• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.7
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• pp.678-684
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• 2009

Many researches on the GNSS integer ambiguity resolution methods for precise positioning and attitude determination applications have been done. However, by the time invariant property of the integer ambiguity, the reuse of integer ambiguity without performing time consuming integer search procedure is possible. In this paper, a new efficient integer ambiguity propagation method is proposed. The initial integer ambiguity can be determined using the famous LAMBDA method and it is propagated with the propagation method. The proposed method can reconfigure the integer ambiguity using the previous epoch's integer ambiguity and new carrier phase measurements under environmental variations such as geometry changes, signal blockage and reacquisition. Experiments with real measurements show the proposed method can determine an integer ambiguity effectively.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.26-37
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• 2004

Consistent and realistic error covariance information is important for position estimation, error analysis, fault detection, and integer ambiguity resolution for differential GNSS. In designing a position domain carrier-smoothed-code filter where incremental carrier phases are used for time-propagation, formulation of consistent error covariance information is not easy due to being bounded and temporal correlation of propagation noises. To provide consistent and correct error covariance information, this paper proposes two recursive filter algorithms based on carrier-smoothed-code techniques: (a) the stepwise optimal position projection filter and (b) the stepwise unbiased position projection filter. A Monte-Carlo simulation result shows that the proposed filter algorithms actually generate consistent error covariance information and the neglection of carrier phase noise induces optimistic error covariance information. It is also shown that the stepwise unbiased position projection filter is attractive since its performance is good and its computational burden is moderate.