Abstract
Real-time positioning (RTP) is a technique used to locate the static or moving objects with an error as small as possible. Although significant work has been conducted, and several kinds of methodologies are planned on high-precision positioning and surveying applications, there is, however, a substantial scope for new techniques that would afford additional communicational and navigational assistance. Therefore, in this letter, an adaptive Kalman Filter (KF) based on the singular spectrum analysis (SSA) forecasting method is proposed for RTP. First, an explanation of KF is introduced, and then the SSA method is incorporated into KF for 3-D state estimation. RTP positioning test has been carried out to demonstrate the accuracy of positioning for the proposed algorithm. The simulation result reveals that the implication of SSA with KF has high-precision estimates than the only common discrete KF model.
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