblies. The performance of the integrated system for the pendulum isdemonstrated by means of simulated and of experimental sensor signals.
The Boeing/Industry GPS landing system flight test experiment
- T Murphy
- D Miller
- D Heine
- C Howell
- A Both
- M Wright
- C Pierce
- J Semler
T. Murphy, D. Miller, D. Heine, C. Howell, A. Both, M. Wright, C.
Pierce, J. Semler, The Boeing/Industry GPS landing system flight test
experiment, in: Proc. of the ION 1996 National Technical Meeting,
Santa Monica, 1996, pp. 155-166.
Nutzung des A340-Flugsimulators für Flugeigenschafts-analysen, in: Entwicklungstrends bei
- W Kindel
W. Kindel, Nutzung des A340-Flugsimulators für Flugeigenschafts-analysen, in: Entwicklungstrends bei Basissystemen, DGLR-Bericht 97-01, DGLR, Bonn, 1997.
- W Kindel
W. Kindel, Nutzung des A340-Flugsimulators für Flugeigenschaftsanalysen, in: Entwicklungstrends bei Basissystemen, DGLR-Bericht
97-01, DGLR, Bonn, 1997.
The Boeing/Industry GPS landing system flight test experiment
- Murphy
Präzise Rollführung von Megalinern auf vorhandenen Rollwegen
- Zimmermann