scholarly journals Analog and Photon Signal Splicing for CO2-DIAL Based on Piecewise Nonlinear Algorithm

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 109
Author(s):  
Chengzhi Xiang ◽  
Ailin Liang

In the CO2 differential absorption lidar (DIAL) system, signals are simultaneously collected through analog detection (AD) and photon counting (PC). These two kinds of signals have their own characteristics. Therefore, a combination of AD and PC signals is of great importance to improve the detection capability (detection range and accuracy) of CO2-DIAL. The traditional signal splicing algorithm cannot meet the accuracy requirements of CO2 inversion due to unreasonable data fitting. In this paper, a piecewise least square splicing algorithm is developed to make signal splicing more flexible and efficient. First, the lidar signal is segmented, and according to the characteristics of each signal, the best fitting parameters are obtained by using the least square fitting with different steps. Then, all the segmented and fitted signals are integrated to realize the effective splicing of the near-field AD signal and the far-field PC signal. A weight gradient strategy is also adopted in signal splicing, and the weights of the AD and PC signals in the spliced signal change with the height. The splicing effect of the improved algorithm is evaluated by the measured signal, which are obtained in Wuhan, China, and the splice of the AD and PC signals in the range of 800–1500 m are completed. Compared with the traditional method, the evaluation parameter R2 and the residual sum of squares of the spliced signal are greatly improved. The linear relationship between the AD and PC signals is improved, and the fitting R2 of differential absorption optical depth reaches 0.909, indicating that the improved signal splicing algorithm can well splice the near-field AD signal and the far-field PC signal.

Author(s):  
Mondher Dhaouadi ◽  
M. Mabrouk ◽  
T. Vuong ◽  
A. Ghazel

1998 ◽  
Vol 38 (10) ◽  
pp. 323-330
Author(s):  
Philip J. W. Roberts

The results of far field modeling of the wastefield formed by the Sand Island, Honolulu, ocean outfall are presented. A far field model, FRFIELD, was coupled to a near field model, NRFIELD. The input data for the models were long time series of oceanographic observations over the whole water column including currents measured by Acoustic Doppler Current Profilers and density stratification measured by thermistor strings. Thousands of simulations were made to predict the statistical variation of wastefield properties around the diffuser. It was shown that the visitation frequency of the wastefield decreases rapidly with distance from the diffuser. The spatial variation of minimum and harmonic average dilutions was also predicted. Average dilution increases rapidly with distance. It is concluded that any impact of the discharge will be confined to a relatively small area around the diffuser and beach impacts are not likely to be significant.


2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dmitry M. Davydov ◽  
Andrey Boev ◽  
Stas Gorbunov

AbstractSituational or persistent body fluid deficit (i.e., de- or hypo-hydration) is considered a significant health risk factor. Bioimpedance analysis (BIA) has been suggested as an alternative to less reliable subjective and biochemical indicators of hydration status. The present study aimed to compare various BIA models in the prediction of direct measures of body compartments associated with hydration/osmolality. Fish (n = 20) was selected as a biological model for physicochemically measuring proximate body compartments associated with hydration such as water, dissolved proteins, and non-osseous minerals as the references or criterion points. Whole-body and segmental/local impedance measures were used to investigate a pool of BIA models, which were compared by Akaike Information Criterion in their ability to accurately predict the body components. Statistical models showed that ‘volumetric-based’ BIA measures obtained in parallel, such as distance2/Rp, could be the best approach in predicting percent of body moisture, proteins, and minerals in the whole-body schema. However, serially-obtained BIA measures, such as the ratio of the reactance to resistance and the resistance adjusted for distance between electrodes, were the best fitting in predicting the compartments in the segmental schema. Validity of these results should be confirmed on humans before implementation in practice.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 28413-28420
Author(s):  
Hojun Lee ◽  
Jongmin Ahn ◽  
Yongcheol Kim ◽  
Jaehak Chung

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