The performance of conventional direction of arrival(DOA)method is greatly affected by the uncertainty of wave velocity in underwater environment.To solve this problem,an acoustic velocity-independent method is propos...The performance of conventional direction of arrival(DOA)method is greatly affected by the uncertainty of wave velocity in underwater environment.To solve this problem,an acoustic velocity-independent method is proposed to estimate the underwater DOA using two arbitrary intersecting uniform linear arrays in this study.By introducing the additional array compared to the conventional DOA methods,the proposed algorithm can make its performance independent of the acoustic velocity through the geometric relationship between those two arrays.The simulation results demonstrate that the proposed method is more accurate and robust than other methods in an unknown sound velocity.展开更多
This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method f...This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.展开更多
基金This work was supported by National Natural Science Foundation of China(No.61871191)Natural Science Foundation of Guangdong Province(Nos.2016A020222003 and 2017A030313368)Science and Technology Planning Project of Guangzhou(No.201804010209).
文摘The performance of conventional direction of arrival(DOA)method is greatly affected by the uncertainty of wave velocity in underwater environment.To solve this problem,an acoustic velocity-independent method is proposed to estimate the underwater DOA using two arbitrary intersecting uniform linear arrays in this study.By introducing the additional array compared to the conventional DOA methods,the proposed algorithm can make its performance independent of the acoustic velocity through the geometric relationship between those two arrays.The simulation results demonstrate that the proposed method is more accurate and robust than other methods in an unknown sound velocity.
基金supported by the National Natural Science Foundation of China(6137116961179006)+1 种基金the Jiangsu Postdoctoral Research Funding Plan(1301013B)the Nanjing University of Aeronautics and Astronautics Funding(NZ2013208)
文摘This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.
