DOA estimation based on sparse representation of the fractional lower order statistics in impulsive noise

2018 ◽  
Vol 5 (4) ◽  
pp. 860-868 ◽  
Author(s):  
Sen Li ◽  
Rongxi He ◽  
Bin Lin ◽  
Fei Sun
Keyword(s):  
Sparse Representation ◽  
Order Statistics ◽  
Lower Order ◽  
Impulsive Noise ◽  
Doa Estimation ◽  
Fractional Lower Order Statistics

A New Algorithm of Range and DOA Estimation of Near Field Sources Based on FLOS-ESPRIT

2014 ◽  
Vol 577 ◽  
pp. 745-748
Author(s):  
Li Guo Wang
Keyword(s):  
Order Statistics ◽  
Computer Simulations ◽  
Lower Order ◽  
Linear Array ◽  
Near Field ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Uniform Linear Array ◽  
Joint Estimate ◽  
Fractional Lower Order Statistics

A new algorithm based on fractional lower order statistics (FLOS) is presented to joint estimate the range and direction of arrival (DOA) parameters of near-field sources. The proposed algorithm adopts centra-symmetric uniform linear array, and constructs three fractional lower order statistics matrixes by the received array data, and utilizes TLS method to estimate the two dimension parameters, the algorithm has high estimation accuracy, only need a parameters pairing easily. The performance of proposed method is verified by computer simulations.

scholarly journals Robust Signals Detection Algorithm Based on Cyclostationarity in Impulsive Noise

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Order Statistics ◽  
Lower Order ◽  
Stable Distribution ◽  
Impulsive Noise ◽  
Detection Algorithm ◽  
Communication Signals ◽  
Alpha Stable Distribution ◽  
Fractional Lower Order Statistics ◽  
Non Gaussian ◽  
Output Snr

A robust method for detecting the communication signals impinging on an antenna with interference and non-Gaussian impulsive noise is introduced in this paper. Degradation of the conventional cyclic detector which based on max-output-SNR criterion in impulsive noise is shown both theoretically and experimentally. By fusing second-order cyclostationarity and fractional lower-order statistics, a type of cyclic fractional lower-order statistics is developed which is defined for exploiting cyclostationarity property. Then, a new robust type of detection algorithm is developed using the theory of optimal filtering based on max-output-SNR criterion and alpha-stable distribution, including the fractional lower-order cyclic matched filter, which is formulated for detecting the communication signals in the presence of interference and non-Gaussian alpha-stable distribution impulsive noise. It is shown that the new method is robust to Gaussian and non-Gaussian impulsive noises, and is immune to the interfering signals which occupy the same spectral band as that of the received signal. Simulation results show the robustness and effectiveness of the proposed algorithm.

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