Strapdown Inertial Measurement Unit Research Articles

Using Functionally Redundant Inertial Measurement Units to Increase Reliability and Ensure Fault Tolerance

This paper aims to assess the possibility of using functionally redundant inertial units to solve problems of increasing reliability and ensuring the fault tolerance of the various classes and purposes of aircraft navigation systems. We present the results of studying failure detection methods to improve the accuracy and reliability of a strapdown functionally redundant inertial unit. The resulting structural redundancy of the strapdown inertial measurement unit is designed to increase the fault tolerance and accuracy of strapdown inertial navigation systems. The methods for detecting sensor failures in functionally redundant inertial units are based on the use of the equations of functionally redundant inertial unit compliance to nominal requirements for the accuracy of measuring the input action vector. To describe the methods for detecting and eliminating failed sensor and algorithm designs based on them, we gave the mathematical models of the measurement vector of functionally redundant inertial units concerning the measured vector and the error identification condition, including the residual of the matching equations with the size due to the level of redundancy, determining the total number of matching equations. The main criterion for determining a failed sensor is non-compliance with the nominal value of the residual included in a certain number of matching equations of the information received from such meters. The developed algorithms are examined using simulation methods. The study of the selected structure of the functionally redundant inertial units shows that the proposed approaches are efficient. Also, we manage to identify the main characteristics of the algorithms for detecting sensor failures that are structurally a part of the functionally redundant inertial units.

Airborne Absolute Gravimetry With a Quantum Sensor, Comparison With Classical Technologies

AbstractWe report an airborne gravity survey with an absolute gravimeter based on atom interferometry and two relative gravimeters: a classical LaCoste&Romberg (L&R) and a novel iMAR strapdown Inertial Measurement Unit. We estimated measurement errors for the quantum gravimeter ranging from 0.6 to 1.3 mGal depending on the flight conditions and the filtering used. Similar measurement errors are obtained with iMAR strapdown gravimeter, but the long‐term stability is five times worse. The traditional L&R platform gravimeter shows larger measurement errors (3–4 mGal). Airborne measurements have been compared to marine, land, and altimetry‐derived gravity data. We obtain a good agreement for the quantum gravimeter with standard deviations and means on differences below or equal to 2 mGal. This study confirms the potential of quantum technology for absolute airborne gravimetry, which is particularly interesting for mapping shallow water or mountainous areas and for linking ground and satellite measurements with homogeneous absolute referencing.

Strapdown inertial measurement unit shock absorption and damping linear system analysis

Strapdown inertial measurement unit shock absorption and damping linear system analysis

Spatial resolution of airborne gravity estimates in Kalman filtering

Abstract Airborne gravimetry is an efficient and reliable method to obtain information on the gravity field, fundamental to gravity field modelling, geoid determination, and flood risk mapping. In evaluation and utilization of gravity estimates, two measures are of fundamental importance, namely the accuracy and spatial resolution. These measures are related to one another through the filtering required to suppress observational noise. As strapdown inertial measurement units (IMUs) are increasingly deployed for airborne gravity surveys, the Kalman filter estimation method is routinely used for gravity determination. Since filtering is not applied directly to the observations in Kalman filtering, it is not straightforward to associate the derived gravity estimates with a measure of spatial resolution. This investigation presents a method for deriving spatial resolution by evaluating the transfer function formed after applying a delta function to the observed accelerations. The method is applied to Kalman-filter-derived gravity estimates from an airborne strapdown IMU system, yielding a full-wavelength spatial resolution of 5.5 km at an accuracy of 0.6 mGal. These results are consistent with a comparison with upward continued terrestrial gravity observations.

Image processing based horizon sensor for estimating the orientation of sounding rockets, launch vehicles and spacecraft

The paper describes how the attitude of a sounding rocket, launch vehicle or satellite with respect to the Earth can be estimated from camera images of the Earth horizon. Details about detecting the horizon in the camera image, fitting hyperbolae or ellipses to the detected horizon curve and deriving the Earth nadir vector and the corresponding error covariance from the fitted conic section are given. The presented method works at low heights, where the projected horizon mostly appears to be hyperbolic, as well as at large heights, where the projected horizon mostly appears to be elliptic and it is irrelevant if the Earth is fully or only partially in the field of view of the camera. The method can be universally used to estimate the direction vectors and attitude with respect to any spherical celestial body such as the Sun or Moon. Using the example of a sounding rocket mission with two cameras aboard, it is illustrated how the estimates of the Earth nadir and the Sun direction vectors are fused with the measurements of a strapdown inertial measurement unit and a GPS receiver to obtain an accurate and continuous estimate of the three-dimensional orientation of the sounding rocket with respect to the Earth.

SIMU/Triple star sensors integrated navigation method of HALE UAV based on atmospheric refraction correction

AbstractTo achieve autonomous all-day flight by high-altitude long-endurance unmanned aerial vehicle (HALE UAV), a new navigation method with deep integration of strapdown inertial measurement unit (SIMU) and triple star sensors based on atmospheric refraction correction is proposed. By analysing the atmospheric refraction model, the stellar azimuth coordinate system is introduced and the coupling relationship between attitude and position is established. Based on the geometric relationship whereby all the stellar azimuth planes intersect on the common zenith direction, the sole celestial navigation system (CNS) method by stellar refraction with triple narrow fields of view (FOVs) is studied and a loss function is built to evaluate the navigation accuracy. Finally, the new SIMU/triple star sensors deep integrated navigation method with refraction correction upgraded from the traditional inertial navigation system (INS)/CNS integrated method can be established. The results of simulations show that the proposed method can effectively restrain navigation error of a HALE UAV in 24 h steady-state cruising in the stratosphere.

Dynamical Analysis for the INS Vibration Control System Used in UAV

A six-degree-of-freedom mechanical dynamic model and its equations of the damping system are established for the offset installation environment of the UAV. The influence parameters of the damping system on the vibration coupling state is studied based on the model. And the optimal parameters of the damping system are obtained by doing the mechanical dynamic calculation. And then the vibration isolator of the UAV strap-down inertial measurement unit is designed and manufactured. Finally, the damping system was tested and verified on the shaking table and in the flight environment of the UAV. It is shown that the damping system could implement the tri-axial equal rigid design when the shaft-to-radius stiffness of the isolator is about 0.8. And the experiments also prove this point. The damping system weakens the coupling problem of the strap-down inertial measurement unit effectively, and it reaches the quasi-decoupled state. The amplitude of the acceleration decreases by more than 50% after vibration isolation.

The Use of Gravity Reductions in the Indirect Strapdown Airborne Gravimetry Processing

Strapdown airborne gravimetry (SAG) is one of the most efficient techniques used in geodesy and geophysics for acquiring gravity data on relatively large regions in a faster and cost-effective way or to fill in the gravity data gaps on areas where it is neither practical nor possible to make terrestrial measurements. Recent studies have shown that accuracies of 1 mGal and precision of sub-mGal levels are possible with the strapdown inertial systems modified for gravimetry (e.g., temperature stabilization). Besides the advancements in the instrumentation, data processing and integration algorithms are evolving consistently. This study investigates the contribution of long- and short-wavelength gravity reductions following the remove–restore procedure in the indirect SAG processing, where the gravity disturbance at flight altitude is modeled stochastically as an additional system state in the Kalman filter sense. The proposed method is implemented to the airborne data collected in central Turkey in 2018 with a thermally stabilized strapdown inertial measurement unit of navigation-grade type. The inclusion of the long- and short-wavelength gravity reductions in the SAG processing limits the in-run bias variations of the Z-accelerometer and changes the parameters of the third-order Gauss–Markov gravity state model significantly. Utilization of the reduced gravity disturbance in the processing provides better long-wavelength stability in the solution by reducing the mean bias of about 2.60 to 0.65 mGal between the airborne gravity estimates and a high-resolution global gravity model. Moreover, a remarkable improvement in the internal precision is achieved when the gravity reductions are introduced into the SAG solution. Comparisons at the crossover points demonstrate that the application of gravity reductions yields considerably lower crossover residuals than the standard solution without reductions. The non-adjusted crossover differences of the long- and short-wavelength removed and restored SAG solution result in an RMSE value of 0.79 mGal, that is, 40% better precision than the standard solution.

New Results from Strapdown Airborne Gravimetry Using Temperature Stabilisation

In recent years, the use of a strapdown Inertial Measurement Unit (IMU) for airborne gravimetry has proven itself to be an accurate and resilient measurement system, improving the operational flexibility. The main concern is erroneous long-wavelength information in the resulting estimates, which is suspected to originate from uncompensated long-term drift of the accelerometers, probably originating from temperature variation. For this reason, iMAR navigation has designed a temperature stabilisation box, which allows for temperature stabilisation of their IMU systems. On a regional airborne gravity survey over the Kattegat Sea between Denmark and Sweden, such a temperature stabilised strapdown IMU was operated alongside a traditional spring-type platform-stabilised gravity system from ZLS. An analysis of the difference in gravity estimates at cross-over locations yielded a mean value of −0.3 mGal for the iMAR system with an indicated accuracy of 1.0 mGal. The temperature stabilisation unit therefore effectively limits the accelerometer drift and improves the long-wavelength information. However, a straightforward merging approach, adjusting the line-based mean values of the iMAR estimates to match that of the ZLS estimates, improved the accuracy to 0.8 mGal. This indicates that the long-wavelength information of the stabilised-platform system is still superior to that of the strapdown system.

Estimating the Accuracy Parameters of Sensors in a Strapdown Inertial Measurement Unit with the Use of a Relatively Coarse Turntable

The technique for calibration of sensors in a strapdown inertial measurement unit on a relatively coarse (1°–2°) turntable are discussed. The proposed technique is based both on direct and indirect methods. Calibration errors are estimated analytically and, also, by means of mathematical simulation. For direct methods, the choice of program orientations is substantiated; the vector method is compared with the scalar one. The results of calibration of a measurement unit on fiber-optic gyroscopes obtained with the use of the proposed technique are given.

Performance Analysis of GNSS-Aided Inertial Navigation Systems on Spinning Flight Vehicles

Inertial navigation on spin-stabilized sounding rockets and missiles is challenging due to the high spin rate about the longitudinal axis. Especially the scale factor error of the roll axis gyroscope causes an accumulating roll angle error, which may subsequently transform to the lateral axes if, for example, the rocket is actively reoriented. This orientation error leads to growing position and velocity estimation errors whenever propulsion or aerodynamic forces act on the rocket. Specialized inertial platforms were developed in the 1970s with gimbaled inertial measurement units isolating the sensors from the high spin rate. Because these platforms are rarely available on the market today, ongoing research focuses on integrated navigation systems with strap-down inertial measurement units and additional aiding sensors such as satellite navigation receivers, Sun sensors, or star tracker. Because satellite navigation receivers are well-established on sounding rockets for range safety anyway, this paper investigates to what extent position, velocity, and particularly orientation errors can be estimated with satellite navigation aiding only. Using the example of SHEFEX-2, the paper discusses the observability of translational and rotational navigation errors by translational aiding measurements along a typical trajectory of a two-staged and actively reoriented sounding rocket both qualitatively and quantitatively.

Adaptive Output-Feedback Image-Based Visual Servoing for Quadrotor Unmanned Aerial Vehicles

This brief presents an adaptive output feedback image-based visual servoing (IBVS) law for a quadrotor unmanned aerial vehicle. The control objective is to regulate the relative 3-D position and yaw of the vehicle to a planar horizontal visual target consisting of multiple points. The control is implemented using a minimal number of commonly available low-cost on-board sensors including a strapdown inertial measurement unit and a monocular camera. The IBVS method relies on moment image features which are defined using a virtual camera. Output feedback introduces a filter to the control which removes the common requirement for linear velocity measurement. The method is adaptive and compensates for a constant force disturbance appearing the translational dynamics and parameter uncertainty in thrust constant, desired feature depth, and mass. Exponential stability of the outer loop and combined inner-outer closed-loop error dynamics is proven. Flight tests demonstrate the proposed method's motion control performance and its ability to compensate parametric uncertainty and reject constant force disturbances.

Guidance and Control Method for Vehicle with Strap-down Seeker

Guidance and control method was presented in this paper for flight vehicle with a strap-down seeker. Firstly, an extended Kalman filter was constructed in LOS (line of sight) coordinate system to estimate the guidance signal based on the information measured by strap-down seeker and inertial measurement unit. Secondly, an optimal guidance law which could reduce the target maneuvering and guidance system dynamics was proposed. Thirdly, three-loop acceleration autopilot with pseudo-angle of attack feedback was presented to control the flight vehicle. Finally, the proposed methods were simulated under typical condition. The simulation results demonstrated that the proposed methods were valid, and good performance could be achieved by the guidance and control method with the guidance signal estimated by the extended Kalman filter.

Development of a MRE isolation system for strapdown inertial measurement unit

At present, the inertial measurement unit (IMU) is widely used in various industrial systems. The precision and service life of IMU declines due to the adverse influences of environmental vibration. Therefore, a magnetorheological elastomer (MRE) isolation system is designed to attenuate the severe vibration of the devices in three directions. Moreover, a phase-based controller (PBC) is proposed to achieve the real-time control of the isolation system. The performances of the PBC and the on-off controller are simulated for comparison under the sinusoidal and swept excitations, respectively. Finally, experiments are conducted to evaluate and verify the effectiveness of the PBC. The experimental results demonstrate that the acceleration root-mean-square of IMU system with PBC decreases by 17.67%. This study is of great significance to the design and engineering applications of the IMU isolation system.

Fault Detection and Isolation for Redundant Inertial Measurement Unit under Quantization

Fault detection and isolation with redundant strapdown inertial measurement unit is critical for ensuring the reliability of the guidance or navigation system in the fields of both aeronautics and astronautics. Although the parity space approach is used widely, it cannot detect the soft fault which affects navigation performance under pulse quantization. This paper develops the three-channel filters to detect the soft fault and conducts theoretical implementation. The constraint conditions of their parameters are explored and the influence of the weight of different ratios is analyzed. The Monte Carlo simulation is carried out in order to verify the validity of the fault detection and isolation method. The simulation results and their analysis provide a theoretical reference for fault detection and isolation with redundant strapdown inertial measurement unit.

Inertial measuring units for future-generation aerospace products: fault-tolerance

A Strapdown Inertial Measurement Unit (SIMU) with structural redundancy intended for improving fault-tolerance and accuracy of inertial navigation systems for space applications is considered. The SIMU includes six angular rate sensors and six accelerometers, which allows for identification and correction of one fault with high probability and two faults with lower probability for each type of sensor. Known theoretical and practical techniques developed and used in this area are briefly described. The problem of optimization of measurement axes orientation is considered. The accuracy of estimation of the measured vector projections in the orthogonal instrument coordinate system serves as the criterion of optimization. A solution of this problem for no faults, one fault, and two faults is proposed. Algorithms of failure detection, identification and correction (FDIC) are analyzed. The results of testing FDIC basic algorithms with the help of mathematical simulation are considered. Optimal measurement axes configurations are compared with each other from the FDIC efficiency point of view. It is shown that neither of the methods yields 100-percent correct diagnostics not only for two faults but for one fault as well. Possible sources of incorrect diagnostics are analyzed.

Analysis and design of an attitude calculation algorithm based on elman neural network for SINS

In view of the shortcomings of strapdown inertial measurement unit (IMU) such as large noise and error accumulation, poor precision of traditional attitude calculation algorithms and poor adaptability to environment, this paper proposes an attitude calculation algorithm aided by Elman neural network. For multi-sensor information fusion, not every neural network is applicable, but the Elman neural network structure contains a receiving layer, which stores the information of the previous hidden layer, this structural feature enables the Elman neural network to predict in continuous signal. The simulation results show the effectiveness of the algorithm and improve the accuracy and adaptability of the algorithm.

Research into Kinect/Inertial Measurement Units Based on Indoor Robots.

As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot’s movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.

Research on the Adaptive Damping Method of Strap-Down Inertial Measurement Unit Based on the Magneto Rheological Technology

To improve the output accuracy of strap-down inertial measurement unit which is in compound dynamic environment of missile which has a high acceleration, strong impact, and high vibration, an adaptive damping method of taking the magneto rheological elastomer as the vibration damper is designed. This method takes the error between the vibration response of the missile and the dynamic response of SIMU as the performance index of optimal control. By optimal control, the stiffness and damping of the magneto rheological elastomer are automatically adjusted, the vibration response of the SIMU is controlled, and the output accuracy of SIMU is improved. Results of experiments show that the method solves the problem that the stiffness and damping of the SIMU damping system could not be changed in real time to adapt to the dynamic environment, and there is almost no time delay and this has an obvious damping effect.

A New Decoupling Matrix Construction Method for Fault Detection and Isolation of a Redundant Strapdown Inertial Measurement Unit

A New Decoupling Matrix Construction Method for Fault Detection and Isolation of a Redundant Strapdown Inertial Measurement Unit