Fourth-Order Cumulants Beamforming for Direction of Arrival Estimation

2014 ◽  
Vol 602-605 ◽  
pp. 3384-3387
Author(s):  
Ting Ting Li
Keyword(s):  
Spatial Resolution ◽  
Fourth Order ◽  
High Spatial Resolution ◽  
Rapid Development ◽  
Direction Of Arrival ◽  
Estimation Methods ◽  
Direction Of Arrival Estimation ◽  
Robust Performance ◽  
Resolution Analysis ◽  
Simulation Results

With the rapid development of DOA (direction-of-arrival) estimation methods, the existing beamforming technologies still have the problem of a way to balance high spatial resolution and robust performance. The aperture extension characteristics of fourth-order cumulants is used to raise the spatial resolution of the array in this paper. By using the structure of minimum redundancy array, the calculation of the fourth-order cumulants matrix can be reduced. Simulations of the properties of fourth–order cumulants beamforming method are analyzed in this paper, including the resolution analysis, multi-sources analysis and error analysis. Simulation results show that the fourth-order cumulants beamforming method has a higher spatial resolution than the conventional beamforming method without increasing the number of the array sensors.

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

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.

Glucose and Lactate Miniaturized Biosensors for SECM-Based High-Spatial Resolution Analysis: A Comparative Study

ACS Sensors ◽  
2017 ◽  
Vol 2 (9) ◽  
pp. 1310-1318 ◽  
Author(s):  
Alice Soldà ◽  
Giovanni Valenti ◽  
Massimo Marcaccio ◽  
Marco Giorgio ◽  
Pier Giuseppe Pelicci ◽  
...  
Keyword(s):  
Comparative Study ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Resolution Analysis

scholarly journals Evaluation of Six High-Spatial Resolution Clear-Sky Surface Upward Longwave Radiation Estimation Methods with MODIS

2020 ◽  
Vol 12 (11) ◽  
pp. 1834
Author(s):  
Boxiong Qin ◽  
Biao Cao ◽  
Hua Li ◽  
Zunjian Bian ◽  
Tian Hu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Hybrid Methods ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Estimation Methods ◽  
Mean Bias Error ◽  
Clear Sky ◽  
Surface Radiation Budget

Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we comprehensively evaluated six SULR estimation methods, including the temperature-emissivity physical methods with the input of the MYD11/MYD21 (TE-MYD11/TE-MYD21), the hybrid methods with top-of-atmosphere (TOA) linear/nonlinear/artificial neural network regressions (TOA-LIN/TOA-NLIN/TOA-ANN), and the hybrid method with bottom-of-atmosphere (BOA) linear regression (BOA-LIN). The recently released MYD21 product and the BOA-LIN—a newly developed method that considers the spatial heterogeneity of the atmosphere—is used initially to estimate SULR. In addition, the four hybrid methods were compared with simulated datasets. All the six methods were evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Surface Radiation Budget Network (SURFRAD) in situ measurements. Simulation analysis shows that the BOA-LIN is the best one among four hybrid methods with accurate atmospheric profiles as input. Comparison of all the six methods shows that the TE-MYD21 performed the best, with a root mean square error (RMSE) and mean bias error (MBE) of 14.0 and −0.2 W/m2, respectively. The RMSE of BOA-LIN, TOA-NLIN, TOA-LIN, TOA-ANN, and TE-MYD11 are equal to 15.2, 16.1, 17.2, 21.2, and 18.5 W/m2, respectively. TE-MYD21 has a much better accuracy than the TE-MYD11 over barren surfaces (NDVI < 0.3) and a similar accuracy over non-barren surfaces (NDVI ≥ 0.3). BOA-LIN is more stable over varying water vapor conditions, compared to other hybrid methods. We conclude that this study provides a valuable reference for choosing the suitable estimation method in the SULR product generation.

scholarly journals AR Model-Based Direction-of-Arrival Estimation of Coherent Signals in the Presence of Unknown Mutual Coupling

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Zhi-Chao Sha ◽  
Zhang-Meng Liu ◽  
Zhi-Tao Huang ◽  
Yi-Yu Zhou
Keyword(s):  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Ar Model ◽  
Estimation Accuracy ◽  
Direction Of Arrival Estimation ◽  
Coherent Signals ◽  
Model Based ◽  
Mixing Matrix ◽  
Simulation Results

This paper addresses the problem of direction-of-arrival (DOA) estimation of coherent signals in the presence of unknown mutual coupling, and an autoregression (AR) model-based method is proposed. The effects of mutual coupling can be eliminated by the inherent mechanism of the proposed algorithm, so the DOAs can be accurately estimated without any calibration sources. After the mixing matrix is estimated by independent component analysis (ICA), several parameter equations are established upon the mixing matrix. Finally, all DOAs of coherent signals are estimated by solving these equations. Compared with traditional methods, the proposed method has higher angle resolution and estimation accuracy. Simulation results demonstrate the effectiveness of the algorithm.

Happy Jack Uraninite: A New Reference Material for High Spatial Resolution Analysis of U‐Rich Matrices

2019 ◽  
Vol 44 (1) ◽  
pp. 125-132
Author(s):  
Corinne Dorais ◽  
Antonio Simonetti ◽  
Loretta Corcoran ◽  
Tyler L. Spano ◽  
Peter C. Burns
Keyword(s):  
Reference Material ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Resolution Analysis
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