Conjugate Gradient Projection onto Convex Sets for Sparse Array Acoustic Holography

Kenbu TERAMOTO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A   No.5   pp.833-839
Publication Date: 1997/05/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Acoustical Inverse Problems)
Category: 
Keyword: 
acoustic imaging,  inversion,  ill-posed problem,  POCS,  

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Summary: 
This paper describes a novel image reconstruction algorithm and experimental results of a 3-dimensional acoustical holographic imaging system which has a limited number of transducers distributed sparsely. The proposed algorithm is based on the conjugate gradient projection onto convex sets (CGPOCS), which allows the addition of convex sets constrained by a priori information to reduce ambiguity and extract resolution iteratively. By several experiments, it is proven that the concept of the new 3-D acoustic image reconstruction algorithm has following improvements:
1. the artifacts caused by the spurious lobes can be reduced under the condition that the inter-spacing of elements is larger than the wave length,
2. the instability caused by the lack of information about the actual point spread function (PSF) can be reduced,
3. the actual PSF can be estimated concurrently with during the image reconstruction process.