Failure detection and isolation analysis of a redundant strapdown inertial measurement unit

The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures

Optimal Configuration of Redundant Inertial Sensors for Navigation and FDI Performance

This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method

중첩 관성 센서에서 레버암 효과 완화의 새로운 기법

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 항공우주공학과, 2021. 2. 박찬국.This masters thesis presents two novel methods to mitigate lever arm effect in Redundant Inertial Measurement Units (RIMUs), each with different approaches. With the presence of a lever arm for each sensing axis, the unexpected accelerations such as Euler and centrifugal accelerations are added to the measurements through rotational motion, resulting in an estimation error of linear acceleration. Therefore, it was previously considered as the best option to minimize the length of the lever arm and compensate the lever arm effect from the accelerometer measurements. However, this approach cannot completely remove the estimation error as the compensated value is based on the estimated angular rates, where the magnitude of the error becomes more apparent with a RIMU composed of low-grade gyroscopes that shows a higher noise level. In order to solve this problem, we propose two methods that can mitigate estimation error using the specific arrangement of the lever arm vectors and the concentrated likelihood method-based nonlinear least squares (NLS). By the proposed methods, the accuracy in compensating the lever arm effect can be increased by placing the lever arm vectors symmetrically or using the information from accelerometers when estimating angular rates. Besides, the suggested methods each have their own advantages in computational efficiency and overall navigation performance, compared to previous method. The effectiveness of the proposed methods is verified through simulations including misalignments of each redundant sensor.본 논문에서는 중첩 관성 센서에서 발생하는 레버암 효과를 완화하기 위한 두 가지 새로운 기법을 제안한다. 중첩 관성 센서에서는 각 센서에 존재하는 레버암에 의해 회전 운동이 가해질 때 마다 오일러 힘이나 원심력과 같이 원치 않는 비력이 가속도 측정치에 섞여 추정 오차를 유발하게 된다. 따라서, 이를 해결하기 위해 제시된 최선의 방법은 길이가 최소화된 레버암에 의한 항 가속도 측정치로부터 보상한 값으로 추정하는 것이었다. 그러나, 보상하는 값이 노이즈가 섞인 각속도 추정치에 기반하기 때문에 기존 접근법은 추정 오차를 완전하게 제거할 수 없으며, 저가형 IMU와 같이 자이로스코프의 잡음 수준이 큰 경우에 대해 오차가 더 커지는 것을 확인할 수 있다. 이러한 문제를 해결하기 위해, 레버암 벡터를 특정한 형태로 배치시키거나 집중 우도 방법에 기반한 비선형 최소 자승 방식을 사용하여 추정 오차를 제거할 수 있는 방식을 제안한다. 제안된 방법에 따르면, 레버암의 대칭적인 배치 형태를 사용하거나 가속도계의 정보를 사용하여 각속도의 추정 오차를 우선적으로 줄여 궁극적으로 가속도 추정에 사용하는 보상하는 값의 정확도를 높이는 방식으로 레버암 효과를 줄일 수 있다. 또한, 제안된 방법은 각각 연산량의 효율성과 전반적인 관성항법 성능의 향상에서 추가적인 이점이 있다. 제안한 방식의 효과는 비정렬 오차를 포함한 시뮬레이션으로 검증하였다.Chapter 1 Introduction 1 1.1 Motivation and background 1 1.2 Objectives and contributions 3 Chapter 2 Related Works 6 2.1 Inertial navigation system 6 2.1.1 Frame mechanization 7 2.1.2 Attitude update algorithm 10 2.1.3 Velocity and position update algorithm 16 2.2 Redundant inertial measurement units (RIMU) 19 2.2.1 Sensing axes configuration for optimal navigation performance 19 2.2.2 Sensing axes configuration for optimal FDI performance 24 Chapter 3 Inertial Navigation based on RIMU 27 3.1 Navigation performance analysis 28 3.1.1 Performance enhancement according to the number of redundant sensors 28 3.1.2 Performance degradation due to the presence of the lever arm 30 3.1.3 Lever arm optimization for minimizing the lever arm effect 33 Chapter 4 Mitigating Lever Arm Effect in RIMU 37 4.1 Symmetric lever arm configuration based on least squares method 37 4.1.1 Lever arm configuration 37 4.1.2 Measurement fusion 39 4.1.3 Performance analysis 42 4.2 Nonlinear least squares method 43 4.2.1 Lever arm configuration 43 4.2.2 Measurement fusion 45 4.2.3 Performance analysis 48 4.3 Simulation results 51 4.3.1 RIMU configuration 51 4.3.2 Navigation performance comparison 53 Chapter 5 Conclusion 62 5.1.1 Conclusion and summary 62 5.1.2 Future works 63 Bibliography 64 국문초록 68Maste

Best Sensor Configuration and Accommodation Rule Based on Navigation Performance for INS with Seven Inertial Sensors

This paper considers the best sensor configuration and fault accommodation problem for inertial navigation systems which use seven inertial sensors such as gyroscopes and accelerometers. We prove that when six inertial sensors are used, the isolation of a double fault cannot be achieved for some combinations of fault magnitudes, whereas when seven inertial sensors are used, the isolation of any double fault can be achieved. There are many configurations which provide the minimum position errors. This paper proposes four configurations which show the best navigation performance and compares their FDI performances. Considering the FDI performance and the complexity of the accommodation rule, we choose one sensor configuration and provide accommodation rules for double faults. A Monte Carlo simulation is performed to show that the accommodation rules work well

Kernel-based fault diagnosis of inertial sensors using analytical redundancy

Kernel methods are able to exploit high-dimensional spaces for representational advantage, while only operating implicitly in such spaces, thus incurring none of the computational cost of doing so. They appear to have the potential to advance the state of the art in control and signal processing applications and are increasingly seeing adoption across these domains. Applications of kernel methods to fault detection and isolation (FDI) have been reported, but few in aerospace research, though they offer a promising way to perform or enhance fault detection. It is mostly in process monitoring, in the chemical processing industry for example, that these techniques have found broader application. This research work explores the use of kernel-based solutions in model-based fault diagnosis for aerospace systems. Specifically, it investigates the application of these techniques to the detection and isolation of IMU/INS sensor faults – a canonical open problem in the aerospace field. Kernel PCA, a kernelised non-linear extension of the well-known principal component analysis (PCA) algorithm, is implemented to tackle IMU fault monitoring. An isolation scheme is extrapolated based on the strong duality known to exist between probably the most widely practiced method of FDI in the aerospace domain – the parity space technique – and linear principal component analysis. The algorithm, termed partial kernel PCA, benefits from the isolation properties of the parity space method as well as the non-linear approximation ability of kernel PCA. Further, a number of unscented non-linear filters for FDI are implemented, equipped with data-driven transition models based on Gaussian processes - a non-parametric Bayesian kernel method. A distributed estimation architecture is proposed, which besides fault diagnosis can contemporaneously perform sensor fusion. It also allows for decoupling faulty sensors from the navigation solution

중첩 관성센서의 고장검출 및 판별 성능에 대한 기하학적 분석 및 최적화

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2016. 8. 박찬국.This thesis suggests optimal configurations for redundant inertial sensors with analysis of geometric parameters with respect to Fault Detection and Identification (FDI). To define FDI performance of each configuration, a performance index for FDI method based on Parity Space Approach (PSA) is applied. Even though this index is dependent on the geometry of sensor configurations, however, it is hard to analyze the performance index directly since it is expressed in the null space of Direction Cosine Matrix (DCM) for the configurations. To solve this limitation, a modified form of the FDI performance index is presented as a function of geometric parameter of the configurations. It makes the FDI performance analysis and optimization of the configurations much easier. Additionally, the optimizations of configurations such as platonic solids, single cones and dual cones are conducted by the modified performance index. Finally, the FDI performance of each configuration is compared with others by the FDI performance index. The comparison result shows that the optimized dual conic configurations achieve FDI performance superior to the one of other configurations. The same results are also confirmed by simulations and experiments on each configuration.Chapter 1.Introduction 1 1.1 Motivation and Background 1 1.2 Objecctives and Contriburions 4 1.3 Organization 5 Chapter 2. Problem Formulation 6 2.1 Sensor Measurement Model 6 2.2 GNC Performance Index 7 2.3 FDI Performance Index 9 2.4 Limitations of Previous Research 12 Chapter 3. Performance Index Modification 14 3.1 Geometric Parameter of Sensor Configuration 14 3.2 Modified Performance Index 15 Chapter 4. Performance Index Optimization 17 4.1 Platonic Solid Configuration 17 4.2 Single Conic Configuration 22 4.3 Dual Conic Configuration 26 4.4 Performance Index Comparison 33 4.5 Summary 35 Chapter 5. Simulation and Experiment 36 5.1 Numerical Simulation 36 5.2 Experiment on Sensor Frame 40 Chapter 6. Conclusions 46 Bibliography 48 국문 초록 51Maste

SIRU development. Volume 1: System development

A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results

Distributed data fusion algorithms for inertial network systems

New approaches to the development of data fusion algorithms for inertial network systems are described. The aim of this development is to increase the accuracy of estimates of inertial state vectors in all the network nodes, including the navigation states, and also to improve the fault tolerance of inertial network systems. An analysis of distributed inertial sensing models is presented and new distributed data fusion algorithms are developed for inertial network systems. The distributed data fusion algorithm comprises two steps: inertial measurement fusion and state fusion. The inertial measurement fusion allows each node to assimilate all the inertial measurements from an inertial network system, which can improve the performance of inertial sensor failure detection and isolation algorithms by providing more information. The state fusion further increases the accuracy and enhances the integrity of the local inertial states and navigation state estimates. The simulation results show that the two-step fusion procedure overcomes the disadvantages of traditional inertial sensor alignment procedures. The slave inertial nodes can be accurately aligned to the master node