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Inertial Navigation System (INS) and Global Positioning System (GPS) technologies have been widely used in a variety of positioning and navigation applications. Because the GPS and the INS complement each other, it is common practice to integrate the two systems. The advantages of GPS/INS integration is that the integrated solution can provide continuous navigation capability even during GPS outages. It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. To solve this problem, the authors propose to use the Bayesian Bootstrap Filtering (BBF) for GPS/INS integration.
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