Jan Rohac

Analyses of Triaxial Accelerometer Calibration Algorithms

This paper proposes a calibration procedure in order to minimize the process time and cost. It relies on the suggestion of optimal positions, in which the calibration procedure takes place, and on position number optimization. Furthermore, this paper describes and compares three useful calibration algorithms applicable on triaxial accelerometer to determine its mathematical error model without a need to use an expensive and precise calibration means, which is commonly required. The sensor error model (SEM) of triaxial accelerometer consists of three scale-factor errors, three nonorthogonality angles, and three offsets. For purposes of calibration, two algorithms were tested-the Levenberg-Marquardt and the Thin-Shell algorithm. Both were then related to algorithm based on Matlab fminunc function to analyze their efficiency and results. The proposed calibration procedure and applied algorithms were experimentally verified on accelerometers available on market. We performed various analyses of proposed procedure and proved its capability to estimate the parameters of SEM without a need of precise calibration means, with minimum number of iteration, both saving time, workload, and costs.

Calibration of low-cost triaxial inertial sensors

Accelerometers (ACCs) and gyroscopes (gyros) are commonly known as inertial sensors and their orthogonal triads generally form an inertial measurement unit (IMU) used as a core means of a navigation system. Before the navigation system is to be used, it is necessary to perform its calibration. A typical process of the IMU calibration usually estimates scale-factors, orthogonality or misalignment errors, and offsets of both triads. These parameters compose the so-called sensor error model (SEM). The process of obtaining accurate information that describes the motion performed within the calibration generally requires a costly and specialized means [1], [2]. Therefore, much effort has been put into cost-effective calibration using an optical motion tracking system [3]-[6], or transferring the calibration into a state estimation problem [7]. In the ACC case, most of the current calibration methods utilize the fact that ACCs are affected by gravity when they are under static conditions. Therefore, we proceed with calibration performed under static conditions, which utilizes the knowledge of the gravity magnitude and ACC output measurements collected at predetermined orientations and performs ACC SEM estimation using nonlinear optimization [6], [8]-[10]. In the gyro case, calibration based on the Earths rate might be inapplicable, for instance due to the fact that Earths rate is under or around the resolution of the gyro, and thus other means to apply and measure angular rates need to be used. This situation commonly arises in the case of low-cost MEMS (Micro-Electro-Mechanical System) based gyros. Thus, expensive mechanical platforms are often inevitable [11]-[14].

Flight attitude track reconstruction using two AHRS units under laboratory conditions

The paper describes a performance analysis of two low-cost AHRS (Attitude and Heading Reference Systems), calibration procedures, and the verification of INS (Inertial Navigation System) mechanization algorithm using dedicated automatic measurement system based on a real-time flight simulation. The measurement system included the flight simulation software FlightGear (FG) that offered a wide range of aircraft dynamics and track simulation possibilities. The FG output data were converted into the form suitable for a servo-controlled Rotational-Tilt Platform (RoTiP) which provided corresponding motion for two AHRS units mounted on it and reference information from optical sensors. The output data of the AHRS units were collected, processed and evaluated to verify the units accuracy and reliability. The methodology and results based on the performance analyses are presented.

Data processing of inertial sensors in strong-vibration environment

Data processing of low-cost inertial sensors has been and still is a big issue for many engineers in commercial companies, laboratories, and academia. Inertial sensors compose a measurement unit used as the basis of navigation systems. These systems can be found almost everywhere; it does not matter if it is in pharmaceutics, robotics, automotive industry, aerospace etc. However, there is always a need to specify under which conditions the systems are supposed to operate. This paper deals with the processing of inertial sensor data measured in an environment with strong vibrations on the ultra-light aircraft ATEC 321. It was a great challenge to process the data in such a way as to ensure the acceptable behavior of the artificial horizon system. Because the system should rely only on acceleration and angular rate sensing, the correctness and efficiency of data filtering as well as consecutive data processing play a key role. Results regarding data analyses and comparisons of different approaches are presented.

Inertial reference unit in a directional gyro mode of operation

This paper deals with a cost effective inertial reference unit design providing both MEMS based navigation unit calibration means and an attitude and heading measurement system in a directional gyro mode of operation. A main contribution of this paper is a novel design of such a universal system not primary relying on a magnetometer (MAG) or GPS aiding. Generally, without this aiding Attitude and Heading Reference Systems (AHRSs) are not directionally stable. Also, having precise reference in a calibration process is crucial and in most cases the solution is expensive. We thus replaced an expensive solution of both applications with the cost effective one suiting mentioned purposes using only one single axis fiber optic gyro supported by an inertial MEMS based aiding system. We also proposed a calibration procedure and blended solution to provide both stable and reliable navigation data with accuracy better than 5 deg/h specified by the TSO-C5e.

Complex Markers for a Mine Detector

This paper describes a novel type of metal markers for eddy current metal detection systems using precise positioning information. The new design for metal markers which are compounded by an ordered array of metal plates with different magnetic parameters has three fundamental advantages: 1. the markers are sensed directly by the metal detector, and no additional hardware is required; 2. the signatures are sharp; 3. not only the position but also the speed of the detector head can be evaluated. In the case of a stand-alone inertial navigation system for evaluating the position of the detector, the precision would be low due to the sensor noise and its integration. However, knowledge of the relative positions and potentially of the detector head speed over the markers can be used as auxiliary in formation, and so the eddy-current mapping system will be capable of determining the size of the magnetic imprint of a detected metal object and its position relative to the markers. This increases the reliability of the object discrimination during humanitarian demining, and decreases the numbers of false alarms, which nowadays constitute 99.9% of all alarms emitted by an ordinary mine detector.

Calibration of a multi-sensor inertial measurement unit with modified sensor frame

Calibration of the inertial measurement units (IMU) used in navigation systems are crucial for ensuring accuracy of a navigation solution. It is common to discuss what calibration means, techniques, and algorithms can be utilized and implemented. For cost-effective measurement units it is desirable to use calibration means and approaches which are not expensive yet capable of providing sufficient accuracy. This paper thus focuses on multi-sensor inertial measurement unit which utilizes a modified sensor frames. Unlike the common IMUs which consist of 3-axial accelerometer and gyroscope frames, the proposed concept of the multi-sensor unit consists of ten modified accelerometer frames supplemented by an unmodified gyro frame. The modified frames of accelerometers are optimized for differential analogue signal processing in order to increase signal-to-noise ratio and hence overall sensing precision. Since the proposed concept of the measurement unit includes higher number of sensing frames it is required to develop a novel “easy to do and implement” calibration method which is the contribution of this paper. The proposed calibration approach was experimentally verified and results confirmed its usability.

Metal Detector Signal Imprints of Detected Objects

Humanitarian demining missions are activities in which an operator safety and time consumption are key issues. To increase a discrimination ability of ATMID metal detector, which we have been using, we extended the capability of the detector with mounting inertial measurement unit (IMU) supplemented by two optical distance sensors on the detector head. That enabled us to perform dead reckoning based on accelerations and angular rates measured by IMU in all three axes. Optical distance sensors have been used for compensation purposes and an initial distance measurement. Our main aim was to interconnect magnetic imprint sensed by the detector with precise localization of its head, which led to imprint size estimation as well as its position. Due to low-cost micro-electro-mechanical system (MEMS) based IMU implementation we have had to deal with unstable dead reckoning outcomes. For this reason we used our designed complex magnetic markers (CMMs) which demarked a searched area plus provided us with precise positioning at its both edges. The main contribution of this paper is in the study and identification of CMM magnetic imprints characteristics and their differences related to various aspects of CMM usage during demining procedure and its conditions. The characteristics of CMMs have been studied and analyzed according to several laboratory experiments and results are presented.

Validation of nonlinear integrated navigation solutions

Abstract There exist numerous navigation solutions already implemented into various navigation systems. Depending on the vehicle in which the navigation system is used, it can be distinguished in most cases among; navigation, tactical, and commercial grade categories of such systems. The core of these systems is formed by inertial sensors, i.e. accelerometers and angular rate sensors/gyros. Navigation and tactical grade systems commonly rely on fiber optic/ring laser gyros and servo/quartz accelerometers with high resolution, sensitivity, and stability. In the case of cost-effective navigation systems, for example piloted light and ultralight aircraft, usually use commercial grade sensors, where the situation differs. The sensor outputs are less stable and sensitive, and suffer from manufacturing limits leading to temperature dependency, bias instability, and misalignment which introduces non-negligible disturbances. These conditions commonly limit the applicability of the navigation solution since its stand-alone operation using free integration of accelerations and angular rates is not stable. This paper addresses a cost-effective solution with commercial grade inertial sensors, and studies the performance of different approaches to obtain navigation solution with robustness to GNSS outages. A main goal of this paper is thus comparison of a nonlinear observer and two extended Kalman filter solutions with respect to the accuracy of estimated quantities and their sensitivity to GNSS outages. The performance analyses are carried out on real flight data and evaluated during phases of the flight when the solutions are challenged by different environmental disturbances.

Validation and Experimental Testing of Observers for Robust GNSS-Aided Inertial Navigation

This chapter is the study of state estimators for robust navigation. Navigation of vehicles is a vast field with multiple decades of research. The main aim is to estimate position, linear velocity, and attitude (PVA) under all dynamics, motions, and conditions via data fusion. The state estimation problem will be considered from two different perspec‐ tives using the same kinematic model. First, the extended Kalman filter (EKF) will be reviewed, as an example of a stochastic approach; second, a recent nonlinear observer will be considered as a deterministic case. A comparative study of strapdown inertial navigation methods for estimating PVA of aerial vehicles fusing inertial sensors with global navigation satellite system (GNSS)-based positioning will be presented. The focus will be on the loosely coupled integration methods and performance analysis to compare these methods in terms of their stability, robustness to vibrations, and disturbances in measurements.