AIAA SCITECH 2022 Forum 2022
DOI: 10.2514/6.2022-1759
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An INS/GNSS fusion architecture in GNSS denied environment using gated recurrent unit

Abstract: One of the most used Position, Navigation and Timing (PNT) technology of the 21st century is Global Navigation Satellite Systems (GNSS). GNSS signals are affected by urban canyons that limit line-of-sight and reduce satellite availability to receivers. Smart cities are expected to adopt autonomous Unmanned Aerial Vehicles (UAV) operations for critical missions such as transportation of organs which are time-sensitive. Therefore, higher accuracy for position and velocity information is required. This paper inve… Show more

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Cited by 17 publications
(13 citation statements)
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“…GRU, on the other hand, is more capable of determining non-linear relationships between the features and using previous state information to provide greater accuracy. This is seen in paper [1], where GRU provided better correlation in cases where the relationship between input features and the outputs was highly non-linear. Table 1 compares the mean, standard deviation, and 95% between the original output (Ublox F9P), tree, KNN, SVM, and GRU.…”
Section: Resultsmentioning
confidence: 78%
See 1 more Smart Citation
“…GRU, on the other hand, is more capable of determining non-linear relationships between the features and using previous state information to provide greater accuracy. This is seen in paper [1], where GRU provided better correlation in cases where the relationship between input features and the outputs was highly non-linear. Table 1 compares the mean, standard deviation, and 95% between the original output (Ublox F9P), tree, KNN, SVM, and GRU.…”
Section: Resultsmentioning
confidence: 78%
“…Since the launch of the Global Positioning System (GPS) in 1983, GNSS has been used in a variety of applications and devices such as navigation for vehicles both on the ground and in the air. [1] [2] Currently, six GNSS systems exist. All these systems work with similar principles to provide positioning information to the receivers.…”
Section: Introductionmentioning
confidence: 99%
“…The GRU model can be describe as the follow equations [13]: z t " σ pW z ¨rh t´1 , X t s `bz q r t " σ pW r ¨rh t´1 , X t s `br q ĥt " tanh pW ¨rr t d h t´1 , X t s `bq…”
Section: Figure 1: Gru Architecturementioning
confidence: 99%
“…The issue with RNN is that it has difficulties solving problems that require learning long-term dependencies due to the gradient of the loss function decaying. [13] applied RNN and its variations long-short term memory network (LSTM) and gated recurrent unit (GRU) for INS navigation when GNSS fails at open sky environment. The results showed that Both LSTM and GRU outperforms RNN with less computational efficiency.…”
Section: ‚ Introductionmentioning
confidence: 99%
“…Machine learning has been used for trajectory inference using measurement data [12], [13] with interesting results. Physics informed neural networks [14] uses prior knowledge of the physics of the system with a neural network to infer the trajectory.…”
Section: Introductionmentioning
confidence: 99%