Showing papers on "Inertial navigation system published in 2001"

Kalman Filtering: Theory and Practice Using MATLAB

Abstract: The definitive textbook and professional reference on Kalman Filtering fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

Inertial sensor technology trends

Abstract: This paper presents an overview of how inertial sensor technology is applied in current applications and how it is expected to be applied in nearand far-term applications. The ongoing trends in inertial sensor technology development are discussed, namely interferometric fiber-optic gyros, micro-mechanical gyros and accelerometers, and micro-optical sensors. Micromechanical sensors and improved fiber-optic gyros are expected to replace many of the current systems using ring laser gyroscopes or mechanical sensors. The successful introduction of the new technologies is primarily driven by cost and cost projections for systems using these new technologies are presented. Externally aiding the inertial navigation system (INS) with the global positioning system (GPS) has opened up the ability to navigate a wide variety of new large-volume applications, such as guided artillery shells. These new applications are driving the need for extremely low-cost, batch-producible sensors.

The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications

Abstract: This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the alignment of the IMU as well as the forward velocity of the vehicle. It is shown that this can be achieved without any external sensing provided that certain observability conditions are met. A theoretical analysis is provided together with a comparison of experimental results between a nonlinear implementation of the algorithm and an IMU/GPS navigation system. This comparison demonstrates the effectiveness of the algorithm. The real time implementation is also addressed through a multiple observation inertial aiding algorithm based on the information filter. The results show that the use of these constraints and vehicle speed guarantees the observability of the velocity and the attitude of the inertial unit, and hence bounds the errors associated with these states. The strategies proposed provides a tighter navigation loop which can sustain outages of GPS for a greater amount of time as compared to when the inertial unit is used with standard integration algorithms.

Accurate mobile robot dead-reckoning with a precision-calibrated fiber-optic gyroscope

Abstract: This paper describes two methods aimed at improving dead-reckoning accuracy with fiber-optic gyroscopes (FOGs) in mobile robots. The first method is a precision calibration procedure for FOGs, which effectively reduces the ill effects of nonlinearity of the scale-factor and temperature dependency. The second method is the implementation of an indirect feedback Kalman filter that fuses the sensor data from the FOG with the odometry system of the mobile robot. The paper also provides experimental results and compares the relative effectiveness of the two methods as implemented on a four-wheel drive/skidsteer Pioneer AT mobile robot.

An outdoor navigation system using GPS and inertial platform

Abstract: The use of the Global Positioning System (GPS) in outdoor localization is a quite common solution in large environments where no other references are available and positioning requirements are not so pressing. Of course, fine motion without the use of an expensive differential device is not an easy task even now that available precision has been greatly improved as the military encoding has been removed. We present a localization algorithm based on Kalman filtering that tries to fuse information coming from an inexpensive single GPS with inertial and, sometimes uncertain, map based data. The algorithm is able to produce an estimated configuration for the robot that can be successfully fed back in a navigation system, leading to a motion whose precision is only related to current information quality. Some experiments show difficulties and possible solutions to this sensor fusion problem.

A nonlinear observer for GPS and INS integration

Abstract: GPS and Inertial Navigation Systems (INS) have complementary properties, and they are therefore well suited for integration. The integrated solution offers better long term accuracy than a stand-alone INS, and better integrity, availability and continuity than a stand-alone GPS receiver, making it suitable for demanding applications. The integration filter is nonlinear both in state and measurements, and the extended Kalman-filter has been used with good results, but it has not been proven globally stable, and it is also computationally intensive, especially within a direct integration architecture. In this work a nonlinear observer suitable for direct integration, due to no covariance update equations, is presented. Global exponential stability of the origin of the combined attitude and velocity error systems is proven.

System and method for creating, storing, and utilizing composite images of a geographic location

Abstract: A system and method synthesizing images of a locale to generate a composite image that provide a panoramic view of the locale. A video camera moves along a street recording images of objects along the street. A GPS receiver and inertial navigation system provide the position of the camera as the images are being recorded. The images are indexed with the position data provided by the GPS receiver and inertial navigation system. The composite image is created on a column-by-column basis by determining which of the acquired images contains the desired pixel column, extracting the pixels associated with the column, and stacking the columns side by side. The composite images are stored in an image database and associated with a street name and number range of the street being depicted in the image. The image database covers a substantial amount of a geographic area allowing a user to visually navigate the area from a user terminal.

Command, control, and navigation experimental results with the NPS ARIES AUV

Abstract: Provides an overview of the Naval Postgraduate School ARIES autonomous underwater vehicle and its control and navigation. An attempt is made to highlight its current operational capabilities and provide a description of future enhancements for greater mission utility and flexibility. An overview of the vehicle design along with descriptions of all major hardware components and sensors is given. A major discussion of the implementation of a modular, multirate, multiprocess software architecture for the ARIES is provided. The architecture is designed to operate using either a single computer processor or two independent, cooperating processors linked through a network interface for improved load balancing. A dual computer implementation is presented since each processor assumes different tasks for mission operation. Also included is a section on the underwater navigation method using a real-time extended Kalman filter that fuses all sensor data and computes the real time position, orientation and velocity. Experimental results for navigational accuracy using a DGPS/IMU/Doppler-aided navigation system are presented with DGPS pop-up maneuvers. Navigational accuracy is a requirement for the use of ARIES as a mobile communications network node. This work provides some examples of missions possible with such a node and the current state of its command and control system.

Integrating INS sensors with GPS velocity measurements for continuous estimation of vehicle sideslip and tire cornering stiffness

Abstract: This paper details a unique method for measuring key vehicle states-body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. A method for integrating inertial navigation system (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire cornering stiffnesses. The experimental results for the GPS velocity-based sideslip angle measurement and cornering stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.

Digital image georeferencing from a multiple camera system by GPS/INS

Abstract: In this paper, the development and testing of an airborne fully digital multi-sensor system for digital mapping data acquisition is presented. The system acquires two streams of data, namely, navigation (georeferencing) data and imaging data. The navigation data are obtained by integrating an accurate strapdown inertial navigation system with a differential GPS system (DGPS). The imaging data are acquired by two low-cost digital cameras, configured in such a way so as to reduce their geometric limitations. The two cameras capture strips of overlapping nadir and oblique images. The GPS/INS-derived trajectory contains the full translational and rotational motion of the carrier aircraft. Thus, image exterior orientation information is extracted from the trajectory, during post-processing. This approach eliminates the need for ground control (GCP) when computing 3D positions of objects that appear in the field of view of the system imaging component. Two approaches for calibrating the system are presented, namely, terrestrial calibration and in-flight calibration. Test flights were conducted over the campus of The University of Calgary. Testing the system showed that best ground point positioning accuracy at 1:12,000 average image scale is 0.2 m (RMS) in easting and northing and 0.3 m (RMS) in height. Preliminary results indicate that major applications of such a system in the future are in the field of digital mapping, at scales of 1:5000 and smaller, and in the generation of digital elevation models for engineering applications.

Enhancement of the inertial navigation system for the Morpheus autonomous underwater vehicles

Abstract: This paper presents the design and development of an enhanced inertial navigation system that is to be integrated into the Morpheus autonomous underwater vehicle at Florida Atlantic University. The inertial measurement unit is based on the off-the-shelf Honeywell HG1700-AG25 3-axis ring-laser gyros and three-axis accelerometers and is aided with ground speed measurements obtained using an RDI Doppler-velocity-log sonar. An extended Kalman filter has been developed, which fuses together asynchronously the inertial and Doppler data, as well as the differential Global Positioning System positional fixes whenever they are available. A complementary filter was implemented to provide a much smoother and stable attitude estimate. Thus far, preliminary study has been made on characterizing the inertial navigation system-based navigation system performance, and the corresponding results and analyzes are provided.

Filtering mechanization method of integrating global positioning system receiver with inertial measurement unit

Abstract: A filtering mechanization method is provided for integrating a Global positioning System receiver with an Inertial Measurement Unit to produce highly accurate and highly reliable mixed GPS/IMU position, velocity, and attitude information of a carrier. The GPS filtered position and velocity data are first individually used as measurements of the two local filters to produce estimates of two sets of the local state vector. Then, the estimates of the two sets of local state vectors are mixed by a master filter device to produce global optimal estimates of master state vector including INS (Inertial Navigation System) navigation parameter errors, inertial sensor errors, and GPS correlated position and velocity errors. The estimates of the two sets of local state vector and master state vector are analyzed by a GPS failure detection/isolation logic module to prevent the mixed GPS/IMU position, velocity, and attitude information from becoming contaminated by undetected GPS failures.

Design of gyroscope-free navigation systems

Abstract: We examine the feasibility of designing a gyroscope-free inertial navigation system (INS) that uses only accelerometers to compute the linear and angular motions of a rigid body. The accelerometer output equation is derived to relate the linear and angular motions of a rigid body relative to a fixed inertial frame. A sufficient condition is given to determine if a configuration of accelerometers is feasible. If the condition is satisfied, the angular and linear motions can be computed separately using two decoupled equations of an input-output (I/O) dynamical system; a state equation for angular velocity and an output equation for linear acceleration. This simple computation scheme is derived from the corresponding dynamical system equations for a special cube configuration for which the angular acceleration is expressed as a linear combination of the accelerometer outputs.

Self-contained mapping and positioning system utilizing point cloud data

Abstract: A self-contained mapping and positioning system for underground mining is provided that is capable of mapping the topography of a region, such as a mine tunnel, and further being able to use the mapped data to determine the position of an object, such as a mining vehicle, within the mine tunnel. The system includes an inertial navigation system (12), a central processing unit (14), a three-dimensional database (16), a three-dimensional camera system (18), an operator console (20) and a survey system having a three-dimensional laser scanner. The survey system using the three-dimensional laser scanner produces point cloud data, i.e., a set of data points representing the topography of the region. The point cloud data is stored within a storage device until the entire region is mapped and then transmitted to the operator console to be post processed. After post processing, the data is exported to the three-dimensional database (16) and then indexed for ease of use by the central processing unit. To determine the position of the object within the region, the system of the instant invention initializes the object in its current position. The object is then either remotely or directly guided to another position from the current position where it is brought to an estimated position by the inertial navigation system (12) or is remotely controlled for performing work, e.g., drilling a mine heading. After a predetermined time of moving the object, there is an error in the position of the object and the operator console makes a call to the central processing unit (14) on board the object to automatically calculate the true position based on the point cloud data stored within the database to update the position of the object. This is done by approximating a search range for the database (16) according to the estimated position. A subset of data corresponding to the search range is removed from the database (16). The three-dimensional camera system then scans images of the surface in proximity to the object and converts the images to a patch of point cloud data. The patch of point cloud data is then matched against the subset of data corresponding to the search range of point cloud data removed from the three-dimensional database (16) until there is less than a predetermined minimum error distance. At that point, the true position of the object is known. This new position is then put back into the inertial navigation system (12) and the positional data of the object is updated with the correct positional data.

Low-Cost INS/GPS Integration: Concepts and Testing

Abstract: The high cost of inertial units is the main obstacle for their inclusion in precision navigation systems to support a variety of application areas. Standard inertial navigation systems (INS) use precise gyro and accelerometer sensors; however, newer inertial devices with compact, lower precision sensors have become available in recent years. This group of instruments, called motion sensors, is six to eight times less costly than a standard INS. Given their weak stand-alone accuracy and poor run-to-run stability, such devices are not usable as sole navigation systems. Even the integration of a motion sensor into a navigation system as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of using a motion sensor, specifically the MotionPak, integrated with DGPS and DGLONASS information, to provide accurate position and attitude information, and to assess its capability to bridge satellite outages for up to 20 seconds. The motion sensor has three orthogonally mounted solid-state' micromachined quartz angular rate sensors, and three high performance linear servo accelerometers mounted in a compact, rugged package. Advanced algorithms are used to integrate the GPS and motion sensor data. These include INS error damping, calculated platform corrections using DGPS (or DGPS/DGLONASS) output, velocity correction, attitude correction and error model estimation for prediction. This multi-loop algorithm structure is very robust, which guarantees a high level of software reliability. Vehicular and aircraft test trials were conducted with the system and the results are discussed. Simulated outages in GPS availability were made to assess the bridging accuracy of the system. Results show that a bridging accuracy of up to 3 m after 10 seconds in vehicular mode and a corresponding accuracy of 6 m after 20 seconds in aircraft mode can be obtained, depending on vehicle dynamics and the specific MotionPak unit used. The attitude accuracy was on the order of 22 to 25 arcmin for roll and pitch, and about 44 arcmin for heading.

DGPS/INS integrated positioning for control of automated vehicle

Abstract: In recent years, the Global Positioning System (GPS) has solidified its presence as a dependable means of navigation by providing absolute positioning in various applications. While GPS alone can provide position information, it has several weaknesses, such as low data output rate and vulnerability to external disturbances. We explore the feasibility of an integrated positioning system using a differential GPS (DGPS) and an inertial navigation system (INS) for the control of an automated vehicle. An extended Kalman filter which combines the measurements from the DGPS, INS, and vehicle sensors to produce estimates of various vehicle states is derived. A methodology which, using map data, converts position measurements to vehicle lateral offset and desired speed, as applicable for the control of an automated vehicle, is presented. An analysis of the overall closed-loop vehicle control system is discussed. Finally, the performance of the proposed control scheme is examined through field tests conducted on two different vehicle platforms, an automated golfcart and a drive-by-wire Honda Accord sedan.

Low complexity anti-jam space-time processing for GPS

Abstract: This paper investigates the performance of reduced rank spacetime processors in the context of anti-jam mitigation for an M-code based GPS receiver utilizing a circular array. Several adaptive processing algorithms are discussed utilizing power minimization techniques. It is assumed an INS (inertial navigation system) or direction finding algorithm is incorporated into the receiver for satellite look direction based algorithms. Reduced rank space-time processing is accomplished via the innovative multistage Wiener filter (MSWF). It is demonstrated that the MSWF does not require matrix inversion, thereby reducing computational complexity. The processing algorithms are compared in terms of available degrees of freedom and distortion of the GPS cross correlation function (CCF).

Fully-coupled positioning system

Abstract: A positioning system is disclosed for measuring a position of a vehicle on land, air, and space, using measurements from a global positioning system receiver and an inertial measurement unit. In the present invention, an integrated Kalman filter processes the all-available measurements of the global positioning system: pseudorange, delta range, carrier phase, and the solution of an inertial navigation system. The integrated Kalman filter is a multi-mode, robust kalman filter, in which optimal integrated mode is selected based on the measurement availability and filter stability. The high accurate solution of the inertial navigation system, which is corrected by the Kalman filter, is used to aid on-the-fly resolution of the carrier phase integer ambiguity of global positioning system in order to incorporate the carrier phase measurements into the Kalman filter, and to aid the carrier phase and code tracking loops of the receiver of the global positioning system to improve the receiver jamming and high dynamic resistance.

Radar-assisted collision avoidance/guidance strategy for planar flight

Abstract: We propose a radar-assisted collision avoidance/guidance strategy (RACAGS) for flight vehicles on low altitude missions. The task of obstacle avoidance and guidance are integrated in a single collision avoidance/guidance strategy. The avionic aids and computational requirements are modest as the strategy mainly depends on range-map and inertial system information. The strategy is first implemented in a planar scenario and then extended to three-dimensional and nominal trajectory following flight scenarios. Several simulation studies are presented for illustration.

Attitude determination and alignment using electro-optical sensors and global navigation satellites

Abstract: An attitude determination and alignment method and system use electro-optical sensors and global navigation satellites to determine attitude knowledge for a spacecraft, satellite, or a high-altitude aircraft. An on-board inertial navigation system uses global navigation satellite system equipment and an attitude determination system uses an electro-optical sensor. The electro-optical sensor view the navigation satellites as surrogate stellar reference sources. The electro-optical sensor replaces the function of a star sensor or tracker and associated processing required for an onboard attitude determination system. Navigation and timing information generated by the GPS/GNSS-INS is used to perform required attitude determination system functions.

Stochastic mapping using forward look sonar

Abstract: This paper investigates the problem of concurrent mapping and localization (CML) using forward look sonar data. Results are presented from processing of an oceanic data set from an 87 kHz US Navy forward look imaging sonar using the stochastic mapping method for CML. The goal is to detect objects on the seabed, map their locations, and concurrently compute an improved trajectory for the vehicle. The resulting trajectory is compared with position estimates computed with an inertial navigation system and Doppler velocity sonar. The results demonstrate the potential of concurrent mapping and localization algorithms to satisfy the navigation requirements of undersea vehicles equipped with forward look sonar.

Sequential Monte Carlo filtering techniques applied to integrated navigation systems

Abstract: This paper addresses the problem of integrated aircraft navigation, more specifically how to integrate inertial navigation with terrain aided positioning. This is a highly nonlinear and non-Gaussian recursive state estimation problem which requires state of the art methods. We propose an algorithm based on the particle filter with particular attention to the complexity of the problem. The proposed algorithm takes advantage of linear and Gaussian structure within the system and solves these parts using the Kalman filter. The remaining parts suffering from severe nonlinear and/or non-Gaussian structure are solved using the particle filter. The proposed filter is applied to a simplified integrated navigation system. The result shows that very good performance is achieved for a tractable computational load.

Rover localization results for the FIDO rover

Abstract: This paper describes the development of a two-tier state estimation approach for NASA/JPL's FIDO Rover that utilizes wheel odometry, inertial measurement sensors, and a sun sensor to generate accurate estimates of the rover's position and attitude throughout a rover traverse. The state estimation approach makes use of a linear Kalman filter to estimate the rate sensor bias terms associated with the inertial measurement sensors and then uses these estimated rate sensor bias terms to compute the attitude of the rover during a traverse. The estimated attitude terms are then combined with the wheel odometry to determine the rover's position and attitude through an extended Kalman filter approach. Finally, the absolute heading of the vehicle is determined via a sun sensor which is then utilized to initialize the rover's heading prior to the next planning cycle for the rover's operations. This paper describes the formulation, implementation, and results associated with the two-tier state estimation approach for the FIDO rover.

LED location beacon system based on processing of digital images

Abstract: This paper is in the field of vehicle positioning technology for the intelligent transportation systems. The ideas of an innovative light-emitting diode (LED)-based location beacon system are developed and verified. The system developed is a combination of several latest technologies which include a CMOS vision sensor, high brightness LED, and digital image processing techniques. It belongs to a new kind of simplex communication link. A digital camera is used to capture images contained in the LED beacon signal. The captured digital images are processed by the algorithms developed and a location code is extracted. The location code can be used for calibration of a vehicle positioning system which may consist of a GPS, inertial navigation system (INS) and other sensors. The issues examined include the structure of the transmitter and the receiver, the signaling method, the transmission protocol of the LED panel, the relationship between the camera capturing rate and the LED pattern update rate, the digital camera exposure technology, and the efficiency of the image processing algorithms. Experiments using a prototype transmitter and a receiver were performed. The experimental results provide a good demonstration of the viability of the ideas and methodologies developed.

Airborne turbulence measurements in the lower troposphere onboard the research aircraft dornier 128-6, D-IBUF

Abstract: The research aircraft Dormer (DO) 128-6, call-sign D-IBUF, operated by the Institute of Flight Guidance and Control of the Technical University of Braunschweig and its scientific equipment is presented The aircraft's operational capabilities and the quality of measurements of meteorological parameters and trace constituents in the lower troposphere are discussed Besides avionic instrumentation for VFR-flights (Visual Flight Rules) and IFR-flights (Instrument Flight Rules) at low altitudes over complex terrain, there are redundant sensors for the measurement of wind, temperature and humidity Together with INS- (Inertial Navigation System) and GPS- (Global Positioning System) navigation a sample frequency of 25 Hz (soon 100 Hz) is realised Using a mean ground speed of 65 m s -1 , the resolution of the measurements is less than 3 m Since 1998, the Institute of Meteorology and Climate Research at the Forschungszentrum Karlsruhe has enlarged the aircraft's research capabilities by the integration of a sensor package for the measurement of CO, NO, NO 2 CO 2 and O 3 with frequencies between 1 Hz and 20 Hz, and detection limits of 1 ppb The equipment does not only allow to detect mean quantities, but also, using the eddy-correlation technique, to calculate small-scale turbulent trace gas fluxes, eg caused by secondary circulation systems, mountain venting, convective cells and other mass transport processes between the boundary layer and the free troposphere (handover) Such data are of great importance to many aspects of air pollution dispersion and air pollution modelling Process studies of the small-scale vertical transport of heat, moisture and trace gases and their parametrisation are some of these aspects The function of the sensor package is shown by calibration results, intercomparison of the measurements of redundant sensors and spectral analysis of the wind components Examples of the detection of secondary circulation systems, of the micro structure of trace gases in urban plumes and the calculation of ozone flux profiles are given

Development of an INS/GPS Navigation Loop for an UAV

Abstract: This master thesis report presents the developement of an INS/GPS navigation loop written in ANSI C++ using a standard matrix library. The filter have been tested on an Unmanned Aerial Vehicle (UAV) called Brumby. Here data have been logged from the Inertial Measurement Unit (IMU) and the Global Positioning System (GPS) receiver. This data have then been postprocessed and run through the navigation filter for estimation of position, attitude and velocity of the vehicle during the flights. The error feedback to the Inertial Navigation System (INS) is done with a complement filter implemented using a kalman filter written in information form.The resulting navigation filter estimates the attitude within two degrees with 95% confidence and the position within two meter using 95% confidence.

Two Different Approaches for Augmented GPS Pedestrian Navigation

Abstract: This paper present the calibration of the different models used for pedestrian navigation. Information on travelled distance and azimuth sensed by inertial sensors is merged with GPS observation through Kalman filtering. All models use GPS positions without differential corrections to calibrate systematic errors present in inertial sensors.

Bridging GPS Gaps in Urban Canyons: The Benefits of ZUPTs

Abstract: This paper describes a study which looked at the impact of zero velocity updates (ZUPTs) on navigation accuracy in urban canyons. Focus was on the speed and reliability of ambiguity resolution supported by periodic ZUPTs. The paper also presents an analysis of the positioning errors after ZUPT events versus unaided and GPS/inertial navigation system (INS) results. The observability aspects of static INS calibration are also briefly addressed.

Adaptive gps and ins integration system

Abstract: This invention relates to the field of Inertial Navigation Systems (INS) and satellite navigation systems such as the Global Positioning System (GPS) and in particular relates to methods of integrating GPS and INS data in order to provide more accurate navigation solutions. The invention provides a method of improving the accuracy of a tightly coupled integrated INS and satellite radio navigation system in cases where the satellite navigation receiver has adaptive tracking loop bandwidths.