Showing papers on "Inertial navigation system published in 2003"

Adaptive Kalman Filtering for Low-cost INS/GPS

Abstract: GPS and low-cost INS sensors are widely used for positioning and attitude determination applications. Low-cost inertial sensors exhibit large errors that can be compensated using position and velocity updates from GPS. Combining both sensors using a Kalman filter provides high-accuracy, real-time navigation. A conventional Kalman filter relies on the correct definition of the measurement and process noise matrices, which are generally defined a priori and remain fixed throughout the processing run. Adaptive Kalman filtering techniques use the residual sequences to adapt the stochastic properties of the filter on line to correspond to the temporal dependence of the errors involved. This paper examines the use of three adaptive filtering techniques. These are artificially scaling the predicted Kalman filter covariance, the Adaptive Kalman Filter and Multiple Model Adaptive Estimation. The algorithms are tested with the GPS and inertial data simulation software. A trajectory taken from a real marine trial is used to test the dynamic alignment of the inertial sensor errors. Results show that on line estimation of the stochastic properties of the inertial system can significantly improve the speed of the dynamic alignment and potentially improve the overall navigation accuracy and integrity.

Vision and inertial sensor cooperation using gravity as a vertical reference

Abstract: This paper explores the combination of inertial sensor data with vision. Visual and inertial sensing are two sensory modalities that can be explored to give robust solutions on image segmentation and recovery of 3D structure from images, increasing the capabilities of autonomous robots and enlarging the application potential of vision systems. In biological systems, the information provided by the vestibular system is fused at a very early processing stage with vision, playing a key role on the execution of visual movements such as gaze holding and tracking, and the visual cues aid the spatial orientation and body equilibrium. In this paper, we set a framework for using inertial sensor data in vision systems, and describe some results obtained. The unit sphere projection camera model is used, providing a simple model for inertial data integration. Using the vertical reference provided by the inertial sensors, the image horizon line can be determined. Using just one vanishing point and the vertical, we can recover the camera's focal distance and provide an external bearing for the system's navigation frame of reference. Knowing the geometry of a stereo rig and its pose from the inertial sensors, the collineations of level planes can be recovered, providing enough restrictions to segment and reconstruct vertical features and leveled planar patches.

Real-time integration of a tactical-grade IMU and GPS for high-accuracy positioning and navigation

Abstract: The integration of the Global Positioning System (GPS) and Inertial Navigation Systems (INSs) is often used to provide accurate positioning and navigation information. For applications requiring the highest accuracy, the quality of the inertial sensors required is usually assumed to be very high. This dissertation investigates the integration of GPS with a tactical-grade Inertial Measurement Unit (IMU) for centimetre-level navigation in real-time. Different GPS/INS integration strategies are investigated to assess their relative performance in terms of position and velocity accuracy during partial and complete data outages, carrier phase ambiguity resolution after such data outages, and the overall statistical reliability of the system. In terms of statistical reliability, the traditional equations used in dynamic systems are redeveloped in light of some practical considerations, including centralized and decentralized filter architectures, and sequential versus simultaneous measurement updating. Results show that the integrated solution outperforms the GPS-only approach in all areas. The difference between loose and tight integration strategies was most significant for ambiguity resolution and system reliability. The integrated solution is capable of providing decimetre-level accuracy or better for durations of about five or ten seconds when a complete or partial GPS outage is simulated. This level of accuracy, extended over longer time intervals, is shown to reduce the time required to resolve the L1 ambiguities by an average of about 50% or more for data outages as long as 30 seconds when using a tight integration strategy. More importantly, the reliability of the ambiguity resolution process is improved with the integrated

Navigation: Principles of Positioning and Guidance

Abstract: From the Table of Contents: Abbreviations and acronyms Introduction Historical review Mathematical fundamentals Physical fundamentals Maps Terrestrial navigation Celestial navigation Terrestrial radio navigation Satellite-based navigation Augmentation systems Inertial navigation Image-based navigation Integrated navigation Routing and guidance Vehicle and traffic management Application examples Critical outlook References Index

Sporting equipment provided with a motion detecting arrangement

Abstract: Method and arrangement for detecting movement-parameters in a moving object. The parameters include acceleration and angular velocity of the object, the arrangement includes an Inertial Navigation System (INS) having at least one gyroscope and accelerometer for measuring an acceleration, angular velocity and effect of attraction of gravity on the sporting equipment.

Real-Time Navigation, Guidance, and Control of a UAV Using Low-Cost Sensors.

Abstract: Applying low-cost sensors for the Guidance, Navigation and Control (GNC) of an autonomous Uninhibited Aerial Vehicle (UAV) is an extremely challenging area. This paper presents the real-time results of applying a low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) receiver for the GNC. The INS/GPS navigation loop provides continuous and reliable navigation solutions to the guidance and flight control loop for autonomous flight. With additional air data and engine thrust data, the guidance loop computes the guidance demands to follow way-point scenarios. The flight control loop generates actuator signals for the control surfaces and thrust vector. The whole GNC algorithm was implemented within an embedded flight control computer. The real-time flight test results show that the vehicle can perform the autonomous flight reliably even under high maneuvering scenarios.

Performance Analysis and Architectures for INS-Aided GPS Tracking Loops

Abstract: GPS and inertial sensors have complementary characteristics, which have been exploited in the design of integrated GPS-inertial navigation and guidance systems. Traditionally, most hybrid GPS-inertial systems have been mechanized by combining the information from GPS and an Inertial Navigation System using either loose integration (i.e., integration at the position, velocity and/or attitude level) or tight integration (integration at the pseudorange, Doppler, or carrier phase level). Such integration schemes provide users with limited immunity against momentary GPS outages and also allow detection of certain classes of GPS signal failures. A third scheme of integration can be used, in which the inertial sensors are used to aid the GPS phase frequency and code tracking loops directly. In this paper, this level of coupling is referred to as ultra-tight integration, and it offers potential improvements to GPS performance, such as higher phase-tracking bandwidth, and more resistance to radio frequency interference or multipath noise. In this paper we propose a simple architecture for GPS-inertial systems with ultra-tight integration and present the results of some trade studies and simulations quantifying the performance of such systems. Performances of the ultra-tight GPS-inertial system are evaluated using a simulation tool developed specifically for this study. The metrics used for the evaluation are allowable reduction in the carrier tracking loop-filter bandwidth for improved signal-to-noise ratio, and robustness against carrier-phase cycle-slips. The sensitivity of these metrics to inertial sensor quality and GPS receiver clock noise is discussed and quantified. These studies show that an ultra-tightly coupled system using low cost/performance inertial sensors and a typical temperature-compensated crystal oscillator can function with a carrier tracking loop-filter bandwidth as low as 3Hz. This structure shows a 14dB improvement in phasenoise suppression when compared to a traditional 15Hz loop filter, and comparable carrier-phase tracking bandwidth to that of the inertial sensors (>30Hz).

Low-cost flight control system for a small autonomous helicopter

Abstract: In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

Indoor Positioning System Using Accelerometry and High Accuracy Heading Sensors

Abstract: The current GPS signal structure and signal power levels are barely sufficient for indoor applications. Recent developments in high sensitivity receiver technology are promising for indoor positioning inside light structures such as wooden frame houses but generally not for concrete high rise buildings. Errors due to multipath and noise associated with weak indoor signals limit the accuracy and availability of GNSS in difficult indoor environments. An alternate approach makes use of inertial technologies. However, the use of a strapdown inertial navigation system (INS) system and its traditional mechanization as a personal indoor positioning system is rather unrealistic due to the rapidly growing positioning errors caused by gyro drifts. Even a high performance INS will cause hundreds of metres of positioning error in 30 minutes without GPS updates. The majority of previously proposed personal positioning systems utilize the Pedestrian Dead Reckoning (PDR) approach. These systems use accelerometers for step detection and step length estimation and magnetic compasses or low cost gyros for heading determination. In such systems, the error sources are the step length estimation error and the heading error. Assuming no heading error, the positioning error is directly proportional to the number of steps and, thus, to the distance traveled. However, the critical component of these systems is heading. Indoor, apart from measuring the Earth's magnetic field, magnetic sensors will be subject to other local electromagnetic fields. Over time, low cost gyros will drift in a significant and unpredictable manner which makes them unsuitable for obtaining adequate heading information. In this paper, the heading problem is resolved by using one deg/hour ring laser gyros. A tactical-grade IMU is used to provide accurate heading information, and accelerometers are used only for step occurrence detection. A special study is carried out to examine errors in heading, if only one gyro is used instead of three. In this case, the three-gyro solution is used as a reference. To test the concept, several long period tests were performed, carrying the IMU in a backpack. Both DGPS and stand-alone receivers were included to compare two different level initialization sources. 3D-gyro heading solutions initialized with DGPS are promising. However, if only one gyro is used or DGPS is not available, heading solution accuracy degrades significantly. Size restrictions on current ring laser gyros limit the application of the proposed system. However, as gyro technology evolves, such a system may be beneficial for applications such as the positioning of rescue workers, police squads, and other indoor location and navigation applications.

Modification of vehicle handling characteristics via steer-by-wire

Abstract: This paper presents a physically intuitive method for altering a vehicle handling characteristics through active steering intervention. A full state feedback controller augments the driver steering command via steer-by-wire to achieve desired handling behavior. Accurate estimates of vehicle states are available from a combination of the Global Positioning System (GPS) and inertial navigation system (INS) sensor measurements. By canceling the effects of steering system dynamics and tyre disturbance forces, the steer-by-wire system is able to track commanded steer angle with minimal error. Experimental results verify that with precise steering control and accurate state information, a vehicle handling characteristics can be modified to match driver preference or to compensate for changes in operating conditions.

Airborne reconnaissance system

Abstract: An airborne reconnaissance system comprising: (1) Gimbals having at least two degrees of freedom; (2) At least one array of light sensors positioned on the gimbals, for being directed by the same within at least two degrees of freedom; (3) Map storage means for storing at least one Digital Elevation Map of an area of interest, divided into portions; (4) Inertial Navigation System for real-time providing to a gimbals control unit navigation and orientation data of the aircraft with respect to a predefined global axes system;(5) Portion selection unit for selecting, one at a time, another area portion from the area of interest; and (6) servo means for directing the gimbals. The system uses data from the inertial navigation system and from the digital elevation map for real-time calculating direction to selected area portions, and for maintaining the direction during integration of light from the terrain, and for producing corresponding images of area portions.

A toolbox of aiding techniques for the HUGIN AUV integrated inertial navigation system

Abstract: Modern AUV designs must handle submerged autonomous operation for long periods of time. The state of the art solution embedded in the HUGIN AUVs is a Doppler velocity log (DVL) aided inertial navigation system (INS) that can integrate various forms of position measurement updates. In autonomous operations, position updates are only available in limited periods of time or space, thus the core velocity aided inertial navigation system must exhibit high accuracy. However, position uncertainty of a DVL aided inertial navigation system will eventually drift off, compromising either mission operation or requirements for accurate positioning of payload data. To meet the requirements for a range of military and civilian AUV applications, the HUGIN vehicles come with at flexible and powerful set of navigation techniques. Methods for position updates include GPS surface fix, DGPS-USBL, underwater transponder positioning (UTP) and bathymetric terrain navigation. Based on synthetic aperture sonar technology, a potentially revolutionary accurate velocity measurement is under development. HUGIN also comes with a navigation post-processing system (NavLab), which can be applied to increase navigational integrity and maximize position accuracy.

Inertial navigation system for mobile objects with constraints

Abstract: An aided inertial navigation system and method for navigating a mobile object having constraints comprising an inertial measurement unit, a processor, and an error correction device. The inertial measurement unit provides acceleration data and/or angular velocity data of the mobile object. The processor is adapted to receive the acceleration data and/or angular velocity data, and to provide output data with position output indicative of position of the mobile object. The error correction device receives as input, state and dynamics information and auxiliary input data including map information associated with the path, speed data, wheel-angle data and discrete data. The error correction device provides as output, state corrections to the processor that enhance accuracy of the position output. The state corrections are used by the processor to estimate position of the mobile object based on the constraints to the mobile object and the map information associated with the path.

Method and system for automatically activating a warning device on a train

Abstract: A method and system for automatically activating a train warning device that uses a positioning system such as a global positioning system (GPS) receiver or an inertial navigation system (INS) to determine the train's position. The system further includes a database containing locations of grade crossings and other locations at which a train is required to give a warning signal and what regulations govern activation of the warning device at such locations.

Magnetometer and differential carrier phase GPS-aided INS for advanced vehicle control

Abstract: This paper describes the design, analysis, implementation, and experimental results of a triple redundancy navigation system incorporating magnetometer, inertial, and carrier phase differential Global Positioning System (GPS) measurements. The navigation system is able to accurately estimate vehicle attitude (including yaw) as long as the vehicle velocity is not zero. The motivating application was lateral vehicle control for intelligent highway systems. The system was designed to operate reliably whether or not GPS and magnetometer measurements were available. The navigation system provides vehicle position, velocity, acceleration, pitch and roll, yaw, and angular rates at 150 Hz with accuracies (standard deviation) of 2.8 cm, 0.8 cm/s, 2.2 cm/s/s, 0.03/spl deg/, 0.18/spl deg/, and 0.1/spl deg//s. This navigation state vector was processed to produce a control state vector at approximately 30 Hz. This triplicate redundancy navigation system reliably demonstrated lateral vehicle control in the following situations: both GPS and magnetometer aiding the inertial navigation system (INS), GPS-aided INS, magnetometer aided-INS, and switching between GPS and magnetometer aiding of the INS at random times.

Low cost GPS/INS sensor fusion system for UAV navigation

Abstract: The performance of UAV is dependent greatly upon onboard sensors due to its characteristics of unmanned operated vehicle. The navigation sensor, which informs where UAV is flying, also is one of those onboard sensors. Small UAV needs the navigation system with the compact, light, cheap and precise navigation solution. As the inertial sensor for precise air navigation is very expensive, it is not popular in small aircraft and UAV. While GPS services a seamless navigation with cheap receiver, it may not receive the satellite signal by the obstacles or the signal jamming. It is GPS/INS sensor fusion that might overcome these constraints. GPS receiver on air vehicle may happen to lose the signal in a dynamic environment such as aircraft maneuver. The multiple GPS antennas were used to increase the coverage of GPS receiver. The ground test showed that GPS/INS sensor fusion system could provide well the attitude information as well as the trajectory according to a vehicle movement.

Seamless sensory system

Abstract: The Seamless Sensory System (3S), the invention, integrates state-of-the-art sensor technology with modern software engineering practices to create seamless positioning. The invention can include the incorporation of GPS/Inertial Navigation/IR and other technologies into a handheld/man wearable/mounted system that will not be compromised in hostile environments. The invention continues accurate navigation in the absence of GPS satellite signals. The invention utilizes a “continuous calibration” Kalman Filter methodology and motion sensor(s) to maintain “GPS-like” accuracy after GPS signals are no longer available. A proprietary technology called an Ultrasonic Doppler Velocity Measurement (UVM) Sensor is the invention's ‘key component’ to create “GPS like performance” under any GPS denied condition. Additional sensors are included to complete the picture of the local environment.

Particle filtering and Cramer-Rao lower bound for underwater navigation

Abstract: We have studied a sea navigation method relying on a digital underwater terrain map and sonar measurements. The method is applicable for both ships and underwater vessels. We have used experimental data to build an underwater map and to investigate the estimation performance. Since the problem is non-linear, due to the measurement relation, we apply a sequential Monte Carlo method, or particle filter, for the state estimation. The fundamental limitations in navigation uncertainty can be described in terms of the Cramer-Rao lower bound, which is interpreted in terms of the inertial navigation system (INS) error, the sensor accuracy and the terrain map excitation. Hence, the Cramer-Rao lower bound can be interpreted and used in the design for INS systems, sensor performance or, if these are given, how much terrain or depth excitation that is needed for use in positioning and navigation.

Direct modification of DGPS information with inertial measurement data

Abstract: A global positioning system based navigation system for a ground vehicle, in particular an agricultural ground vehicle such as a tractor, combine, sprayer, or the like, includes an inertial compensation assembly that provides inertial augmentation to compensate global positioning system based navigation information such as position, course, and track spacing for errors caused by variation of ground vehicle attitude (i.e., roll and yaw) over non-level terrain.

Self-position estimating device for leg type movable robots

Abstract: On the basis of a deviation between the detected or estimated value of the actual attitude of a predetermined region of the upper body (3) or the like of a robot (1), and the posture of a target gait, the amount of attitude rotation deviation change as the amount of time-dependent change in this deviation is found. Supposing that the robot (1) has turned around a certain axis of rotation by this amount of rotation deviation change, the position of the robot (1) (for example, ground-engaging position) is estimated. Further, the accuracy of the estimated position is improved by correcting the estimated position of the robot (1) by inertial navigation system according to the difference between this estimated position and the position of the robot (1) estimated by inertial navigation system using an acceleration sensor or the like.

Carrier Phase GPS-Aided INS-Based Vehicle Lateral Control

Abstract: This paper describes the design, analysis, and implementation of a vehicle control system using control state information obtained from a carrier phase (CP) differential global positioning system (DGPS) aided inertial navigation system (INS). Experimental data from CP DGPS/INS control experiments onboard a PATH 1 vehicle is included. This testing was completed with a magnetometer sensing system onboard and running to provide a ground truth reference for comparison with the CP DGPS/INS. Navigation accuracy has previously been demonstrated at the cm level with the full navigation state updated at 150 Hz. In this article, lateral position control performance is demonstrated during challenging high-speed maneuvers with trajectory tracking accuracy at the decimeter level. During these initial experiments, the control state updated at 30 Hz. Increased trajectory following accuracy is possible, but there is an inherent tradeoff between the tracking accuracy and the ride comfort. This level of performance demonstrates that CP DGPS/ INS technology has the potential to serve as one component of the reliable multisensor centimeter-level position reference system that is necessary for vehicle position control applications, including automated highway systems (AHS).

Spatial image information system and method for supporting efficient storage and retrieval of spatial images

Abstract: Disclosed is a spatial image information method and system for rapid and efficient storage in a relation type database and retrieval and management of spatial images acquired by a combined system of a global positioning system (GPS), an inertial navigation system (INS), and an image acquisition device (i.e., CCD camera). The spatial image acquired by the GPS/INS/CCD camera combined system is combined with an exterior orientation composed of a camera position (x,y,z), accelerated velocity, slope and direction at the moment the image is acquired and an interior orientation acquired by a camera calibration, so that calculation of a specified spatial coordinate information becomes possible. The spatial image information system includes a section for efficiently storing a chain of still spatial image sequences acquired by the GPS/INS/CCD camera combined system, the exterior orientation, and the interior orientation in the relation type database, a section for storing spatial information recognized as the same object by a user as maintaining the relationship with the stored still spatial image sequences, a section for efficiently retrieving images that satisfy a certain spatial information operation from the still spatial image sequences, and an interface section for external systems.

Foot-to-Foot Range Measurement as an Aid to Personal Navigation

Abstract: Ultimately there will be times when all enhancements to GPS signal reception fail. In these situations a number of approaches to GPS denied navigation have been proposed. These often make use of supplemental radio frequency signals, some of which actually require setting up a local RF infrastructure. The personal navigation aid proposed here, although utilizing a radio frequency signal, is intended to be self contained and of low power. It consists of a micromechanical IMU on each boot combined with a series of foot-to-foot range measurements. A frequency generator at the waist sends a signal down one leg to a transmitting antenna on one boot. The RF signal is received on the other boot and sent to the waist pack thereby closing the loop. A detector at the waist measures phase change and thus measures the changing distance between the two feet. Our analysis shows that this scalar distance change measurement used in conjunction with micro-mechanical inertial instruments on each foot and combined with "zero-velocity updates" at each (or most) foot falls enables quite accurate personal navigation. The performance of an unaided inertial navigation system based on modest quality micromechanical instruments is truly poor. Our analysis shows a 2.5 km error in each horizontal direction after walking in a straight line for 10 minutes (2900 ft). The addition of zero velocity updates reduces this error to 60 m predominantly in the cross range axis. The addition of the foot-to-foot range change measurement reduces this value by another two orders of magnitude, to 0.6 m This measurement concept is a big step toward an accu-rate self-contained personal navigation system It is not dependent on external signals or ambient light. The RF could be very low power (it only has to extend over the foot-to-foot distance). As such it should be relatively covert compared to a Doppler radar or acoustic Doppler device. There is a price to pay in terms of body mounted hardware, but this could be mitigated by the push toward instrumented clothing.

Multisensor integration using neuron computing for land-vehicle navigation

Abstract: Most of the present navigation sensor integration techniques are based on Kalman-filtering estimation procedures. Although Kalman filtering represents one of the best solutions for multisensor integration, it still has some drawbacks in terms of stability, computation load, immunity to noise effects and observability. Furthermore, Kalman filters perform adequately only under certain predefined dynamic models. Neuron computing, a technology of artificial neural network (ANN), is a powerful tool for solving nonlinear problems that involve mapping input data to output data without having any prior knowledge about the mathematical process involved. This article suggests a multisensor integration approach for fusing data from an inertial navigation system (INS) and differential global positioning system (DGPS) hardware utilizing multilayer feed-forward neural networks with a back propagation learning algorithm. In addition, it addresses the impact of neural network (NN) parameters and random noise on positioning accuracy.

Signal processing for AUV based interferometric synthetic aperture sonar

Abstract: This paper presents signal processing techniques particularly suited for interferometric Synthetic Aperture Sonar (SAS) systems onboard Autonomous Underwater Vehicles (AUV) (or other platforms carrying high grade navigation systems). The signal processing is applied to data collected in a controlled rail experiment at Elba Island, Italy, using a wideband interferometric SAS and an Inertial Navigation System (INS). We evaluate different strategies in fusing sonar micronavigation by the Displaced Phase Center Antenna (DPCA) technique with Aided INS (AINS). We obtained highest navigation accuracy using DPCA as aiding sensor into the AINS, then using raw DPCA surge and sway in combination with the AINS attitude and position. Coarse cross correlation based bathymetry and full resolution interferometry (based on the interferogram) is tested on the full swath and objects. Coarse bathymetry is more reliable than the interferogram technique. Phase wraparounds are avoided by estimating the coarse bathymetry first, then using the full resolution phase estimates as correction. Although much work remains, this technique does show a clear potential in improving object classification ability.

System and a method of three-dimensional modeling and restitution of an object

Abstract: The invention relates to a system for three-dimensionally modeling and restitution a subject, the system comprising a housing suitable for being carried in the hand by an operator, the housing having an optical unit with stereoscopic digital video cameras co-operating with an inertial navigation unit having a trihedron of optical fiber gyros and a trihedron of accelerometers for generating position and displacement signals in a frame of reference. The housing may also include, in particular, a telemeter laser, an infrared video camera, a GPS unit, inclinometers, and tri-flux magnetometers. A second subassembly connected to the housing by an optical and/or electrical connection cable contains an electrical power supply, electronic circuits, and a microcomputer for processing signals delivered by the housing and for generating a three-dimensional model of the subject, implementing a photogrammetric technique.

Optimising the Transfer Alignment of Weapon INS

Abstract: Transfer alignment is the process of initialising and calibrating a weapon INS using data from the host aircraft's navigation system. To determine which transfer alignment technique performs best, different design options have been assessed, supported by simulation work. The dependence of transfer alignment performance on environmental factors, such as manoeuvres, alignment duration, lever arm and inertial sensor quality has also been studied. ‘Rapid’ alignment, using attitude as well as velocity measurements was found to perform better than ‘conventional’ techniques using only velocity. Innovative developments include the estimation of additional acceleration and gyro states and estimation of force dependent relative orientation, which has enabled robust alignment using wing rock manoeuvres, which do not require the pilot to change trajectory. Transfer alignment has been verified in real-time by flight trials on a Tornado aircraft. In addition, techniques have been developed to prevent transients in the aircraft integrated navigation solution following GPS re-acquisition after an outage of several minutes from disrupting the transfer alignment process.

Constrained unscented Kalman filter based fusion of GPS/INS/digital map for vehicle localization

Abstract: Accurate vehicle localization is very important for various applications of intelligent transportation systems (ITS) including cooperative driving, collision avoidance, and vehicle navigation. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to fuse differential global position system (DGPS), inertial navigation system (INS) and digital map to estimate the vehicle states. Using the road geometry information obtained from a digital map database, some state constraints can be formed. The measurements of DGPS and INS are used to set up the dynamic and measurement equations of the nonlinear filtering. The vehicle states are first estimated by the loosely coupled DGPS/INS system and the unconstrained UKF, and then the UUKF estimates are projected into the state constraints to obtain the final CUKF estimates. Synthetic and real data are used to evaluate the performance of the CUKF algorithm for fusing DGPS, INS and digital map.

Low cost automation using INS/GPS data fusion for accurate positioning

Abstract: Low cost automation often requires accurate positioning. This happens whenever a vehicle or robotic manipulator is used to move materials, parts or minerals on the factory floor or outdoors. In last few years, such vehicles and devices are mostly autonomous. This paper presents the method of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-D environment and is of particular importance for guidance, navigation, and control of mobile, autonomous vehicles. The Extended Kalman Filter (EKF) and the noise characteristic have been modified using the Fuzzy Logic Adaptive System and compared with the performance of regular EKF. It has been demonstrated that the Fuzzy Adaptive Kalman Filter gives better results (more accurate) than the EKF. The presented method is suitable for real-time control and is relatively inexpensive. Also, it applies to fusion process with sensors different than INS or GPS.