Anum Pirkani;Andrew G. Stove;Dillon Kumar;Mikhail Cherniakov;Marina S. Gashinova
{"title":"77 GHz FMCW Imaging Radar for Low Observable and Small Marine Target Detection in Dynamic Sea Conditions Based on Combined MIMO and DBS","authors":"Anum Pirkani;Andrew G. Stove;Dillon Kumar;Mikhail Cherniakov;Marina S. Gashinova","doi":"10.1109/TRS.2024.3400694","DOIUrl":null,"url":null,"abstract":"High-resolution radar sensing is essential to provide situational awareness to small- and medium-sized marine platforms. However, detecting small targets on the sea surface is a challenging task for marine surveillance radars because of the weak echoes and relatively low velocity. While there is a similarity and significant body of research on high-resolution radar sensing in the automotive environment, the direct translation of such techniques to marine sensing is difficult due to the fundamentally dynamic underlaying sea surface. This article addresses the need of developing novel radar sensing capabilities to image and, potentially, classify small marine targets, such as paddlers, buoys, flotsam and jetsam, or the incoming large waves. Our proposed approach combines multiple-input–multiple-output (MIMO) and Doppler beam sharpening (DBS) beamforming techniques with the ordered statistics cell averaging constant false alarm rate (OSCA-CFAR) for robust target detection, density-based spatial clustering of applications with noise (DBSCAN) for clustering, and an adaptive focusing technique. With the developed methodology, multiple small “dynamic” targets within the marine scene have been imaged and detected against substantially suppressed sea background.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"2 ","pages":"517-534"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Radar Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10530133/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
High-resolution radar sensing is essential to provide situational awareness to small- and medium-sized marine platforms. However, detecting small targets on the sea surface is a challenging task for marine surveillance radars because of the weak echoes and relatively low velocity. While there is a similarity and significant body of research on high-resolution radar sensing in the automotive environment, the direct translation of such techniques to marine sensing is difficult due to the fundamentally dynamic underlaying sea surface. This article addresses the need of developing novel radar sensing capabilities to image and, potentially, classify small marine targets, such as paddlers, buoys, flotsam and jetsam, or the incoming large waves. Our proposed approach combines multiple-input–multiple-output (MIMO) and Doppler beam sharpening (DBS) beamforming techniques with the ordered statistics cell averaging constant false alarm rate (OSCA-CFAR) for robust target detection, density-based spatial clustering of applications with noise (DBSCAN) for clustering, and an adaptive focusing technique. With the developed methodology, multiple small “dynamic” targets within the marine scene have been imaged and detected against substantially suppressed sea background.