scholarly journals A Channelization-Based DOA Estimation Method for Wideband Signals

Sensors ◽  
2016 ◽  
Vol 16 (7) ◽  
pp. 1031 ◽  
Author(s):  
Rui Guo ◽  
Yue Zhang ◽  
Qianqiang Lin ◽  
Zengping Chen
Keyword(s):  
Estimation Method ◽  
Doa Estimation ◽  
Wideband Signals

Off-grid DoA estimation method of wideband signals

2020 ◽  
Vol 33 (14) ◽  
pp. e4466
Author(s):  
Yasoub Eghbali ◽  
Mahmoud Ferdosizade Naeiny
Keyword(s):  
Estimation Method ◽  
Doa Estimation ◽  
Wideband Signals

scholarly journals Underdetermined DOA Estimation of Wideband LFM Signals Based on Gridless Sparse Reconstruction in the FRF Domain

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2383 ◽  
Author(s):  
Yue Cui ◽  
Junfeng Wang ◽  
Jie Qi ◽  
Zhanying Zhang ◽  
Jinqi Zhu
Keyword(s):  
Covariance Matrix ◽  
Degrees Of Freedom ◽  
Sparse Matrix ◽  
Estimation Method ◽  
Doa Estimation ◽  
Sparse Reconstruction ◽  
Virtual Sensors ◽  
Steering Vector ◽  
Wideband Signals ◽  
Variant Frequency

An underdetermined direction of arrival (DOA) estimation method of wideband linear frequency modulated (LFM) signals is proposed without grid mismatch. According to the concentration property of LFM signal in the fractional Fourier (FRF) domain, the received sparse model of wideband signals with time-variant steering vector is firstly derived based on a coprime array. Afterwards, by interpolating virtual sensors, a virtual extended uniform linear array (ULA) is constructed with more degrees of freedom, and its covariance matrix in the FRF domain is recovered by employing sparse matrix reconstruction. Meanwhile, in order to avoid the grid mismatch problem, the modified atomic norm minimization is used to retrieve the covariance matrix with the consecutive basis. Different from the existing methods that approximately assume the frequency and the steering vector of the wideband signals are time-invariant in every narrowband frequency bin, the proposed method not only can directly solve more DOAs of LFM signals than the number of physical sensors with time-variant frequency and steering vector, but also obtain higher resolution and more accurate DOA estimation performance by the gridless sparse reconstruction. Simulation results demonstrate the effectiveness of the proposed method.

Underdetermined DOA Estimation Method for Wideband Signals Using Joint Nonnegative Sparse Bayesian Learning

2017 ◽  
Vol 24 (5) ◽  
pp. 535-539 ◽  
Author(s):  
Nan Hu ◽  
Bing Sun ◽  
Yi Zhang ◽  
Jisheng Dai ◽  
Jiajun Wang ◽  
...  
Keyword(s):  
Bayesian Learning ◽  
Estimation Method ◽  
Doa Estimation ◽  
Sparse Bayesian Learning ◽  
Wideband Signals

A Novel DOA Estimation Method for Wideband Signals

2011 ◽  
Vol 403-408 ◽  
pp. 2861-2865
Author(s):  
Fu Gang Liu ◽  
Ming Diao
Keyword(s):  
Performance Improvement ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Bias ◽  
Wideband Signals ◽  
Significant Performance ◽  
Simulation Results ◽  
The Impact ◽  
Real Time Application ◽  
Conventional Algorithm

For direction of arrival (DOA) estimation of wideband signals, the traditional algorithms’ estimating accuracy and complexity were mainly affected by pre-estimation of DOA. By forming an angle set which elements were arithmetic progressions in the range of possible arriving angles, the algorithm used the new angle vector to replace the preliminary estimation of arriving angles. It can avoid the impact of pre-estimation bias on performance of DOA estimation and greatly reduce the amount of computation and the consumed time for DOA estimation to favor the real-time application of wideband DOA estimation. The simulation results showed that the proposed algorithm was able to provide significant performance improvement over the conventional algorithm.

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