Multiple IMU system test plan, volume 4

Operating procedures for this redundant system are described. A test plan is developed with two objectives. First, performance of the hardware and software delivered is demonstrated. Second, applicability of multiple IMU systems to the space shuttle mission is shown through detailed experiments with FDI algorithms and other multiple IMU software: gyrocompassing, calibration, and navigation. Gimbal flip is examined in light of its possible detrimental effects on FDI and navigation. For Vol. 3, see N74-10296

Multiple IMU system hardware interface design, volume 2

The design of each system component is described. Emphasis is placed on functional requirements unique in this system, including data bus communication, data bus transmitters and receivers, and ternary-to-binary torquing decision logic. Mechanization drawings are presented

SIRU utilization. Volume 1: Theory, development and test evaluation

The theory, development, and test evaluations of the Strapdown Inertial Reference Unit (SIRU) are discussed. The statistical failure detection and isolation, single position calibration, and self alignment techniques are emphasized. Circuit diagrams of the system components are provided. Mathematical models are developed to show the performance characteristics of the subsystems. Specific areas of the utilization program are identified as: (1) error source propagation characteristics and (2) local level navigation performance demonstrations

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

Space shuttle avionics system

The Space Shuttle avionics system, which was conceived in the early 1970's and became operational in the 1980's represents a significant advancement of avionics system technology in the areas of systems and redundacy management, digital data base technology, flight software, flight control integration, digital fly-by-wire technology, crew display interface, and operational concepts. The origins and the evolution of the system are traced; the requirements, the constraints, and other factors which led to the final configuration are outlined; and the functional operation of the system is described. An overall system block diagram is included

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

Preliminary design of a redundant strapped down inertial navigation unit using two-degree-of-freedom tuned-gimbal gyroscopes

This redundant strapdown INS preliminary design study demonstrates the practicality of a skewed sensor system configuration by means of: (1) devising a practical system mechanization utilizing proven strapdown instruments, (2) thoroughly analyzing the skewed sensor redundancy management concept to determine optimum geometry, data processing requirements, and realistic reliability estimates, and (3) implementing the redundant computers into a low-cost, maintainable configuration

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

Redundant MEMS-IMU integrated with GPS for Performance Assessment in Sports

In this article, we investigate two different algorithms for the integration of GPS with redundant MEMS-IMUs. Firstly, the inertial measurements are combined in the observation space to generate a synthetic set of data which is then integrated with GPS by the standard algorithms. In the second approach, the method of strapdown navigation needs to be adapted in order to account for the redundant measurements. Both methods are evaluated in experiments where redundant MEMSIMUs are fixed in different geometries: orthogonallyredundant and skew-redundant IMUs. For the latter configuration, the performance improvement using a synthetic IMU is shown to be 30% on the average. The extended mechanization approach provides slightly better results (about 45% improvement) as the systematic errors of the individual sensors are considered separately rather than their fusion when forming compound measurements. The maximum errors are shown to be reduced even by a factor of 2

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