Integrity of an integrated GPS/INS system in the presence of slowly growing errors. Part II: analysis
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This is the second of two consecutive papers (Part II) in this journal on the monitoring of the integrity of integrated GPS/INS systems. Part I established that the worst class of error for an integrated system in terms of failure detection performance is that of slowly growing errors (SGEs). It was also concluded that among the integration architectures, the tightly coupled architecture provides the best mechanism to tackle SGEs due to its simpler structure and accessibility to the relevant measurements. In a subsequent comparison of the existing integrity algorithms, the multiple solution separation (MSS) and autonomous integrity monitoring by extrapolation (AIME) methods were selected for further analysis because of their representative characteristics of the current integrity algorithms. This paper carries out a detailed investigation of the capability of the MSS and AIME algorithms to deal with the SGEs, using a realistic simulation platform and limited real data analysis. Results show that although it is possible for the existing algorithms to detect SGEs, the time it takes to detect them varies inversely to the rate of growth of the SGE. A new algorithm is developed to deal with this based on the concept of rate detection. Simulation results show that the new algorithm can detect SGEs earlier than the current algorithms. This is validated by preliminary tests with real data.
KeywordsKalman Filter Inertial Measurement Unit Measurement Matrix Inertial Navigation System Simulation Platform
The authors acknowledge the financial support of Government of Pakistan, Imperial College London and Dr Imran Iqbal Bhatti. The real GPS and INS data used in this paper was provided by the SPACE project—a consortium involving Imperial College London, The University of Nottingham, UCL and the University of Leeds. The assistance rendered by Dr Chris Hide (IESSG, Nottingham) with data manipulation and simulation, is acknowledged.
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