Showing papers on "Inertial navigation system published in 2005"

Pedestrian tracking with shoe-mounted inertial sensors

Abstract: A navigation system that tracks the location of a person on foot is useful for finding and rescuing firefighters or other emergency first responders, or for location-aware computing, personal navigation assistance, mobile 3D audio, and mixed or augmented reality applications. One of the main obstacles to the real-world deployment of location-sensitive wearable computing, including mixed reality (MR), is that current position-tracking technologies require an instrumented, marked, or premapped environment. At InterSense, we've developed a system called NavShoe, which uses a new approach to position tracking based on inertial sensing. Our wireless inertial sensor is small enough to easily tuck into the shoelaces, and sufficiently low power to run all day on a small battery. Although it can't be used alone for precise registration of close-range objects, in outdoor applications augmenting distant objects, a user would barely notice the NavShoe's meter-level error combined with any error in the head's assumed location relative to the foot. NavShoe can greatly reduce the database search space for computer vision, making it much simpler and more robust. The NavShoe device provides not only robust approximate position, but also an extremely accurate orientation tracker on the foot.

Strapdown Inertial Navigation Technology, Second Edition

Abstract: photographing -not to mention walking in the city -plus those of us engaged with defense activities can state it is more convenient to get lost if one knows where this happ ens. Perhaps this is one of the key reasons why methods and technologies for navigation have been an area of continuing efforts and interest. After the introduction of fast moving vehicles, and later when defensive or hostile weapons came into use, it was not sufficient to know where the platform was located but it was really vital to be aware of its momentary alignment, of course , in a three dimensional space. New challenges were put to the shoulders of the navigator. When time, equipment. and location allow, navigation rel ying on external references such as radio beacons on ground or up in the space orbits are often preferred. However, such cooperative systems may not be available, or their performance is inadequat e for the short time constants of platform motion. We are thus forced to use autonomous navigation modes. It is here that inertial navigation systems have.

Design of a wireless assisted pedestrian dead reckoning system - the NavMote experience

Abstract: In this paper, we combine inertial sensing and sensor network technology to create a pedestrian dead reckoning system. The core of the system is a lightweight sensor-and-wireless-embedded device called NavMote that is carried by a pedestrian. The NavMote gathers information about pedestrian motion from an integrated magnetic compass and accelerometers. When the NavMote comes within range of a sensor network (composed of NetMotes), it downloads the compressed data to the network. The network relays the data via a RelayMote to an information center where the data are processed into an estimate of the pedestrian trajectory based on a dead reckoning algorithm. System details including the NavMote hardware/software, sensor network middleware services, and the dead reckoning algorithm are provided. In particular, simple but effective step detection and step length estimation methods are implemented in order to reduce computation, memory, and communication requirements on the Motes. Static and dynamic calibrations of the compass data are crucial to compensate the heading errors. The dead reckoning performance is further enhanced by wireless telemetry and map matching. Extensive testing results show that satisfactory tracking performance with relatively long operational time is achieved. The paper also serves as a brief survey on pedestrian navigation systems, sensors, and techniques.

Modification of vehicle handling characteristics via steer-by-wire

Abstract: While changing the handling characteristics of a conventional vehicle normally requires physical modification, a vehicle equipped with steer-by-wire can accomplish the same effect through active steering intervention. This paper presents an intuitive method for altering a vehicle's handling characteristics by augmenting the driver's steering command with full vehicle state feedback. The vehicle can be made more or less responsive depending on the driver's preference and particular operating conditions. Achieving a smooth, continuous change in handling quality requires both accurate state estimation and well-controlled steering inputs from the steer-by-wire system. Accurate estimates of vehicle states are available from a combination of global positioning system (GPS) and inertial navigation system (INS) sensor measurements. By canceling the effects of steering system dynamics and tire 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, the handling modification is exactly equivalent to changing the front tire cornering stiffness.

Observability of error States in GPS/INS integration

Abstract: Observability properties of errors in an integrated navigation system are studied with a control-theoretic approach in this paper. A navigation system with a low-grade inertial measurement unit and an accurate single-antenna Global Positioning System (GPS) measurement system is considered for observability analysis. Uncertainties in attitude, gyro bias, and GPS antenna lever arm were shown to determine unobservable errors in the position, velocity, and accelerometer bias. It was proved that all the errors can be made observable by maneuvering. Acceleration changes improve the estimates of attitude and gyro bias. Changes in angular velocity enhance the lever arm estimate. However, both the motions of translation and constant angular velocity have no influence on the estimation of the lever arm. A covariance simulation with an extended Kalman filter was performed to confirm the observability analysis.

Strapdown inertial navigation system algorithms based on dual quaternions

Abstract: The design of strapdown inertial navigation system (INS) algorithms based on dual quaternions is addressed. Dual quaternion is a most concise and efficient mathematical tool to represent rotation and translation simultaneously, i.e., the general displacement of a rigid body. The principle of strapdown inertial navigation is represented using the tool of dual quaternion. It is shown that the principle can be expressed by three continuous kinematic equations in dual quaternion. These equations take the same form as the attitude quaternion rate equation. Subsequently, one new numerical integration algorithm is structured to solve the three kinematic equations, utilizing the traditional two-speed approach originally developed in attitude integration. The duality between the coning and sculling corrections, raised in the recent literature, can be essentially explained by splitting the new algorithm into the corresponding rotational and translational parts. The superiority of the new algorithm over conventional ones in accuracy is analytically derived. A variety of simulations are carried out to support the analytic results. The numerical results agree well with the analyses. The new algorithm turns out to be a better choice than any conventional algorithm for high-precision navigation systems and high-maneuver applications. Several guidelines in choosing a suitable navigation algorithm are also provided.

Sensor fusion for model-based detection in pipe and cable locator systems

Abstract: Line locator systems that fuse traditional sensors used in a combined pipe and cable locator (electromagnetic coils, magnetometers, and ground penetrating radar antennas) with low cost inertial sensors (accelerometers, gyroscopes) in a model-based approach are presented. Such systems can utilize inexpensive MEMS sensors for inertial navigation. A pseudo-inertial frame is defined that uses the centerline of the tracked utility, or an aboveground fixed object as the navigational reference. An inertial sensor correction mechanism that limits the tracking errors over time when the model is implemented in state-space form using, for example, the Extended Kalman Filter (EKF) is disclosed.

Design of accelerometer-based inertial navigation systems

Abstract: We examine the feasibility of designing an accelerometer-based (or gyroscope-free) inertial navigation system that uses only accelerometer measurements 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 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. The effects of accelerometer location and orientation errors are analyzed. Algorithms that identify and compensate these errors are developed.

Vision-Aided Inertial Navigation for Flight Control

Abstract: Published in the Journal of Aerospace Computing, Information, and Communication, Vol. 2, September 2005

Online INS/GPS integration with a radial basis function neural network

Abstract: Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.

Performance of an AUV navigation system at Arctic latitudes

Abstract: In October 2001, the Monterey Bay Aquarium Research Institute (MBARI) operated an autonomous underwater vehicle (AUV) in the Arctic at latitudes exceeding 80/spl deg/. The navigation instruments consisted of a ring-laser gyro inertial navigation system (INS) coupled with a DVL and GPS, a separate fiber-optic-based gyro-compass, and a traditional flux-gate AHRS system. The instruments were tested on deck, in open water, and under ice. This paper describes the performance of these instruments at high latitudes.

Epipolar Constraints for Vision-Aided Inertial Navigation

Abstract: This paper describes a new method to improve inertial navigation using feature-based constraints from one or more video cameras The proposed method lengthens the period of time during which a human or vehicle can navigate in GPS-deprived environments Our approach integrates well with existing navigation systems, because we invoke general sensor models that represent a wide range of available hardware The inertial model includes errors in bias, scale, and random walk Any purely projective camera and tracking algorithm may be used, as long as the tracking output can be expressed as ray vectors extending from known locations on the sensor body A modified linear Kalman filter performs the data fusion Unlike traditional SLAM, our state vector contains only inertial sensor errors related to position This choice allows uncertainty to be properly represented by a covariance matrix We do not augment the state with feature coordinates Instead, image data contributes stochastic epipolar constraints over a broad baseline in time and space, resulting in improved observability of the IMU error states The constraints lead to a relative residual and associated relative covariance, defined partly by the state history Navigation results are presented using high-quality synthetic data and real fisheye imagery

Sigma-Point Kalman Filtering for Integrated GPS and Inertial Navigation

Abstract: A sigma-point Kalman filter is derived for integrating GPS measurements with inertial measurements from gyros and accelerometers to determine both the position and the attitude of a moving vehicle. Sigma-point filters use a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard extended Kalman filter (KKF), leading to faster convergence from inaccurate initial conditions in position/attitude estimation problems. The filter formulation is based on standard inertial navigation equations. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is used to guarantee that quaternion normalization is maintained in the filter. Simulation and experimental results are shown to compare the performance of the sigma-point filter with a standard EKF approach.

NavLab, a Generic Simulation and Post-processing Tool for Navigation

Abstract: The ambition of getting one common tool for a great variety of navigation tasks was the background for the development of NavLab (Navigation Laboratory). The main emphasis during the development has been a solid theoretical foundation with a stringent mathematical representation to ensure that statistical optimality is maintained throughout the entire system. NavLab is implemented in Matlab, and consists of a simulator and an estimator. ○ Simulations are carried out by specifying a trajectory for the vehicle, and the available types of sensors. The output is a set of simulated sensor measurements. ○ The estimator is a flexible aided inertial navigation system, which makes optimal Kalman filtered and smoothed estimates of position, attitude and velocity based on the available set of measurements. The measurements can be either from the simulator or from real sensors of a vehicle. This structure makes NavLab useful for a wide range of navigation applications, including research and development, analysis, real data post-processing and as a decision basis for sensor purchase and mission planning. NavLab has been used extensively for mass-production of accurate navigation results (having post-processed more than 5000 hours of real data in four continents). Vehicles navigated by NavLab include autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs), ships and aircraft.

A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing

Abstract: In this paper, we develop a system for which applications in the field of personal navigation are planned. In the current version, the system embodies a Global Positioning System (GPS) receiver and an inertial measurement unit (IMU), composed of two dual-axis accelerometers and one single-axis gyro. The IMU is positioned at a subject's foot instep, and it is intended to produce estimates of some gait parameters, including stride length, stride time, and walking speed. Data from GPS and IMU are managed by a DSP-based control box. The computations performed by the DSP processor allow to detect subsequent foot contacts by a threshold-based method applied to gyro signal, and to reconstruct the trajectory of the foot instep by numerical strapdown integration. Features of human walking dynamics are incorporated in the algorithm to enhance the estimation accuracy against errors due to sensor noise and integration drift. All computations are performed by the DSP processor in real-time conditions. The foot sensor performance is assessed during outdoor level walking trials. The traveled distance estimated by inertial dead-reckoning is compared with the estimate produced by GPS in experimental conditions where GPS can be used as a reference source for accurate absolute positioning. Results show the remarkable accuracy achieved by foot inertial sensing.

Lane keeping based on location technology

Abstract: Vehicle positioning with an accuracy of 10 cm or less will enable lane-keeping assistance in addition to other safety benefits when an enhanced lane-level digital map is in place. With constantly evolving technology and sensors, a high-precision positioning system that fits into the automotive market can be expected within the next decade. Such a system will incorporate Global Positioning System (GPS) and inertial system (INS) for enhanced positioning performance and availability. In this paper, the technology fields that will have a significant impact on the deployment of a centimeter-level vehicle-positioning system will be discussed. Vision-based lane-recognition (VBLR) systems are relatively mature and have already been introduced to the market for lane-departure warning, etc. However, both systems have some limitations. GPS/INS-based systems may suffer from frequent satellite signal masking or blockage, while vision-based systems do not work well in adverse weather conditions or with poor lane signature. Effectively combining these two technologies can make a robust lane-departure warning system. A precision map was made for the test area near Stuttgart using DaimlerChrysler Research and Technology North America (RTNA)'s map-making approach. A Mercedes S-class equipped with both a vision system and a high-precision GPS/INS was used for the test. The positioning map-matching results and the vision offset are compared and the complementary effectiveness is illustrated.

Vision-aided inertial navigation for flight control

Abstract: Published in the Journal of Aerospace Computing, Information, and Communication, Vol. 2, September 2005

Daytime stellar imager

Abstract: An automatic celestial navigation system for navigating both night and day by observation of K-band or H-band infrared light from multiple stars. In a first set of preferred embodiments three relatively large aperture telescopes are rigidly mounted on a movable platform such as a ship or airplane with each telescope being directed at a substantially different portion of sky. Embodiments in this first set tend to be relatively large and heavy, such as about one cubic meter and about 60 pounds. In a second set of preferred embodiments one or more smaller aperture telescopes are pivotably mounted on a movable platform such as a ship, airplane or missile so that the telescope or telescopes can be pivoted to point toward specific regions of the sky. Embodiments of this second set are mechanically more complicated than those of the first set, but are much smaller and lighter and are especially useful for guidance of aircraft and missiles. Telescope optics focus (on to a pixel array of a sensor) H-band or K-band light from one or more stars in the field of view of each telescope. Each system also includes an inclinometer, an accurate timing device and a computer processor having access to catalogued infrared star charts. The processor for each system is programmed with special algorithms to use image data from the infrared sensors, inclination information from the inclinometer, time information from the timing device and the catalogued star charts information to determine positions of the platform. Direction information from two stars is needed for locating the platform with respect to the celestial sphere. The computer is also preferably programmed to use this celestial position information to calculate latitude and longitude which may be displayed on a display device such as a monitor or used by a guidance control system. These embodiments are jam proof and insensitive to radio frequency interference. These systems provide efficient alternatives to GPS when GPS is unavailable and can be used for periodic augmentation of inertial navigation systems.

Navigation Error Analysis of Atom Interferometer Inertial Sensor

Abstract: The recent development of the atom interferometer and its demonstration as an inertial sensor of acceleration and rotation rate augur a new generation of inertial navigation systems that would rival today's satellite navigation accuracy at the few-meter level. This paper reviews the principles of inertial measurement using the atom interferometer from a rudimentary viewpoint to illustrate the fundamentals and to highlight some of the potential shortcomings with a particular type, the cold-atom interferometer. One of these shortcomings is the fact that this interferometer requires a finite period of time during which the atoms are prepared (cooled) before they enter the interferometer and respond to its dynamics relative to an inertial frame. This lapse in the measurement duty cycle could be supplemented with very precise conventional inertial measurement units (IMUs), or eliminated with multiple, interleaved atom interferometers. Error analyses show that cold-atom interferometric IMUs that capture 50 percent of the dynamics must be coupled with conventional IMUs that are 50 times more accurate than typical navigation-grade units to sustain a horizontal position error of under 5 m (root mean square) after 1 h.

A Performance Comparison of Tightly Coupled GPS/INS Navigation Systems Based on Extended and Sigma Point Kalman Filters

Abstract: In this paper, the fusion of GPS pseudorange and deltarange measurements with inertial sensor data is adressed. For many years, extended Kalman filters (EKF) have been applied for this task with great success. However, from a theoretical point of view, the EKF is a sub-optimal choice: The system dynamics model, which is given by the inertial navigation strapdown equations, as well as the pseudorange and deltarange measurement models are nonlinear. The EKF approximates the propagation of Gaussian random vectors through these nonlinear equations by a linear transformation. This allows to capture the variance-covariance matrix of the propagated Gaussian random vectors with first order accuracy only. The family of sigma-point Kalman filters (SPKF) offers an approximation of variance-covariance matrix which is accurate to at least second order. Therefore, the performance of EKF-based and SPKFbased tightly coupled GPS/INS systems is compared in numerical simulations. Different inertial sensor grades from MEMS to FOG and a variety of scenarios are investigated, including situations with less than four satellites in view. Additionally, the simulation results were confirmed by the post-processing of raw GPS and inertial sensor data that was recorded during a test drive. It was found that except for specific situations without practical relevance, EKF and SPKF offer an identical performance. This is due to the fact that for tightly coupled - as well as loosely coupled - GPS/INS integration the higher-order transformation terms are negligible, which is shown analytically.

6DoF SLAM aided GNSS/INS Navigation in GNSS Denied and Unknown Environments

Abstract: This paper presents the results of augmenting 6DoF Simultaneous Localisation and Mapping (SLAM) with GNSS/INS navigation system. SLAM algorithm is a feature based terrain aided navigation system that has the capability for online map building, and simultaneously utilising the generated map to constrain the errors in the on-board Inertial Navigation System (INS). In this paper, indirect SLAM is developed based on error analysis and then is integrated to GNSS/INS fusion filter. If GNSS information is available, the system performs feature- based mapping using the GNSS/INS solution. If GNSS is not available, the previously and/or newly generated map is now used to estimate the INS errors. Simulation results will be presented which shows that the system can provide reliable and accurate navigation solutions in GNSS denied environments for an extended period of time.

A scheme for improving the performance of a gyroscope-free inertial measurement unit

Abstract: A gyroscope-free inertial measurement unit (GF-IMU) uses only accelerometers to compute specific force and angular rate. It is a low-cost inertial system, but its measurement error diverges at a rate that is an order faster than that of a conventional inertial system equipped with gyroscopes. In this paper, a redundant accelerometer-aided gyroscope-free IMU is designed to achieve a stable and bounded system. In this system, a three-axis accelerometer is used in addition to a set of six accelerometers that is typical in a conventional gyroscope-free IMU. The linear error dynamics of this aided gyroscope-free IMU is derived, and the effects of accelerometer errors are analyzed.

Integration of DGPS with a Low Cost MEMS - Based Inertial Measurement Unit (IMU) for Land Vehicle Navigation Application

Abstract: This paper focuses on evaluating the feasibility of using a low cost Micro Electro Mechanical System (MEMS) – based Inertial Measurement Unit (IMU) integrated with Differential Global Positioning System (DGPS), for land vehicle navigation. The main focus is on position accuracy analysis using a closed loop decentralized GPS/INS integration scheme. A Kalman filter is proposed for the IMU which models sensor scale factors and turn on biases. A performance comparative analysis of the MEMS Crista IMU with a tactical grade HG1700 IMU is presented. GPS outages are simulated in a clean data set collected in open sky conditions, by artificially omitting satellites during post-processing in order to asses the stand-alone performance of each IMU. Two different methods are investigated to prevent the errors from accumulating in the Inertial Navigation System (INS) in the absence of GPS. One is to use the constrained motion attributes of a land vehicle to bound the drift in the INS solution. This method is suitable for use in real-time applications. Another method is specifically a post processing scheme which involves the use of a Rauch Tung Streibel (RTS) smoother. Simultaneous field testing using DGPS and MEMS, tactical, and navigation-grade IMUs was conducted to allow for a direct comparison of their relative performance. The results show that in open sky conditions with MEMS IMU measurements and a pseudorange/Doppler derived DGPS solution, a positional accuracy better than 38 cm can be achieved. The use of vehicle movement constraints during GPS outages can prevent errors from accumulating, and can provide the improvement of up-to 80% in the position domain, whereas the corresponding improvements using the RTS smoother are about 99%.

The Silicon Oscillating Accelerometer: A High-Performance MEMS Accelerometer for Precision Navigation and Strategic Guidance Applications

Abstract: "The intercontinental ballistic missile (ICBM) and submarine-launched strategic missiles developed over the past 50 years have employed successive generations of increasingly accurate inertial guidance systems. The comparatively short time of guided flight and high acceleration levels characteristic of the ballistic missile application place a premium on accelerometer performance to achieve desired weapon system accuracy. Currently, the U.S. strategic missile arsenal relies on variants of the pendulous integrating gyro accelerometer (PIGA) to meet the high-performance, radiation-hard requirements of the weapon system. Likewise, precision navigation systems, such as the currently deployed SSBN Ship Inertial Navigation Systems (SINS), employ highly specialized and complex electromechanical instruments that, like the PIGA, present a system life-cycle cost and maintenance challenge. The PIGA and the Electromagnetic Accelerometer (EMA) demonstrate unsurpassed performance, however, their life-cycle cost has motivated a search for a highperformance, solid-state, strategic accelerometer. The Draper Laboratory is currently in the process of developing the Silicon Oscillating Accelerometer (SOA), a MEMS-based sensor that has demonstrated in laboratory testing the part-per-million (ppm)/µg scalefactor and bias performance stability required of precision guidance navigation applications. The ICBM and SSBN applications have significantly different environmental, acceleration dynamic range, and resolution requirements that are best satisfied by optimizing the SOA geometry for each application. The design flexibility and wafer-scale fabrication methods of the silicon MEMS process enable manufacturing both instrument designs with essentially zero incremental cost associated with the additional instrument assembly line. That is, the SOAs developed for the ICBM guidance and SSBN navigation applications share a common sensor package, electronics architecture, main housing and instrument assembly process. This paper will give an overview of the Draper SOA and compare and contrast performance data taken to date on both versions of the SOA."

RIC (robust internal-loop compensator) based flight control of a quad-rotor type UAV

Abstract: A QRT (quad-rotor type) hovering robot system is developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV (unmanned aerial vehicle) is equipped with four propellers driven by each electric motor, an embedded controller, an INS (inertial navigation system) using three rate gyros and accelerometers, a CCD (charge coupled device) camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. The developed hovering robot shows stable flying performances under the adoption of RIC (robust internal-loop compensator) based disturbance compensation and the vision based localization method. Although a model is incorrect, RIC method can design a controller by regarding the inaccurate part of the model and sensor noises as disturbances. The UAV can also avoid obstacles using eight IRs (infrareds) and four ultrasonic range sensors. This kind of micro UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment.

GPS/INS uses low-cost MEMS IMU

Abstract: A description of the design, operation, and test results of a miniature, low-cost, integrated GPS/inertial navigation system that uses commercial off-the-shelf micro-electro-mechanical system (MEMS) accelerometers and gyroscopes. The MEMS inertial measurement unit (EMU) is packaged in a small size and provides the raw EMU data through a serial interface to a processor board where the inertial navigation solution and integrated GPS/inertial Kalman filter is generated. The GPS/inertial software integration is performed using NAVSYS' modular InterNav software product. This allows integration with different low-cost GPS chip sets or receivers and also allows the integrated GPS/inertial navigation solution to be embedded as an application on a customer's host computer. This modular object-oriented architecture facilitates integration of the miniature MEMS GPS/INS navigation system for embedded navigation applications and is designed to handle the large errors characteristic of a low-grade MEMS IMU. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system. Data is provided showing the position, velocity, and attitude accuracy when operating with GPS aiding and also for periods where GPS dropouts occur and alternative navigation update sources are used to bound the MEMS inertial navigation error growth.

In use parameter estimation of inertial sensors by detecting multilevel quasi-static states

Abstract: We present an autoadaptive algorithm for in-use parameter estimation of MEMS inertial accelerometers and gyros using multi-level quasi-static states for greater accuracy and reliability. Multi-level quasi-static states are detected robustly using data from both gyros and accelerometers. Proper estimation of time-varying sensor parameters allows us to develop a mixed-reality real-time hand-held orientation tracker with dynamic accuracy of less than 20. Existing methods like Kalman filters do not take time-varying nature of parameters into account, instead modelling the time-variation as higher values in noise covariance matrices; thus underestimating the sensor capabilities.