Approaches to optimal inertial instrument calibration using slewing

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.Includes bibliographical references (p. 61).Calibration of an inertial measurement unit is important to the success of accuracy-sensitive missions. This thesis analyzes calibration techniques for two inertial measurement mechanizations: (1) an inertially stabilized system and (2) an inertially referenced slew. An inertially referenced slew rotates the inertial measurement unit with respect to an inertial reference frame independent of the vehicle motion. The appropriate inertially referenced slew is determined by a proposed optimal calibration method that maximizes the correlation between a measurement and a covector, specifying a mission performance index. The performances of a six-position dwell calibration (inertially stabilized system) and an optimal slewing calibration (inertially referenced slew) are determined to be dependent on the mission. The inertially stabilized system is preferred for determining accelerometer errors and an inertially referenced slew is preferred for calibrating rate-sensitive gyroscope errors.by Theresia C. Becker.S.M

Sensor fusion and actuator system of a quadrotor helicopter

This article focuses on the sensor and actuator system of an autonomous indoor quadrotor helicopter. The sensor system has two parts: an inertial measurement unit (IMU) and a vision system. The fusion between the two systems is solved by extended Kalman filters. The calibration of the inertial measurement unit is described for various types of errors. The variance analysis is performed for the noise sources of sensors. The actuators of the helicopter are the four rotors. The identification and low level control of the brushless DC motor based rotor system is also presented. The embedded control system integrates a lot of processors and communication lines. The verification of the system´s parts were performed under real-time conditions. The main results of the paper are the new calibration algorithm for the different sensors and the real-time realization of the complex sensory system that may be part of a formation control system of UAVs

Блочная калибровка инерциально-измерительного модуля

Представлено новий метод калібрування інерціальних вимірювальних блоків для безплатформової інерціальної технології. Інерціальний вимірювальний блок складається з акселерометрів, гіроскопів і системи обробки сигналів. Як правило, для калібрування інерціального вимірювального блоку використовують метод тестових поворотів та обертання на поворотному столі. Новий метод калібрування основано на вимірюванні повного кута повороту або кінцевого обертання. Фактично пропонується повертати інерціальний вимірювальний блок навколо одної осі кінцевого повороту. Для розв’язання рівняння калібрування необхідно забезпечити рівність рангу основної матриці порядку базової матриці. Результати змодельованих даних ІВБ представлено для демонстрації ефективності нового методу калібрування.A new calibration method is proposed for the inertial measurement units of strapdown inertial technology. Such a block consists of accelerometers, gyroscopes and a signal processing system. As a rule, the method of test turnings and rotations on rotary table is used for calibration of the inertial measurement unit. The new method is based on measurement of the full angle of turning or the final rotation. In fact, it is proposed to turn the inertial measurement unit around the axis of final rotation. To solve the equation of calibration, it is necessary to provide the equality of the rank and order of basic matrix. The results of modeling data demonstrate an efficiency of new method of calibration

Airdata calibration of a high-performance aircraft for measuring atmospheric wind profiles

The research airdata system of an instrumented F-104 aircraft has been calibrated to measure winds aloft in support of the space shuttle wind measurement investigation at the National Aeronautics and Space Administration Ames Research Center Dryden Flight Research Facility. For this investigation, wind measurement accuracies comparable to those obtained from Jimsphere balloons were desired. This required an airdata calibration more accurate than needed for most aircraft research programs. The F-104 aircraft was equipped with a research pilot-static noseboom with integral angle-of-attack and flank angle-of-attack vanes and a ring-laser-gyro inertial reference unit. Tower fly-bys and radar acceleration-decelerations were used to calibrate Mach number and total temperature. Angle of attack and angle of sideslip were calibrated with a trajectory reconstruction technique using a multiple-state linear Kalman filter. The F-104 aircraft and instrumentation configuration, flight test maneuvers, data corrections, calibration techniques, and resulting calibrations and data repeatability are presented. Recommendations for future airdata systems on aircraft used to measure winds aloft are also given

Attitude Sensor and Gyro Calibration for Messenger

The Redundant Inertial Measurement Unit Attitude Determination/Calibration (RADICAL(TM)) filter was used to estimate star tracker and gyro calibration parameters using MESSENGER telemetry data from three calibration events. We present an overview of the MESSENGER attitude sensors and their configuration is given, the calibration maneuvers are described, the results are compared with previous calibrations, and variations and trends in the estimated calibration parameters are examined. The warm restart and covariance bump features of the RADICAL(TM) filter were used to estimate calibration parameters from two disjoint telemetry streams. Results show that the calibration parameters converge faster with much less transient variation during convergence than when the filter is cold-started at the start of each telemetry stream

3D-Calibration of the IMU

International audienceA new calibration method for Inertial Measurement Unit (IMU) of strapdown inertial technology was presented. IMU has been composed of accelerometers, gyroscopes and a circuit of signal processing. Normally, a rate transfer test and multi-position tests are used for IMU calibration. The new calibration method is based on whole angle rotation or finite rotation. In fact it is suggested to turn over IMU around three axes simultaneously. In order to solve the equation of calibration, it is necessary to provide an equality of a rank of basic matrix into degree of basic matrix. The results of simulated IMU data presented to demonstrate the performance of the new calibration method

A user interactive calibration program for an object tracking system using a triaxial accelerometer

A major method in object tracking systems and other inertial measurement devices resolves around the use of one, two, or three axis accelerometers. A leader in the field such devices is Microstrain Incorporated. They have developed a three axis accelerometer that uses a three axis magnetic sensor array to compute the pitch, roll, and yaw of a compact inertial measurement unit. In researching such devices, it became apparent that data collected using such units is extremely sensitive both to local magnetic fields and human interactions with the devices. It is therefore of great importance to ensure the device or devices are properly calibrated. In the construction of an effective calibration program, it is necessary to measure and zero out even minor discrepancies, as even small misalignments have deleterious effects on device performance

Automated Static Camera Calibration with Intelligent Vehicles

Connected and cooperative driving requires precise calibration of the roadside infrastructure for having a reliable perception system. To solve this requirement in an automated manner, we present a robust extrinsic calibration method for automated geo-referenced camera calibration. Our method requires a calibration vehicle equipped with a combined GNSS/RTK receiver and an inertial measurement unit (IMU) for self-localization. In order to remove any requirements for the target's appearance and the local traffic conditions, we propose a novel approach using hypothesis filtering. Our method does not require any human interaction with the information recorded by both the infrastructure and the vehicle. Furthermore, we do not limit road access for other road users during calibration. We demonstrate the feasibility and accuracy of our approach by evaluating our approach on synthetic datasets as well as a real-world connected intersection, and deploying the calibration on real infrastructure. Our source code is publicly available.Comment: 7 pages, 3 figures, accepted for presentation at the 34th IEEE Intelligent Vehicles Symposium (IV 2023), June 4 - June 7, 2023, Anchorage, Alaska, United States of Americ