Data fusion methodologies for multisensor aircraft navigation systems

摘要

The thesis covers data fusion for aircraft navigation systems in distributed sensorsystems. Data fusion methodologies are developed for the design, development,analysis and simulation of multisensor aircraft navigation systems. The problems ofsensor failure detection and isolation (FDI), distributed data fusion algorithms andinertial state integrity monitoring in inertial network systems are studied.Various existing integrated navigation systems and Kalman filter architectures arereviewed and a new generalised multisensor data fusion model is presented for thedesign and development of multisensor navigation systems. Normalised navigationalgorithms are described for data fusion filter design of inertial network systems.A normalised measurement model of skewed redundant inertial measurement units(SRIMU) is presented and performance criteria are developed to evaluate optimalconfigurations of SRIMUs in terms of the measurement accuracy and FDI capability.Novel sensor error compensation filters are designed for the correction of SRIMUmeasurement errors. Generalised likelihood ratio test (GLRT) methods are improvedto detect various failure modes, including short time and sequential moving-windowGLRT algorithms.State-identical and state-associated fusion algorithms are developed for two forms ofdistributed sensor network systems. In particular, innovative inertial network sensingmodels and inertial network fusion algorithms are developed to provide estimates ofinertial vector states and similar node states. Fusion filter-based integrity monitoringalgorithms are also presented to detect network sensor failures and to examine theconsistency of node state estimates in the inertial network system.The FDI and data fusion algorithms developed in this thesis are tested and theirperformance is evaluated using a multisensor software simulation system developedduring this study programme. The moving-window GLRT algorithms for optimalSRIMU configurations are shown to perform well and are also able to detect jumpand drift failures in an inertial network system. It is concluded that the inertialnetwork fusion algorithms could be used in a low-cost inertial network system andare capable of correctly estimating the inertial vector states and the node states.