Showing papers on "Inertial measurement unit published in 2006"

Advanced integration of WIFI and inertial navigation systems for indoor mobile positioning

Abstract: This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.

Miniaturized inertial measurement unit and associated methods

Abstract: A self-contained, integrated micro-cube-sized inertial measurement unit is provided wherein accuracy is achieved through the use of specifically oriented sensors, the orientation serving to substantially cancel noise and other first-order effects, and the use of a noise-reducing algorithm such as wavelet cascade denoising and an error correcting algorithm such as a Kalman filter embedded in a digital signal processor device. In a particular embodiment, a pair of three sets of angle rate sensors are orientable triaxially in opposite directions, wherein each set is mounted on a different sector of a base orientable normal to the other two and comprising N gyroscopes oriented at 360/N-degree increments, where N ≥ 2. At least one accelerometer is included to provide triaxial data. Signals are output from the angle rate sensors and accelerometer for calculating a change in attitude, position, angular rate, acceleration, and/or velocity of the unit.

Motion tracking system

Abstract: A motion tracking system for tracking an object composed of object parts in a three-dimensional space. The system comprises a number of magnetic field transmitters; a number of field receivers for receiving the magnetic fields of the field transmitters; a number of inertial measurement units for recording a linear acceleration; a number of angular velocity transducers for recording angular velocities. The system further comprises a processor for controlling the transmitters and receiving signals coming from the field receivers and the inertial measurement unit; which processor contains a module for deriving orientation and/or position information of the constituent object parts of the object on the basis of the received signals. The processor is configured for intermittently controlling the transmitters transmit at a predetermined frequency, wherein the position and/or orientation information is derived by periodically calibrating the motion information coming from the inertial measurement unit with the motion information coming from the magnetic field receivers.

Calibration of a MEMS inertial measurement unit

Abstract: An approach for calibrating a low-cost IMU isstudied, requiring no mechanical platform for the accelerometercalibration and only a simple rotating table for the gyrocalibration. The proposed calibr ...

Integrated GPS/INS System for Pedestrian Navigation in a Signal Degraded Environment

Abstract: This paper evaluates the performance of a shoe/foot mounted inertial system for pedestrian navigation application. Two different grades of inertial sensors are used, namely a medium cost tactical grade Honeywell HG1700 inertial measurement unit (IMU) and a low-cost MEMS-based Crista IMU (Cloud Cap Technology). The inertial sensors are used in two different ways for computing the navigation solution. The first method is a conventional integration algorithm where IMU measurements are processed through a set of mechanization equation to compute a six degree-offreedom (DOF) navigation solution. Such a system is referred to as an Inertial Navigation System (INS). The integration of this system with GPS is performed using a tightly coupled integration scheme. Since the sensor is placed on the foot, the designed integrated system exploits the small period for which foot comes to rest at each step (stance-phase of the gait cycle) and uses Zero Velocity Update (ZUPT) to keep the INS errors bounded in the absence of GPS. An algorithm for detecting the stance-phase using the pattern of three-dimensional acceleration is discussed. In the second method, the navigation solutions is computed using the fact that a pedestrian takes one step at a time, and thus positions can be computed by propagating the step-length in the direction of pedestrian motion. This algorithm is termed as pedestrian dead-reckoning (PDR) algorithm. The IMU measurement in this algorithm is used to detect the step, estimate the step-length, and determine the heading for solution propagation. Different algorithms for stridelength estimation and step-detection are discussed in this paper. The PDR system is also integrated with GPS through a tightly coupled integration scheme. The performance of both the systems is evaluated through field tests conducted in challenging GPS environments using both inertial sensors. The specific focus is on the system performance under long GPS outages of duration upto 30 minutes.

Performance evaluation of low cost MEMS-based IMU integrated with GPS for land vehicle navigation application

Abstract: ............................................................................................................................................... III ACKNOWLEDGEMENTS.........................................................................................................................V DEDICATION............................................................................................................................................ VI TABLE OF CONTENTS..........................................................................................................................VII LIST OF TABLES ..................................................................................................................................... XI LIST OF FIGURES ................................................................................................................................ XIII LIST OF SYMBOLS............................................................................................................................... XVI LIST OF ABBREVIATIONS................................................................................................................. XIX CHAPTER ONE : INTRODUCTION.........................................................................................................1 1.1 BACKGROUND .......................................................................................................................................1 1.2 LOW COST INERTIAL SENSORS ..............................................................................................................5 1.2.1 MEMS Inertial Sensors .................................................................................................................5 1.2.2 Performance Characteristics ........................................................................................................6 1.3 PREVIOUS RESEARCH AND THEIR LIMITATIONS.....................................................................................8 1.3.1 Integration Strategy ......................................................................................................................8 1.3.2 Initial Alignment .........................................................................................................................10 1.3.3 Sensor Error Calibration/Modeling............................................................................................11 1.3.4 Rapid Degradation in Solution during GPS Outage...................................................................13 1.3.5 Operational Environment ...........................................................................................................16 1.4 OBJECTIVES.........................................................................................................................................17 1.5 RESEARCH METHODOLOGY SUMMARY ...............................................................................................19

Sensor data fusion for body state estimation in a hexapod robot with dynamical gaits

Abstract: We report on a hybrid 12-dimensional full body state estimator for a hexapod robot executing a jogging gait in steady state on level terrain with regularly alternating ground contact and aerial phases of motion. We use a repeating sequence of continuous time dynamical models that are switched in and out of an extended Kalman filter to fuse measurements from a novel leg pose sensor and inertial sensors. Our inertial measurement unit supplements the traditionally paired three-axis rate gyro and three-axis accelerometer with a set of three additional three-axis accelerometer suites, thereby providing additional angular acceleration measurement, avoiding the need for localization of the accelerometer at the center of mass on the robot's body, and simplifying installation and calibration. We implement this estimation procedure offline, using data extracted from numerous repeated runs of the hexapod robot RHex (bearing the appropriate sensor suite) and evaluate its performance with reference to a visual ground-truth measurement system, comparing as well the relative performance of different fusion approaches implemented via different model sequences

Sensemble: a wireless, compact, multi-user sensor system for interactive dance

Abstract: We describe the design of a system of compact, wireless sensor modules meant to capture expressive motion when worn at the wrists and ankles of a dancer. The sensors form a high-speed RF network geared toward real-time data acquisition from multiple devices simultaneously, enabling a small dance ensemble to become a collective interface for music control. Each sensor node includes a 6-axis inertial measurement unit (IMU) comprised of three orthogonal gyroscopes and accelerometers in order to capture local dynamics, as well as a capacitive sensor to measure close range node-to-node proximity. The nodes may also be augmented with other digital or analog sensors. This paper describes application goals, presents the prototype hardware design, introduces concepts for feature extraction and interpretation, and discusses early test results.

Fusion of Imaging and Inertial Sensors for Navigation

Abstract: : The motivation of this research is to address the limitations of satellite-based navigation by fusing imaging and inertial systems. The research begins by rigorously describing the imaging and navigation problem and developing practical models of the sensors, then presenting a transformation technique to detect features within an image. Given a set of features, a statistical feature projection technique is developed which utilizes inertial measurements to predict vectors in the feature space between images. This coupling of the imaging and inertial sensors at a deep level is then used to aid the statistical feature matching function. The feature matches and inertial measurements are then used to estimate the navigation trajectory using an extended Kalman filter. After accomplishing a proper calibration, the image-aided inertial navigation algorithm is then tested using a combination of simulation and ground tests using both tactical and consumer- grade inertial sensors. While limitations of the Kalman filter are identified, the experimental results demonstrate a navigation performance improvement of at least two orders of magnitude over the respective inertial-only solutions.

Robust positioning technique in low-cost DR/GPS for land navigation

Abstract: This paper describes a dead-reckoning (DR) construction for land navigation and sigma-point-based receding-horizon Kalman finite-impulse response (SPRHKF) filter for DR/GPS integration system. A simple DR construction is adopted to improve the performance of both pure land DR navigation and DR/GPS integration system. In order to overcome the flaws of the extended Kalman filter (EKF), the sigma-point KF (SPKF) is merged with the receding-horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can occur in the microelectromechanical systems' inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS integration system for land navigation seamlessly

Precision free-inertial navigation with gravity compensation by an onboard gradiometer

Abstract: Precise inertial navigation depends on external aiding to remove various systematic errors in the sensed accelerations and rotations that cause an accumulation of position error up to many hundreds of meters per hour. Technological developments in inertial sensors are underway to eliminate this dependence at the level of a few meters uncertainty over one hour of unaided inertial navigation. However, no matter how precise the inertial measurement units are, the systematic effect of unknown gravitation can cause navigation errors up to several hundred meters per hour. Compensation for this effect can take several forms, but always requires updates or information from systems external to the inertial navigator. This report analyzes the unique capabilities provided by an onboard integrated gravity gradiometer that senses the gravitational gradients, thus enabling in situ compensation. Particular attention is given to the coupling of observed gradients with angular rates and accelerations. It is shown that errors from conventional precision gyros negate the effect of gradiometer aiding on the cross-track position error if only the essential gradients are measured [accuracy of 0.1 Eotvos (E)]. With additional measurements of appropriate symmetric gradient components, both along-track and cross-track errors caused by gravitation can be controlled at the 5-m level after one hour of free-inertial navigation.

Arrangement for and method of two dimensional and three dimensional precision location and orientation determination

Abstract: In one embodiment of the present invention, a method of and apparatus for determining inaccurate GPS samples in a set of GPS samples is disclosed, according to the following actions: a) obtaining GPS samples as taken by a global positioning system on board a vehicle when traveling along a trajectory; b) obtaining a first estimation of the trajectory based on the GPS samples; c) obtaining a second estimation of the trajectory at least based on measurements made by an inertial measurement unit on board vehicle when traveling along the trajectory; d) comparing the first and second estimations; e) establishing locations where the first estimation shows a variation compared with the second estimation above a predetermined threshold; f) if no such locations can be established continue with action j), otherwise continue with action g); g) removing GPS samples associated with the locations of high variation as being inaccurate GPS samples, thus forming a set of remaining GPS samples; h) calculating the first estimation anew of the trajectory based on the remaining GPS samples and calculating the second estimation anew; i) repeating actions d) to h); j) ending the actions.

Experimental study on the estimation of lever arm in GPS/INS

Abstract: Lever-arm uncertainty can be an important error source in the integration of the Global Positioning System (GPS) and inertial navigation system (INS). This paper presents both numerical and experimental studies on the estimation of the lever arm in the integration of a very-low-grade inertial measurement unit (IMU) with an accurate single-antenna GPS measurement system. Covariance simulation results showed that maneuvers play an important role on the estimation of the lever arm and attitude. The length of the lever arm has a rather insignificant effect on the estimation of these. Experimental tests conducted with a low-cost microelectromechanical system (MEMS) IMU and a carrier-phase differential GPS (CDGPS) measurement system showed that the lever arm can be estimated with centimeter-level accuracy. The test results confirmed that angular motions and horizontal accelerations improve the estimates of the lever arm and yaw angle, respectively.

Sensor Fusion for Augmented Reality

Abstract: In Augmented Reality (AR), the position and orientation of the camera have to be estimated with high accuracy and low latency. This nonlinear estimation problem is studied in the present paper. The proposed solution makes use of measurements from inertial sensors and computer vision. These measurements are fused using a Kalman filtering framework, incorporating a rather detailed model for the dynamics of the camera. Experiments show that the resulting filter provides good estimates of the camera motion, even during fast movements.

Design and implementation of an inertial measurement unit for control of artificial limbs: Application on leg orthoses

Abstract: This paper presents the design and implementation of a cost-effective and small inertial measurement unit (IMU) for application on leg smart orthotics and prosthetics IMU design based on biomechanical considerations for lower leg devices is presented Methods for calculation of a number of biomechanical parameters related to gait based on the unit are discussed, including calibration and offset correction procedures An approach for electronic knee joint control of orthosis during cyclic walking based on IMU signals is discussed Finally, experiments are conducted for a subject walking on a flat surface wearing a mechanically driven orthosis with the proposed sensor Experimental results demonstrate the IMU suitability and feasibility for real-time embedded control of wearable assistive devices for walking restoration and monitoring

Analysis of an Ultra-Tightly Coupled GPS/INS System in Jamming

Abstract: The performance of an Ultra-Tightly Coupled (UTC) Global Positioning System/Inertial Navigation System (GPS/INS) is evaluated using a system simulation of the GPS receiver and navigation processing. The UTC system being analyzed uses a bank of pre-filters to estimate code delay error and Doppler frequency error for each satellite. These outputs are sent to a central Kalman navigation filter. This central processor generates estimates of inertial navigation position, velocity, and attitude errors; IMU biases; and user clock errors, which are used to correct the navigation solution. In the UTC approach, outputs from the central navigation processor, after projection into satellite line-of-sight coordinates, are used to control the code and carrier replica signals for each satellite channel. In contrast, a conventional tightly coupled GPS/INS system uses separate tracking loops for each satellite channel, which operate autonomously. As a result, the UTC design is considered more robust to jamming and vehicle dynamics. Closed-loop UTC navigation performance is evaluated over a realistic precision guided munition (PGM) scenario in the presence of broadband jamming directed against the GPS system. A realistic IMU error model is assumed, and UTC performance is evaluated over a range of jamming levels. Some preliminary conclusions are then formed about the effectiveness of the UTC approach.

Statistical Fault Detection with Applications to IMU Disturbances

Abstract: This thesis deals with the problem of detecting faults in an environment where the measurements are affected by additive noise. To do this, a residual sensitive to faults is derived and statistical methods are used to distinguish faults from noise. Standard methods for fault detection compare a batch of data with a model of the system using the generalized likelihood ratio. Careful treatment of the initial state of the model is quite important, in particular for short batch sizes. One method to handle this is the parity-space method which solves the problem by removing the influence of the initial state using a projection. In this thesis, the case where prior knowledge about the initial state is available is treated. This can be obtained for example from a Kalman filter. Combining the prior estimate with a minimum variance estimate from the data batch results in a smoothed estimate. The influence of the estimated initial state is then removed. It is also shown that removing the influence of the initial state by an estimate from the data batch will result in the parity-space method. To model slowly changing faults, an efficient parameterization using Chebyshev polynomials is given. The methods described above have been applied to an Inertial Measurement Unit, IMU. The IMU usually consists of accelerometers and gyroscopes, but has in this work been extended with a magnetometer. Traditionally, the IMU has been used to estimate position and orientation of airplanes, missiles etc. Recently, the size and cost has decreased making it possible to use IMU:s for applications such as augmented reality and body motion analysis. Since a magnetometer is very sensitive to disturbances from metal, such disturbances have to be detected. Detection of the disturbances makes compensation possible. Another topic covered is the fundamental question of observability for fault inputs. Given a fixed or linearly growing fault, conditions for observability are given. The measurements from the IMU show that the noise distribution of the sensors can be well approximated with white Gaussian noise. This gives good correspondence between practical and theoretical results when the sensor is kept at rest. The disturbances for the IMU can be approximated using smooth functions with respect to time. Low rank parameterizations can therefore be used to describe the disturbances. The results show that the use of smoothing to obtain the initial state estimate and parameterization of the disturbances improves the detection performance drastically.

A coupled estimation and control analysis for attitude stabilisation of mini aerial vehicles

Abstract: Commercially viable aerial robotic vehicles require robust and efficient, but low-cost attitude (vehicle orientation) stabilisation systems. A typical attitude stabilisation system employs a low-cost IMU and consists of an attitude estimator as well as an attitude controller. This paper proposes a coupled non-linear attitude estimation and control design for the attitude stabilisation of low-cost aerial robotic vehicles. Attitude estimation is based on a non-linear complementary filter expressed on the rotation group. The attitude control algorithm is based on a non-linear control Lyapunov function analysis derived directly in terms of the rigid-body attitude dynamics. The interaction terms are bounded in terms of estimation and control errors and the full coupled system is shown to be (almost) globally stable.

INS-Assisted High Sensitivity GPS Receivers For Degraded Signal Navigation

Abstract: This paper proposes a novel architecture for ultra-tight integration of a High Sensitivity Global Positioning System (HSGPS) receiver with an Inertial Navigation System (INS), to address the issue of GPS tracking and positioning in degraded signal environments By enhancing signal tracking loops in receivers through the use of optimal controllers/estimators and aiding from external source such as INS, the capabilities of the GPS receiver can be enhanced to provide the positioning in indoor and urban canyon environments The proposed approach is distinct from the commonly used ultra-tightly coupled GPS/INS approaches, and absorbs different tracking enhancement technologies used in typical HSGPS receivers, multi-channel co-operated GPS receivers and the current ultra-tightly coupled GPS/INS methods The method consists of three loops in signal tracking: sophisticated conventional Delay Lock Loops (DLL) and Phase Lock Loops (PLL) in all individual signal tracking channels, external INS aiding loop and multi-channel cooperated tracking loop, namely CO-OP loop The signal tracking strategy is described, with specific focus on the discussion of the role of CO-OP loop in the developed ultra-tightly coupled GPS/INS Furthermore, the effect of inertial measurement unit (IMU) quality and the effect of receiver oscillator noise and coherent integration time on weak signal tracking are also analyzed in this paper To perform ultra-tight integration, an INS simulator is developed, and static and dynamic field tests were simulated to analyze the system performance The test results show that, the designed INS-aided GPS receiver can track the incoming weak GPS signals down to 15 dBHz without carrier phase locked, or 25 dB-Hz with carrier phase locked When there are multiple strong GPS signals in view, the other weak signals can be tracked down to 15 dB-Hz with carrier phase locked

Inertial measurement unit using rotatable MEMS sensors

Abstract: A MEM inertial sensor (e.g. accelerometer, gyroscope) having integral rotational means for providing static and dynamic bias compensation is disclosed. A bias compensated MEM inertial sensor is described comprising a MEM inertial sense element disposed on a rotatable MEM stage. A MEM actuator drives the rotation of the stage between at least two predetermined rotational positions. Measuring and comparing the output of the MEM inertial sensor in the at least two rotational positions allows for both static and dynamic bias compensation in inertial calculations based on the sensor's output. An inertial measurement unit (IMU) comprising a plurality of independently rotatable MEM inertial sensors and methods for making bias compensated inertial measurements are disclosed.

Control Laws For The Tele Operation Of An Unmanned Aerial Vehicle Known As An X4-flyer

Abstract: In this paper, we present a control design for the tele-operation of a miniature unmanned aerial vehicle known as an X4-flyer. A simple dynamic nonlinear model for the vehicle, valid for quasi-stationary flight conditions, is derived as a basis for the control design. An attitude control based on information issued from an Inertial Measurement Unit is designed. In order to control the vehicle altitude, an adaptive controller avoiding the ground effects and based on measurements issued from an ultrasonic low cost sensor is designed. In order to compute the altitude velocity, an estimator based on the proposed modelling is used. At the end of the paper, experimental results are presented.

Time-Differenced Carrier Phase Measurements for Tightly Coupled GPS/INS Integration

Abstract: A tightly coupled GPS/INS system is characterized by the fact that pseudorange and deltarange measurements are processed in the navigation filter in order to estimate the errors of the inertial navigation solution and to calibrate the inertial measurement unit. In this paper, the usage of time differenced carrier phase measurements instead of the delta range measurements is proposed. Usually, DGPS corrections are required in order to exploit the high accuracy of the carrier phase measurements by removing the common mode errors like ionospheric errors, ephemeris errors, or satellite clock errors. Then, techniques like carrier aided smoothing or ambiguity fixing can be applied. With the approach described in this paper, DGPS corrections are not required. Additionally, a fixing of the integer ambiguities, which is especially difficult when a single frequency receiver is used, is not required either. Forming time differences of successive carrier phase measurements, the constant integer ambiguities and most of the slowly varying common mode errors are removed. These carrier phase differences do not allow for an absolute centimeter-level positioning as it can be achieved with a DGPS base station and an ambiguity fixing, but the noise in the position information is reduced and the accuracy of the velocity and attitude estimates are improved. Details of this approach are clarified and the processing of this type of measurement in the navigation filter is addressed. The improvement in performance is illustrated via hardware-in-the-loop test results and the analysis of flight test data collected with a micro aerial vehicle.

System and method for determining aircraft hard landing events from inertial and aircraft reference frame data

Abstract: This invention allows for the precise determination of an aircraft's landing conditions and whether an aircraft has experienced a hard landing that exceeds the allowable design loads of the aircraft's landing gear. The system comprises a computer that measures signals from an inertial measurement unit (IMU) at high data rates (e.g. 100 Hz) and also records signals from the aircraft avionics data bus. The computer compares the output from the inertial measurement unit's accelerometers against at least one predetermined threshold parameter to determine whether the aircraft's three dimensional landing deceleration is safely within the design allowances or other regulatory limitations, or whether the landing event needs further investigation.

A Prototype Personal Navigation System

Abstract: Honeywell Laboratories recently funded the dev- elopment of a prototype personal navigation system based on MEMS technologies. The system components include an MEMS inertial measurement unit, a three-axis magnetometer, a baro- metric pressure sensor, and a SAASM GPS receiver. The system also uses Honeywell's human motion-based pedometry algo- rithm. The navigation process is based on a strap-down inertial navigator aided by feedback from a Kalman filter using typical measurements from the GPS, magnetometer and barometer when available. A key innovation is the addition of an inde- pendent measurement of distance traveled based on use of a human motion algorithm. The navigation system combines the best features of dead reckoning and inertial navigation, resulting in positioning performance exceeding that achieved with either method alone. Subsequent to the Honeywell effort, DARPA funded an individual Personal Inertial Navigation System (iPINS) seedling program. Honeywell worked to improve the baseline personal navigation system with the objective of demonstrating the feasibility of reliably achieving navigation accuracy < 1% of distance traveled in GPS-denied scenarios. In addition, an analysis was conducted to determine the benefit of incorporating terrain correlation into the personal navigation system. The results of this analysis indicate that overall navigation accuracy can be significantly improved through the application of terrain correlation. This paper presents an overview of Honeywell Laboratories' prototype Personal Navigation system, the software architecture, and the personal navigation algorithms. Demonstration results from the DARPA iPINS seedling program are presented. In addition, the paper includes the conclusions from the terrain correlation analysis conducted under the iPINS seedling program.

A low-cost attitude heading reference system by combination of GPS and magnetometers and MEMS inertial sensors for mobile applications

Abstract: This paper describes a prototype system for attitude and heading determination. A L1-only GPS receiver is integrated with microelectromechanical gyroscopes, accelerometers and magnetometers. In contrast to a multi-antenna/multi-receiver GPS attitude determination system, this system uses a single antenna/single receiver configuration to derive standalone velocity and acceleration solutions from the GPS L1 carrier phase measurements. No reference station is needed to form differences of carrier phase measurements for the velocity and acceleration calculation. The GPSderived acceleration is further used in the attitude determination by combination with the three-dimension acceleration sensed by the accelerometers. The magnetometers sense the Earth’s magnetic field intensity, and can give the heading estimation regardless of the status of the host platform. To satisfy real-time applications, infinite impulse response differentiators instead of finite impulse response differentiators are used to derive the acceleration from GPS. The algorithms have been implemented and their efficiency demonstrated by experiments.

Non-GPS Navigation for Emergency Responders

Abstract: - This paper introduces a novel navigation system for walking persons The system is of particular benefit for emergency responders, who often have to enter and move around in large structures where GPS is unavailable We refer to our system as “Personal Odometry System” (POS) The POS measures the position of a walking person relative to a known starting position, such as the entrance to a building This is accomplished by instrumenting one boot of the subject with a 3-axis gyroscope and a 3-axis accelerometer (collectively called “inertial measurement unit” – IMU) This paper describes the POS hardware and explains the basics of our approach The paper also presents extensive experimental results, which illustrate the utility and practicality of our system I I NTRODUCTION This paper describes our Personal Odometry System (POS) for measuring and tracking the momentary location and trajectory of a walking person, even if GPS is not available We believe that such a system might be of particular value for emergency responders For example, fire fighters entering a burning building are at risk to be injured and unable to report their position With the POS reporting the user’s position to a central command post, each emergency responder’s location could be tracked in real-time Another application involves the “clearing” of a large building by emergency or security personnel Their challenge often is to keep track of rooms already cleared and areas that were not cleared, yet Our system’s ability to track each person’s location provides a useful solution for this problem Our proposed POS does not require GPS This is an important distinction, since GPS is not available indoors Furthermore, GPS is unreliable under dense foliage, in so-called “urban canyons,” and generally in any environment, in which a clear view of a good part of the sky is not available There are some approaches to personal position estimation without GPS Typically, these systems require external references, also called “fiducials,” such as preinstalled active beacons, receivers, or optical retroreflectors Common to all fiducial-based position estimation systems is that the fiducials must be installed in the work space at precisely surveyed locations before the system can be used This installation is time consuming and expensive, and in case of emergency response completely unfeasible Fiducial-based systems also require an active radiation source, such as infrared light [1], ultrasound [2], or magnetic fields [3], which may be undesirable in security-related applications Generally, fiducial-based systems perform well and are able to provide absolute position and orientation in real-time If the application permits the installation of fiducials ahead of time, then these systems have the significant advantage that errors don’t grow with time, as is the case in our POS Another way of implementing absolute position estimation is computer vision ([4] and [5]) Images are compared and matched against a pre-compiled database Computer vision has the advantage that the environment does not need to be modified, but the approach requires potentially very large databases Work is also being done on so-called Simultaneous Location and Mapping (SLAM) methods, which don’t require a precompiled database However, SLAM systems are not as reliable, may accrue errors over time and distance, and poor visibility and unfavorable light conditions can result in completely false position estimation [6][7] The scientific literature offers only very few approaches that do not require external references The simplest one of them is the pedometer, that is, a device that counts steps Pedometers must be calibrated for the stride length of the user and they produce large errors when the user moves in any other way than his or her normal walking pattern One commercially available personal navigation system based on this principle is the Dead Reckoning Module (DRM) by PointResearch [8] It uses accelerometers to identify steps, and linear displacement is computed assuming that the step size is constant Orientation is measured using a digital compass, which is combined with the traveled distance (step counts) to estimate 2-D position The performance of this system depends on the accuracy of determining the stride

Integration of a GPS aided Strapdown Inertial Navigation System for Land Vehicles

Abstract: The estimation accuracy of a low-cost inertial navigation system (INS) is limited by the accuracy of the used sensors and the imperfect mathematical modeling of the error sources. By fusing the INS data with GPS data, the errors can be bounded and the accuracy increases considerably. In this project, a low-cost in-house constructed inertial measurement unit (IMU) and an off-the-shelf GPS receiver are used for the data acquisition. The measurements are integrated with a loosely coupled GPS aided INS approach. For the assessment of the results, one data set with real data obtained from a field test is available. The tuning of the covariance matrices is a delicate adjustment and does not always provide convergence. Values for acceptable results could be found and two implementations of inertial navigation systems are compared. The use of nonholonomic constraints showed a dramatic increase in the accuracy. An analysis of the importance and influence of different IMU sensor errors provides a foundation for the modeling and inclusion of further error states in the extended Kalman filter.