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Since the 3D imaging needs a great deal of memory space, we consider the methods of downsampling to reduce the data quantity. In the azimuth direction, we proposed a method based on the multiple measurement vectors (MMV) model, which can enhance computational efficiency and elevate the performance of antinoise, to recover the signal. Further, in cross-track direction, since the resolution is restricted by the length of array, as well as platform size, the influence of off-grid effect is more serious than azimuth direction. Continuous compressive sensing (CCS), which can solve the off-grid effect of the classical compressive sensing (CS), is presented to obtain the precise imaging result under the noise scenarios. Finally, we validate our method by extension numerical experiments.<\/jats:p>","DOI":"10.1155\/2017\/6207828","type":"journal-article","created":{"date-parts":[[2017,4,5]],"date-time":"2017-04-05T17:18:54Z","timestamp":1491412734000},"page":"1-11","source":"Crossref","is-referenced-by-count":3,"title":["Downward-Looking Linear Array 3D SAR Imaging Based on Multiple Measurement Vectors Model and Continuous Compressive Sensing"],"prefix":"10.1155","volume":"2017","author":[{"given":"Qi-yong","family":"Liu","sequence":"first","affiliation":[{"name":"Information and Navigation College, Air Force Engineering University, Xi\u2019an 710077, China"},{"name":"Collaborative Innovation Center of Information Sensing and Understanding, Xi\u2019an 710077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2773-3437","authenticated-orcid":true,"given":"Qun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Information and Navigation 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