Flight route EDR estimation using MHE to fuse three-dimensional wind information in the QAR data analysis - Hongping Wei; Haosen Li; Weiling Liu; Zibo Zhuang; Jun Chen (PLoS ONE, 2025)
To address the problem that vertical wind data can provide information only on turbulence fluctuations in the vertical direction, meaning that the consideration of insufficiently compre-hensive turbulence information leads to low accuracy in eddy dissipation rate(EDR) estimation based on vertical wind (VWE), the paper proposes a flight route EDR estimation using MHE to fuse three-dimensional wind information in the Quick Access Recorder(QAR) data analysis. Quality control is performed on QAR data to eliminate irrelevant features for computing vertical wind and the two horizontal wind components. The corresponding formulas are then applied to obtain three-dimensional wind data information. Subsequently, a multi-head attention mechanism is employed to quantify the relationship between three-dimensional wind characteristics and the feature matrix (vertical acceleration). This process generates feature fusion weights, which are mapped onto the three-dimensional wind matrix and used to convert the three-dimensional wind data into one-dimensional wind data, thereby achieving the fusion of three-dimensional wind features. Finally, through maximum likelihood estimation(MLE) combine the new wind data in the frequency domain, the estimation of the flight route EDR is realized. Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. The proposed algorithm provides highly accurate EDR estimations for flight paths and demonstrates good practical applicability for assessing turbulence intensity along flight routes, thereby enhancing the safety of aircraft during flight.