Strapdown Inertial Measurement Unit Research Articles

Kinematic Modeling and Analysis of Skid-Steered Mobile Robots With Applications to Low-Cost Inertial-Measurement-Unit-Based Motion Estimation

Skid-steered mobile robots are widely used because of their simple mechanism and high reliability. Understanding the kinematics and dynamics of such a robotic platform is, however, challenging due to the complex wheel/ground interactions and kinematic constraints. In this paper, we develop a kinematic modeling scheme to analyze the skid-steered mobile robot. Based on the analysis of the kinematics of the skid-steered mobile robot, we reveal the underlying geometric and kinematic relationships between the wheel slips and locations of the instantaneous rotation centers. As an application example, we also present how to utilize the modeling and analysis for robot positioning and wheel slip estimation using only low-cost strapdown inertial measurement units. The robot positioning and wheel slip-estimation scheme is based on an extended Kalman filter (EKF) design that incorporates the kinematic constraints for accuracy enhancement. The performance of the EKF-based positioning and wheel slip-estimation scheme are also presented. The estimation methodology is tested and validated experimentally on a robotic test bed.

Astronavigation System as an Autonomous Enhancement Suite for a Strapdown Inertial Navigation System: An Evaluation

reliability. The foremost requirement for the solution of this problem is a strapdown inertial navigation system (SINS), which is autonomous, reliable and jamming resistant, but at the same time, errors in SINS increase with time. Therefore, for the SINS error correction, astronavigation system (ANS) is used as an additional navaid. This paper considers the ANS as an enhancement source for the SINS and presents its theoretical and practical aspects. The typical ANS makes use of star-trackers which are expensive, complicated in their structure and demand a-priori definition and vigilant preparation of each onboard attitude fix. To make this system cost effective and simple, an advanced configuration employs a charge coupled device (CCD) based star sensor rigidly mounted on a strapdown inertial measurement unit (SIMU). Consequently, in this evaluation, the ANS makes use of CCD based star sensors. Simulation results are presented to demonstrate the validity of the method for improving the navigation reliability and performance.

A consistent and robust Kalman filter design for in-motion alignment of inertial navigation system

The necessity recurrently comes up to align a strapdown inertial navigation system (SINS) in a moving vehicle to avoid a long run-up of the inertial system before a start or launch command is issued. This in-motion alignment is therefore achieved by integrating SINS data with some external aiding source such as the Global Positioning System (GPS) by using some form of measurement matching method. Consequently, this paper illustrates a reliable in-motion alignment scheme for a low-cost strapdown inertial measurement unit (SIMU) using a consistent and robust Kalman filter (RKF) structure. An error model of the SINS is derived and the state vector comprises attitude, velocity, position and sensor errors. Velocity information from the GPS with maneuvering is employed as a measurement to the filter. Experimentation results show that the proposed filter is less sensitive to impulsive noise and gives better estimates of the navigation parameters.

Strategic inertial navigation systems - high-accuracy inertially stabilized platforms for hostile environments

This article provides an overview of the technical challenges and solutions for ISP designers for strategic inertial navigation systems (INSs). The design descriptions herein are mostly generic, with occasional references to existing or past strategic systems. The article discusses four primary topics, namely, system design options, environments and mitigation techniques, preflight calibration and alignment (C&A) in-flight navigation mechanizations, and test and verification. IEEE standard terminology of inertial sensors and inertial systems is used throughout the article. The best-known application of ISPs is stabilization and control of payloads such as electro-optical sensors and laser beams. Perhaps less well known is that ISPs are used in a variety of aircraft and missile navigation systems. With the introduction of digital computers, the breadth of application of ISPs for navigation began to diminish, and strapdown INS became prevalent. This trend has accelerated with the navigation aiding of the global positioning system (GPS), which can render a strapdown inertial measurement unit (IMU) more accurate than the best ISPs. Today, only self-contained precision navigation systems use ISPs. Strategic navigation systems are among this small group.

Realization of Initial Alignment Algorithm for Strapdown Inertial Navigation System using Central Difference Filter

Abstract Alignment is the process whereby the orientation of the axes of an inertial navigation system is determined with respect to the reference system. In this paper, the initial alignment error equations of the strapdown inertial navigation system (SINS) with large initial azimuth error have been derived with inclusion of nonlinear characteristics. The second order central difference filter (CDF2) has been used for solution of the alignment problem. Simulations have been carried out to validate and corroborate the stationary alignment case employing a strapdown inertial measurement unit (SIMU). A performance comparison between the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the CDF demonstrate that the accuracy of attitude error estimation using the CDF2 is better than that of using the EKF or the UKF.

Feedforward ins aiding: an investigation of maneuvers for in-flight alignment

Navigation in autonomous vehicles involves integrating measurements from on-board inertial sensors and external data collected by various sensors. In this paper, the computer-frame velocity error model is augmented with a random constant model of accelerometer bias and rate-gyro drift for use in a Kalman filter-based fusion of a low-cost rotating inertial navigation system (INS) with external position and velocity measurements. The impact of model mismatch and maneuvers on the estimation of misalignment and inertial measurement unit (IMU) error is investigated. Previously, the literature focused on analyzing the stripped observability matrix that results from applying piece-wise constant acceleration segments to a stabilized, gimbaled INS to determine the accuracy of misalignment, accelerometer bias, and rate-gyro drift estimation. However, its validation via covariance analysis neglected model mismatch. Here, a vertically undamped, three channel INS with a rotating IMU with respect to the host vehicle is simulated. Such IMU rotation does not require the accurate mechanism of a gimbaled INS (GINS) and obviates the need to maneuver away from the desired trajectory during in-flight alignment (IFA) with a strapdown IMU. In comparison with a stationary GINS at a known location, IMU rotation enhances estimation of accelerometer bias, and partially improves estimation of rate-gyro drift and misalignment. Finally, combining IMU rotation with distinct acceleration segments yields full observability, thus significantly enhancing estimation of rate-gyro drift and misalignment.

Pseudo long base line navigation algorithm for underwater vehicles with inertial sensors and two acoustic range measurements

This paper presents an integrated navigational algorithm for unmanned underwater vehicles (UUV) using two acoustic range transducers and strap-down inertial measurement unit (SD-IMU). A range measurement model is derived for a UUV having one acoustic transducer and cruising around two reference transponders at sea floor or surface. The proposed algorithm, called pseudo long base line (PLBL), estimates the position of the vehicle integrating the SD-IMU signals corrected with the two range measurements. Extended Kalman filter was applied to propagate error covariance, to update measurement errors and to correct state equation whenever the external measurements are available. Simulations were conducted to illustrate the effectiveness of the PLBL using the 6-d.o.f. nonlinear numerical model of a UUV at current flow, excluding bottom-fixed DVL. This paper also shows the error convergence of the vehicle's initial position by the additional range measurements without velocity information.

An algorithm for astro-inertial navigation using CCD star sensors

A self-contained suite of astro-inertial navigation system is capable of autonomous mission and is operationally reliable. The typical astronavigation system (ANS) makes use of star-trackers, which are expensive and complex. To make the system cost effective and less complex, the star-tracker is replaced by a charge coupled device (CCD)-based star sensor, rigidly mounted on a strapdown inertial measurement unit (SIMU) of the system. This electro-optical star sensor is compact and easy to use with an ANS that utilizes efficient star identification techniques. This paper designs an algorithm that estimates axes misalignment angles of strapdown inertial navigation system (SINS) that makes stars' observations utilizing a CCD star sensor. Mathematical modeling of the suggested scheme was carried out and transformations between different frames were exercised. From the image projection geometry, stars' right ascensions and declinations, relative to the body frame, were estimated. Lastly, from the known stars' position vectors in mathematical platform and reference frames, axes misalignment matrix representing SINS attitude errors can be estimated employing the derived relationship.

Development of inspection gauge system for gas pipeline

An autonomous pipeline inspection gauge system has been developed for determining position, orientation, curvature, and deformations such as dents and wrinkles of operating pipelines by Korea Gas Company and Seoul National University. The most important part of several subsystems is the Strapdown Inertial Measurement Unit (SIMU), which is integrated with velocity and distance sensors, weld detection system, and digital recording device. The Geometry Pipeline Inspection Gauge (GeoPIG) is designed to operate continuously and autonomously for a week or longer in operating gas pipelines. In this paper, the design concepts, system integration, and data processing/analysis method for the PIG will be presented. Results from the recent experiment for a 58 kilometer gas pipeline will be discussed.

Operational Experience with Optimal Integration of Low-Cost Inertial Sensors and GPS for Flight Test Requirements

This paper describes the development of, and operational flight test experience with, a real-time integrated navigation system that is based on a low-cost strapdown Inertial Measurement Unit (IMU) ...

Calibration of Measurement Delay in Global Positioning System/Strapdown Inertial Navigation System

The effect of a constant transmission delay that occurs in delivering measurements from a global positioning system receiver to a Kalman Ž lter for an aided strapdown inertial navigation is analyzed. Steady-state conditions under the measurement delay are derived based on measurement residual observation. A new error model for circular trajectories is derived to show that the currently computed navigation variables converge not to the current true variables but to the neighborhood of the past true variables at the instant the delayed measurements were actually sampled. Based on the steady-state conditions and the new error model, causes and effects of an erroneously large estimation error of forward accelerometer bias are presented. To eliminate the undesirable delay effects given any combination of a global positioning system receiver and a strapdown inertial measurement unit, a simple delay calibration algorithm is proposed. The proposed algorithm is based on the characteristics that the heading error is biased by a controlled vehicle maneuver and advantageouslyrequires no modiŽ cation in onboard hardware.

Calibration of Time Synchronization Error in GPS/SDINS Hybrid Navigation

In this study, we analyzed the effect of a constant transmission delay that occurs in delivering measurements from a global positioning system receiver to a Kalman filter for an aided strapdown inertial navigation system and propose an efficient delay calibration algorithm. A new error model for the circular trajectories is derived to show that all the currently computed navigation variables converge not to the current true variables but to the neighborhood of the past true variables at the instant the delayed measurements were actually sampled. In order to eliminate the undesirable delay effects given various combinations of receivers and strapdown inertial measurement units, a simple delay calibration algorithm is proposed. The proposed algorithm is enabled by the vehicle's controlled maneuver, and advantageously requires no modification in onboard hardware.

Parity Vector Compensation for Fault Diagnosis of Inertial Sensor Unit

A scheme based on neural network is presented to improve the fault detection and isolation (FDI) performance of a skewed redundant strapdown inertial measurement unit. The neural network is trained to eliminate the effects of input axis misalignment, scale factor errors and biases on parity vector. One advantage of the proposed technique over other compensation algorithm based on Kalman filter or bias separated estimation is that it does not require dynamic equation of error states and statistics of noise. The simulation results show that the proposed method can significantly improve the FDI performance of the skewed inertial sensor sets.

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

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

Testing and evaluation of an integrated GPS/INS system for small AUV navigation

A Small Autonomous Underwater Vehicle Navigation System (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated Global Positioning System/Inertial Navigation System (GPS/INS) navigation system composed of low-cost and small-size components. It is designed to demonstrate the feasibility of using a low-cost strap-down inertial measurement unit (IMU) to navigate between intermittent GPS fixes. The present hardware consists of a GPS/DGPS receiver, IMU, compass, water speed sensor, water depth sensor, and a data processing computer. The software is based on a 12-state complementary filter that combines measurement data from all sensors to derive a vehicle position/orientation estimate. This paper describes hardware and software design and testing results of the SANS. It is shown that results from tilt table testing and bench testing provide an effective means for tuning filter gains. Ground vehicle testing verifies the overall functioning of the SANS and exhibits an encouraging degree of accuracy.

A high integrity IMU/GPS navigation loop for autonomous land vehicle applications

This paper describes the development and implementation of a high integrity navigation system, based on the combined use of the Global Positioning System (GPS) and an inertial measurement unit (IMU), for autonomous land vehicle applications. The paper focuses on the issue of achieving the integrity required of the navigation loop for use in autonomous systems. The paper highlights the detection of possible faults both before and during the fusion process in order to enhance the integrity of the navigation loop. The implementation of this fault detection methodology considers both low frequency faults in the IMU caused by bias in the sensor readings and the misalignment of the unit, and high frequency faults from the GPS receiver caused by multipath errors. The implementation, based on a low-cost, strapdown IMU, aided by either standard or carrier phase GPS technologies, is described. Results of the fusion process are presented.

Parity Vector Compensation Using Non-Linear Filtering

The performance of a failure detection and isolation(FDI) algorithm applied to a redundant strapdown inertial measurement unit (IMU) is limited by sensor errors such as input misalignments, scale factor errors, and biases. Non-linear filtering is proposed to estimate the combinations of sensor errors which affect the parity vector, the estimates are used to form a compensated parity vector. The compensated parity vector is used to make FDI decision for improving FDI performance. Simulation results prove that the FDI performance can be improved greatly by using the proposed method

Gyroscope free strapdown inertial measurement unit by six linear accelerometers

A six-accelerome ter configuration is presented to compute the rotationa^ and translational acceleration of a rigid body. This theoretical minimum accelerometer configuration has as stable a mechanization equation as that of recent results of nine-accelero meter schemes. Associated equations/that can be used to work with the accelerometer location and orientation errors are also derived. For navigation application, the novel design can be integrated with other sensors of complementary characteristics to enhance the performance.

Vector gravimetry using GPS in free-fall and in an Earth-fixed frame

The Global Positioning System (GPS) is considered in conjunction with a strapdown Inertial Measurement Unit (IMU) for measuring the gravity vector. A comparison of this system in space and on an airborne platform shows the relative importance of each system element in these two different acceleration environments. With currently available instrumentation, the acceleration measurement accuracy is the deciding factor in space, while on an Earth-bound (including airborne) platform, the attitude error of the IMU is most critical. A simulation shows that GPS-derived accelerations in space can be accurate to better than 0.1mgal for a 30s integration time, leading to estimates of 1° mean gravity anomalies on the Earth's surface with an accuracy of 4–5 mgal. On an airborne platform, the horizontal gravity estimation error is tightly coupled to the attitude error of the platform, which can only be bounded by external attitude updates. Horizontal gravity errors of 5mgal are achievable if the attitude is maintained to an accuracy of 1arcsec.

Strapdown inertial measurement units for motion compensation for synthetic aperture radars

It is shown that synthetic-aperture radar (SAR) motion can be compensated by using an antenna-mounted strapdown inertial measurement unit (IMU) as the motion sensing system, but sensor and system errors affect SAR image quality. A strapdown IMU consists of three accelerator channels and three gyro channels. Strapdown IMU errors include gyro-scale and accelerometer-scale factor and bias errors, velocity error, platform tilt, and errors induced by limited inertial sensor bandwidth. The effects of these errors on the SAR image quality are presented in terms of the SAR impulse response. IMU errors that cause low-frequency phase errors (less than one cycle per array time) are categorized in terms of quadratic and cubic phase errors. IMU errors that cause high-frequency phase errors (greater than one cycle per array time) are categorized in terms of the integrated sidelobe ratio and peak sidelobe ratio. A motion compensation system conceptualization is described wherein a strapdown IMU is attached to an antenna and transfer-aligns to the aircraft's master navigator.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>