Spatial averaging of time-frequency distributions for signal recovery in uniform linear arrays

2000 ◽  
Vol 48 (10) ◽  
pp. 2892-2902 ◽  
Author(s):  
Yimin Zhang ◽  
M.G. Amin
Keyword(s):  
Signal Recovery ◽  
Spatial Averaging ◽  
Frequency Distributions ◽  
Linear Arrays ◽  
Time Frequency

scholarly journals Structure-Aware Bayesian Compressive Sensing for Near-Field Source Localization Based on Sensor-Angle Distributions

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Si Qin ◽  
Yimin D. Zhang ◽  
Qisong Wu ◽  
Moeness G. Amin
Keyword(s):  
Spatial Frequency ◽  
Compressive Sensing ◽  
Source Localization ◽  
Near Field ◽  
Joint Space ◽  
Angle Distribution ◽  
Field Source ◽  
Frequency Distributions ◽  
Linear Arrays ◽  
Time Frequency

A novel technique for localization of narrowband near-field sources is presented. The technique utilizes the sensor-angle distribution (SAD) that treats the source range and direction-of-arrival (DOA) information as sensor-dependent phase progression. The SAD draws parallel to quadratic time-frequency distributions and, as such, is able to reveal the changes in the spatial frequency over sensor positions. For a moderate source range, the SAD signature is of a polynomial shape, thus simplifying the parameter estimation. Both uniform and sparse linear arrays are considered in this work. To exploit the sparsity and continuity of the SAD signature in the joint space and spatial frequency domain, a modified Bayesian compressive sensing algorithm is exploited to estimate the SAD signature. In this method, a spike-and-slab prior is used to statistically encourage sparsity of the SAD across each segmented SAD region, and a patterned prior is imposed to enforce the continuous structure of the SAD. The results are then mapped back to source range and DOA estimation for source localization. The effectiveness of the proposed technique is verified using simulation results with uniform and sparse linear arrays where the array sensors are located on a grid but with consecutive and missing positions.

A deductive construction of third-order time-frequency distributions

1994 ◽  
Vol 36 (3) ◽  
pp. 277-286 ◽  
Author(s):  
Pierre-Olivier Amblard ◽  
Jean-Louis Lacoume
Keyword(s):  
Third Order ◽  
Frequency Distributions ◽  
Time Frequency
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