DOA Estimation for Noncircular Signals under Strong Impulsive Noise

Direction of arrival (DOA) estimation under impulsive noise has been an important research area. Most present methods are based on the fractional lower order statistics, while the computation load is heavy, and the estimation property degrades when the noise impact is strong. To get around this conundrum, a novel solution is presented, where the noncircular signals are introduced for modelling, a filtering preprocessing method is introduced to eliminate the impulsive noise, and a matrix reconstruction method is presented to smooth the residual noise. Firstly, the filtering preprocessing method is implemented to cut out the impulsive noise. Secondly, the characteristic of the noncircular signal is utilized to extend the array aperture. Thirdly, a new matrix reconstruction method is proposed to smooth the residual noise. Finally, the classical ESPRIT algorithm is adopted to estimate the DOAs. Simulations under different comparison of dimensions are conducted, and the mainstream methods are selected as comparison. The simulation results illustrate the outstanding performance of the proposed method in a strong impulsive noise environment.

[1]  Yinrui Gao,et al.  Generalized covariance-based ESPRIT-like solution to direction of arrival estimation for strictly non-circular signals under Alpha-stable distributed noise , 2021, Digit. Signal Process..

[2]  Haiyun Xu,et al.  A Transformed Coprime Array With Reduced Mutual Coupling for DOA Estimation of Non-Circular Signals , 2021, IEEE Access.

[3]  Mark Wagner,et al.  Gridless DOA Estimation and Root-MUSIC for Non-Uniform Linear Arrays , 2020, IEEE Transactions on Signal Processing.

[4]  Wei Zhang,et al.  An Improved ESPRIT-Like Algorithm for Coherent Signals DOA Estimation , 2020, IEEE Communications Letters.

[5]  Jiacheng Zhang,et al.  Bounded non-linear covariance based ESPRIT method for noncircular signals in presence of impulsive noise , 2019, Digit. Signal Process..

[6]  M. Diao,et al.  Direction finding of bistatic MIMO radar based on quantum-inspired grey wolf optimization in the impulse noise , 2018, EURASIP J. Adv. Signal Process..

[7]  Wen-Hsien Fang,et al.  Nested algorithms for joint DOD and DOA estimation in bistatic MIMO radar , 2018, Multidimens. Syst. Signal Process..

[8]  Chao Ge,et al.  Noncircular Signal DOA Estimation with Reduced Dimension MUSIC for Coprime Linear Array , 2018, 2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC).

[9]  Wei Liu,et al.  Three-dimensional millimetre-wave beam tracking based on smart phone sensor measurements and direction of arrival/time of arrival estimation for 5G networks , 2018 .

[10]  K. V. S. Hari,et al.  Subspace-based DOA estimation using Fractional Lower Order statistics , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  Jean Pierre Delmas,et al.  Statistical Performance of MUSIC-Like Algorithms in Resolving Noncircular Sources , 2008, IEEE Transactions on Signal Processing.

[12]  Chrysostomos L. Nikias,et al.  Joint estimation of time delay and frequency delay in impulsive noise using fractional lower order statistics , 1996, IEEE Trans. Signal Process..

[13]  Chrysostomos L. Nikias,et al.  Fast estimation of the parameters of alpha-stable impulsive interference using asymptotic extreme value theory , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[14]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[15]  Diao Ming,et al.  Direction finding of signal subspace fitting algorithm based on reconstructed fractional lower order covariance , 2009 .