Showing papers on "Inertial reference unit published in 2013"

A Wireless Micro Inertial Measurement Unit (IMU)

Abstract: In this paper, we present a wireless micro inertial measurement unit (IMU) with the smallest volume and weight requirements available at the moment. With a size of 22 mm × 14 mm × 4 mm (1.2 cm3), this IMU provides full control over the data of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. It meets the design prerequisites of a space-saving design and eliminates the need for hard-wired data communication, while still being competitive with state-of-the-art commercially available MEMS IMUs. A CC430 microcontroller sends the collected raw data to a base station wirelessly with a maximum sensor sample rate of 640 samples/s. Thereby, the IMU performance is optimized by moving data post processing to the base station. This development offers important features in portable applications with their significant size and weight requirements. Due to its small size, the IMU can be integrated into clothes or shoes for accurate position estimation in mobile applications and location-based services. We demonstrate the performance of the wireless micro IMU in a localization experiment where it is placed on a shoe for pedestrian tracking. With sensor data-fusion based on a Kalman filter combined with the zero velocity update, we can precisely track a person in an indoor area.

Nonlinear observer for GNSS-aided inertial navigation with quaternion-based attitude estimation

Abstract: For applications with limited computational capacity, observers designed based on nonlinear stability theory offer an alternative to computationally demanding extended Kalman filters. In this paper, we present a semiglobally stable nonlinear observer for estimating position, velocity, attitude, and gyro bias by combining a GNSS receiver with an inertial measurement unit including a magnetometer. Previous work by the authors on this topic was based on local navigation equations that ignored the Earth's rotation and curvature. Moreover, the attitude was represented by an over-parameterized 9-degrees-of-freedom matrix. The current paper improves on these aspects by using navigation equations that take the Earth's rotation and curvature into account, and by representing the attitude estimate as a unit quaternion. Furthermore, the observer is tested experimentally on data from a light fixed-wing aircraft.

Low-Cost Antenna Attitude Estimation by Fusing Inertial Sensing and Two-Antenna GPS for Vehicle-Mounted Satcom-on-the-Move

Abstract: In this paper, we develop a low-cost method to determine the vehicle attitude for vehicle-mounted satellite-communication (satcom)-on-the-move (SOTM) using a micro inertial measurement unit (MIMU) and a two-antenna global positioning system (GPS). An adaptive Euler-angle-based unscented Kalman filter (UKF) is utilized to fuse these sensors to guard against the effects induced by GPS outages and vehicle accelerations. When the two-antenna GPS can provide the vehicle yaw angle, the vehicle accelerations that introduce large errors to the accelerometer-measured gravitational acceleration can be corrected by the GPS-measured velocity and sideslip angle. When the two-antenna GPS fails to provide the yaw angle and needed information, the yaw angle is estimated only by integrating gyroscopes. The estimation of the pitch and roll angles is adaptively controlled by the vehicle acceleration detection rules. These rules make full use of the gyroscope output and the filtering results, which are more compatible with vehicle use than conventional accelerometer norm-based rule. The proposed method is verified with driving tests, suggesting that this technique is a viable candidate for low-cost SOTM.

A localization system using inertial measurement units from wireless commercial hand-held devices

Abstract: This paper describes a newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets. First, a step counting technique was implemented. Second, a novel step length estimator is proposed. These two algorithms utilize the data from accelerometer sensor only. Third, the heading information was obtained using a gyroscope with complementary filter in quaternion form. The combined algorithm was implemented on a low-power ARM processor to provide the trajectory points relative to an initial point. The proposed technique was tested by 10 subjects, in different shoes with different paces. The dependence of the performance of the technology on the attaching point of the mobile device is weak. The proposed algorithms have better balance and estimation accuracy and depend in less degree on the variety in physical parameters of people in comparison with the existing techniques. In experiments inertial measurement units were mounted in different places, i.e. in the hand, in trousers or in T-shirt pockets. The return position error did not exceed 5% of the total travelled distance for all performed tests.

A robust self-alignment method for ship's strapdown INS under mooring conditions.

Abstract: Strapdown inertial navigation systems (INS) need an alignment process to determine the initial attitude matrix between the body frame and the navigation frame. The conventional alignment process is to compute the initial attitude matrix using the gravity and Earth rotational rate measurements. However, under mooring conditions, the inertial measurement unit (IMU) employed in a ship's strapdown INS often suffers from both the intrinsic sensor noise components and the external disturbance components caused by the motions of the sea waves and wind waves, so a rapid and precise alignment of a ship's strapdown INS without any auxiliary information is hard to achieve. A robust solution is given in this paper to solve this problem. The inertial frame based alignment method is utilized to adapt the mooring condition, most of the periodical low-frequency external disturbance components could be removed by the mathematical integration and averaging characteristic of this method. A novel prefilter named hidden Markov model based Kalman filter (HMM-KF) is proposed to remove the relatively high-frequency error components. Different from the digital filters, the HMM-KF barely cause time-delay problem. The turntable, mooring and sea experiments favorably validate the rapidness and accuracy of the proposed self-alignment method and the good de-noising performance of HMM-KF.

Error analyses and calibration methods with accelerometers for optical angle encoders in rotational inertial navigation systems

Abstract: By rotating a strapdown inertial navigation system (INS) over one or more axes, a number of error sources originating from the employed sensors cancel out during the integration process. Rotary angle accuracy has an effect on the performance of rotational INS (RINS). The application of existing calibration methods based on gyroscope measurements is restricted by the structure of the inertial measurement unit (IMU) and scale factor stability of the gyroscope. The multireadhead method has problems in miniaturization and cost. Hence, optical angle encoder calibration methods using accelerometers are proposed, on the basis of navigation error and accuracy requirement analyses for a single-axis RINS. The test results show that the accuracy of calibration methods proposed is higher than 4 arcsec (1σ).

Inertial Measurement and Navigation System And Method Having Low Drift MEMS Gyroscopes And Accelerometers Operable In GPS Denied Environments

Abstract: An inertial measurement unit includes physically distinct sectors positioned in groups of orthogonally oriented angle rate sensors on a different sector of a base having orthogonally oriented accelerometers positioned thereon. A processor receiving signals from the sensors and accelerometers calculates a change in attitude, position, angular rate, velocity, acceleration of the unit over a plurality of finite time increments, or a combination thereof. The gyros and accelerometers have low-drift measurement accuracy for operation in a GPS-denied environment by preselecting pairs of gyros for physical assignment to achieve low-drift accuracy, determining weights for the gyros to be combined in tiered pairs, preselecting the accelerometers for physical assignment in low-drift pairs, determining weights for accelerometer optimal low-drift pair combining in tiers, or a combination thereof.

Inertial Sensors and Their Applications

Abstract: Due to the universal presence of motion, vibration, and shock, inertial motion sensors can be applied in various contexts. Development of the microelectromechanical (MEMS) technology opens up many new consumer and automotive applications for accelerometers and gyroscopes. The large variety of application creates different requirements to inertial sensors in terms of accuracy, size, power consumption and cost. It makes it difficult to choose sensors that are suited best for the particular application. Signal processing methods depend on the application and should reflect on the physical principles behind this application. This chapter describes the principles of operation of accelerometers and gyroscopes, different applications involving the inertial sensors. It also gives examples of signal processing algorithms for pedestrian navigation and motion classification.

3-D position estimation from inertial sensing: Minimizing the error from the process of double integration of accelerations

Abstract: This paper introduces a new approach to 3-D position estimation from acceleration data, i.e., a 3-D motion tracking system having a small size and low-cost magnetic and inertial measurement unit (MIMU) composed by both a digital compass and a gyroscope as interaction technology. A major challenge is to minimize the error caused by the process of double integration of accelerations due to motion (these ones have to be separated from the accelerations due to gravity). Owing to drift error, position estimation cannot be performed with adequate accuracy for periods longer than few seconds. For this reason, we propose a method to detect motion stops and only integrate accelerations in moments of effective hand motion during the demonstration process. The proposed system is validated and evaluated with experiments reporting a common daily life pick-and-place task.

The low cost micro inertial measurement unit

Abstract: Measuring the orientation of the mobile objects is essential for autonomous navigation. In order to construct low cost, miniature aerial vehicles a miniature inertial measurement unit was designed and constructed by the research team from Silesian University of Technology. Presented device can be distinguished by many times smaller volume than the solutions currently available at the market. It is worth mentioning with smaller size comes no degradation of the quality of measurements. Therefore it is possible to the presented sensor for real life applications.

Quick calibration method for inertial measurement unit

Abstract: The invention relates to a quick calibration method for an inertial measurement unit (IMU). According to the method, a user holds and rotates the IMU to move in all directions without any external equipment, so that twelve error coefficients including gyro biases, gyro scale factors, accelerometer biases and accelerometer scale factors can be accurately calibrated in a short time. The quick calibration method for the IMU is characterized by being free of hardware cost, high in efficiency and simple and easy to implement, and can ensure certain calibration precision. Thus, the quick calibration method is especially suitable for in-situ quick calibration for the medium- and low-grade IMUs, thereby effectively solving the problem of environmental sensitivity of the error coefficients of the mechanical IMU, and promoting popularization and application of MEMS (micro-electro mechanical systems) inertial devices.

Fiber-based rotary strapdown inertial navigation system

Abstract: Navigation involves the integration of methodologies and systems for estimating the time-varying attitude of moving objects. A fiber strapdown inertial navigation system (FSINS) is presently used in several applications related to vehicle navigation. However, the absolute attitude and position from FSINS contain an error that increases with time. In order to improve the performance of FSINS based on our present inertial sensors, the auto-compensation of inertial sensor bias in rotation error modulation was proposed. The aim is to develop a rotary FSINS, in which the significant sensor bias is automatically compensated by rotating the inertial measurement unit (IMU), to offer the comparable navigation performance to navigation-grade IMU. In the proposed rotational technol- ogy, the IMU is rotated back and forth in azimuth through four orthogonal positions relative to the vehicle's longitudinal axis. Simulation and exper- imental testing are conducted for the prototype, and the results showed that the rotary FSINS's navigation performance is improved. © 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) (DOI: 10.1117/1.OE.52.7.076106) Subject terms: fiber strapdown inertial navigation system; inertial measurement unit; rotating configuration.

Method and apparatus for determining a relative orientation of points on a rigid body

Abstract: An inertial measurement unit is affixed to a rigid body. The inertial measurement includes a gyroscope that measures a first angular velocity and an angular acceleration; a first accelerometer that measures a first acceleration; a communications unit that receives a measurement signal, the measurement signal including a second acceleration transmitted from a second accelerometer, the second accelerometer being affixed to the rigid body; and a controller that calculates a relative orientation of the inertial measurement unit and the second accelerometer, and a distance separating the inertial measurement unit and the second accelerometer.

Closed loop atomic inertial sensor

Abstract: An apparatus for inertial sensing is provided. The apparatus comprises at least one atomic inertial sensor, and one or more micro-electrical-mechanical systems (MEMS) inertial sensors operatively coupled to the atomic inertial sensor. The atomic inertial sensor and the MEMS inertial sensors operatively communicate with each other in a closed feedback loop.

Gravity gradiometer integrated inertial navigation

Abstract: In high precision inertial navigation, gravity field modeling error becomes a limiting factor. Granted that high precision accelerometers are used, airborne gravity gradiometry can be employed in a self-contained way to accurately estimate the gravity field on the fly and eliminate the gravity field modeling error. The local acceleration of gravity will be estimated using the onboard accelerometer measurements, provided that the acceleration measurements are very accurate, as is the case in high precision INS using cold atom interferometry-based accelerometers. An autonomous free-inertial gravity gradiometer integrated aircraft navigation system is promulgated. The accurate mapping of the gravity field along the aircraft's flight path is an added benefit.

High altitude UAV navigation using IMU, GPS and camera

Abstract: This paper deals with the integration of measurements provided by inertial sensors (gyroscopes and accelerometers), GPS (Global Positioning System) and a video system in order to estimate position and attitude of an high altitude UAV (Unmanned Aerial Vehicle). In such a case, the vision algorithms present ambiguities due to the plane degeneracy. This ambiguity can be avoided fusing the video information with inertial sensors measurements. On the other hand, inertial sensors are widely used for aircraft navigation because they represent a low cost and compact solution, but their measurements suffer of several errors which cause a rapid divergence of position and attitude estimates. To avoid divergence, inertial sensors are usually coupled with other systems as for example GPS. A camera presents several advantages with respect to GPS as for example great accuracy and higher data rate. Moreover, it can be used in urban area or, more in general, where no useful GPS signal is present. On the contrary, it has lower data rate than inertial sensors and its measurements have latencies which can prejudice the performances and the effectiveness of the flight control system. The integration of inertial sensors with a camera allows exploiting the better features of both the systems, providing better performances in position and attitude estimation. The data fusion is performed via a multirate Unscented Kalman Filter (UKF) because of the nonlinear dynamic system equation. Experimental results show the effectiveness of the proposed method.

Sensor Fusion with Low-Grade Inertial Sensors and Odometer to Estimate Geodetic Coordinates in Environments without GPS Signal

Abstract: This paper presents a sensor fusion algorithm based on a Kalman Filter to estimate geodetic coordinates and reconstruct a car test trajectory in environments where there is no GPS signal. The sensor fusion algorithm is based on low-grade strapdown inertial sensors (i.e. accelerometers and gyroscopes) and an incremental odometer, from which, velocity measurements is obtained. Since the dynamic system is non linear, an Extended Kalman Filter (EKF) is used to estimate the states (i.e. latitude, longitude and altitude) and reconstruct the test trajectory. The relevance of this work is given by the fact that, in the current literature, much has been published about the merger Inertial Sensors and GPS, however, currently no literature that addresses the form of sensor fusion proposed here is available. Another aspect that could be emphasized is that the proposed algorithm has potential to be applied in environments where GPS signals are not available, such as Pipeline Inspection Gauge (PIG) as depicted below in figure 2. The inertial navigation system developed and tested, shows that only with inertial sensors measurements, a closed tested trajectory can not be reconstructed satisfactorily, however when it uses the sensor fusion, the trajectory can be reconstructed with relative success. On preliminary experiments, it was possible reconstruct a closed trajectory of approximately 2800m, attaining a final error of 13m.

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Abstract: Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Development of a MEMs-based IMU Unit

Abstract: In this study, gyroscope-free inertial measurement unit interface is developed to simulate new system configurations called YILDIZ using known calculation methods and implementation of MEMS accelerometers based on cubic arrangement. Additionally significant effect of different sensing directions and sensor allocations are taken into consideration. Throughout the project, simulation studies, realization of sample gyro-free MEMs-based INS systems, and collection of data through data acquisition systems are performed in given order. Using simulation of the system, parameter-dependent errors are aimed to be minimized on the system output. Then, near-ideal geometry and the sensor configurations can be reached and the system can be realized. Prototype outputs are processed and efficient algorithms are developed using Matlab-Simulink environment.

Distance estimation using inertial sensor and vision

Abstract: A simple distance estimation algorithm using inertial sensors and a mono camera is proposed. Two images of a target are obtained by moving a mono camera. The movement of the camera is estimated using inertial sensors and used as the baseline for the distance estimation. Through experiments, the accuracy of the proposed method is evaluated, where the distance error is 3.9% on average in a few meter ranges.

Observability analysis of a vision-aided inertial navigation system using planar features on the ground

Abstract: In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point feature are considered as state variables. In particular, we prove that the system has only three unobservable directions corresponding to global translations along the x and y axes, and rotations around the gravity vector. Hence, compared to general VINS, an advantage of using only ground features is that the vertical translation becomes observable. The findings of the theoretical analysis are validated through real-world experiments.

Inertial navigation accuracy increasing using redundant sensors

Abstract: The inertial instruments can achieve high accuracy for long periods of time only by redundancy. Redundant inertial measurement unit is an inertial sensing device composed by more than three accelerometers and three gyroscopes. This paper analyses the performance of redundant inertial measurement unit and their various sensors configurations. By suitable geometric configurations it is possible to extract the maximum amount of reliability and accuracy from a given number of redundant single-degree-of-freedom gyroscopes or accelerometers. This paper gives particularly attractive configurations of four, five and six sensors. These combinations are capable of functioning with any three sensors, of detecting a malfunction with any four, And of isolating a malfunction with any five. In contrast, arrangements with redundant sensors whose input axes are parallel to only three orthogonal axes require five sensors to detect and nine sensors to isolate a malfunction. The sensors configurations shown not only minimize system error when all sensors are operable, but when all but three have malfunctioned as well the reliability and accuracy of these redundant configurations are compared to a conventional unit of three orthogonal instruments.

A Kalman Filter for Odometry using a Wheel Mounted Inertial Sensor

Abstract: This paper describes an Extended Kalman Filter for a wheel mo unted inertial measurement unit using two accelerometers and a single gyroscope as a substitute for cl assical odometry sensing. The sensor can be mounted with minimal effort on existing wheeled vehicles. I t is highly robust against vibration while rolling on uneven terrain and can cope with higher speeds even when th e measurement range is partially exceeded. It has been developed as a component of a GPS based urban navig ation assistant for elderly people using walkers, wheelchairs, or tricycles as an add-on device.

A miniature, low-cost MEMS AHRS with application to posture control of robotic fish

Abstract: Inertial sensing is of paramount importance for a wide variety of navigation, guidance and control tasks. Historically, application of inertial sensing was limited to high-performance, high-cost aerospace and military fields. Recent MEMS technology has enabled miniaturization, mass production, and cost reduction of inertial sensors. This paper presents the development and robotic application of a miniature, low-cost AHRS unit based on MEMS technology. The sensor suite includes a tri-axis gyroscope, a tri-axis accelerometer and a tri-axis magnetometer. Fusion of the sensor measurements is achieved with a quaternion-based EKF algorithm. The performance of the AHRS unit is evaluated with a rotating platform and the results suggest numerous application possibilities. As an application case, the AHRS unit is employed for posture measurement of a robotic fish. By adjusting the lift forces produced by pectoral fins on both sides, the robotic fish can maintain desired posture during highspeed swimming.

High-accuracy heading determination

Abstract: In a system of systems context, a variety of applications are dependent on the knowledge of location and attitude of individual agents in order to collaborate. For example, a soldier on the battle field observing a potential target transmits this information to a base station which then is shared with an unmanned air vehicle for surveillance. Without precise knowledge of the soldier's position and azimuth angle to the target, the handoff to the UAV would not carry much merit. The availability of low-cost MEMS inertial measurement units (IMU) increases the feasibility of realizing a compact inertial navigation systems (INS) capable of operating in a variety of environments, including GPS degraded or denied scenarios. Due to errors in the IMU, it is very challenging to self-initialize the attitude of the device in a reasonable time frame. In this paper, we present a novel approach that utilizes a unique magnetohydrodynamic (MHD) angular rate sensor (ARS) in a carouseling configuration in order to perform attitude self-initialization to within 4-milli radians in less than a minute. Further more, real environmental issues, such as platform vibration and base motion (e.g. sinking) are also addressed.

MEMS inertial navigation systems for aircraft

Abstract: This chapter discusses MEMS accelerometers and gyroscopes and how inertial navigation systems (INS) are used with these sensors for aircraft. The chapter first reviews MEMS sensors and the limitations of MEMS inertial sensors to be embedded in INS, then discusses INS and the integration of INS with global positioning systems (GPS); it provides background on the use of sensor fusion and a Kalman filter to aid INS, and presents the challenges and trends of MEMS INS for aircraft.

Method to determine a direction and amplitude of a current velocity estimate of a moving device

Abstract: A new method for the estimation of ego-motion (the direction and amplitude of the velocity) of a mobile device comprising optic-flow and inertial sensors (hereinafter the apparatus). The velocity is expressed in the apparatus's reference frame, which is moving with the apparatus. The method relies on short-term inertial navigation and the direction of the translational optic-flow in order to estimate ego-motion, defined as the velocity estimate (that describes the speed amplitude and the direction of motion). A key characteristic of the invention is the use of optic-flow without the need for any kind of feature tracking. Moreover, the algorithm uses the direction of the optic-flow and does not need the norm, thanks to the fact that the scale of the velocity is solved by the use of inertial navigation and changes in direction of the apparatus.