{"title":"Synthetic aperture image enhancement with near-coinciding Nonuniform sampling case","authors":"Xuebo Zhang , Peixuan Yang , Dengyu Cao","doi":"10.1016/j.compeleceng.2024.109818","DOIUrl":null,"url":null,"abstract":"<div><div>Multireceiver synthetic aperture sonar (SAS) uses multiple receivers to collect echoed signals, leading to nonuniform sampling in the azimuth dimension if the moving distance between adjacent pings is not half the receiver array length. The filter bank reconstruction (FBR) method, based on matrix inversion, is commonly used to address this by reconstructing uniform data from nonuniform signals. However, in practice, near-coinciding sampling can occur due to inaccuracies in the towed velocity of the SAS system, influenced by ocean conditions. The signal correlation of these near-coinciding receivers is very strong, and thus the steering vectors corresponding to these receivers are not completely independent. This further leads to an ill-conditioned system transfer function matrix made up of the receiver steering vectors, and results in inaccurate calculations of inverse matrix. Consequently, the FBR method suffers from significant signal-to-noise ratio loss or fails to reconstruct uniform signals accurately. This degradation in signal quality directly impacts the accuracy of target reconstruction, leading to errors in identifying and locating targets. This paper quantitatively defines nonuniform sampling with near-coinciding samples and discusses performance loss in various cases. To enhance imaging performance, we propose a method for reconstructing uniform signals. Simulation results demonstrate that the proposed method outperforms the conventional FBR method, providing better target reconstruction and higher efficiency.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"120 ","pages":"Article 109818"},"PeriodicalIF":4.0000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Electrical Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045790624007456","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
Multireceiver synthetic aperture sonar (SAS) uses multiple receivers to collect echoed signals, leading to nonuniform sampling in the azimuth dimension if the moving distance between adjacent pings is not half the receiver array length. The filter bank reconstruction (FBR) method, based on matrix inversion, is commonly used to address this by reconstructing uniform data from nonuniform signals. However, in practice, near-coinciding sampling can occur due to inaccuracies in the towed velocity of the SAS system, influenced by ocean conditions. The signal correlation of these near-coinciding receivers is very strong, and thus the steering vectors corresponding to these receivers are not completely independent. This further leads to an ill-conditioned system transfer function matrix made up of the receiver steering vectors, and results in inaccurate calculations of inverse matrix. Consequently, the FBR method suffers from significant signal-to-noise ratio loss or fails to reconstruct uniform signals accurately. This degradation in signal quality directly impacts the accuracy of target reconstruction, leading to errors in identifying and locating targets. This paper quantitatively defines nonuniform sampling with near-coinciding samples and discusses performance loss in various cases. To enhance imaging performance, we propose a method for reconstructing uniform signals. Simulation results demonstrate that the proposed method outperforms the conventional FBR method, providing better target reconstruction and higher efficiency.
期刊介绍:
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.
Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.