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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 内容类型：会议论文    专题：北京航空航天大学    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 SAR IMAGE SEGMENTATION BASED ON BMFCM 会议论文 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017-01-01 作者:  Xu, Hailun;  Sun, Bing;  Chen, Jie;  Guo, Wei;  Qiao, Zhijun 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/30 SAR image segmentation  FCM  MRF  bias field estimation   A Decentralized Method for BeiDou Satellite Autonomous Orbit Determination Based on Schmidt-Kalman Filter 会议论文 29th International Technical Meeting of The-Satellite-Division-of-the-Institute-of-Navigation (ION GNSS+), Portland, OR, 2016-09-12 作者:  He, Zhijun;  Zhao, Hongbo;  Feng, Wenquan;  Sun, Chao 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30 An On-board Autonomous Detection Technology of carrier leakage on GNSS Signal 会议论文 29th International Technical Meeting of The-Satellite-Division-of-the-Institute-of-Navigation (ION GNSS+), Portland, OR, 2016-09-12 作者:  Rong, Zhiqiang;  Zhao, Hongbo;  Sun, Hua;  Sun, Chao;  He, Zhijun 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/30 A Decentralized Method for BeiDou Satellite Autonomous Orbit Determination Based on Schmidt-Kalman Filter 会议论文 PROCEEDINGS OF THE 29TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2016), 2016-01-01 作者:  He, Zhijun;  Zhao, Hongbo;  Feng, Wenquan;  Sun, Chao 收藏  |  浏览/下载：1/0  |  提交时间：2019/12/30 Compressive sensing for a general SAR imaging model based on Maxwell's equation 会议论文 Conference on Compressive Sensing IV, Baltimore, MD, 2015-01-01 作者:  Sun, Bing;  Gu, Haicheng;  Hu, Mengqi;  Qiao, Zhijun 收藏  |  浏览/下载：2/0  |  提交时间：2020/01/06 compressive sensing  general echo model  Maxwell's equations  synthetic aperture radar (SAR)   Image reconstruction and compressive sensing in MIMO radar 会议论文 Conference on Radar Sensor Technology XVIII, Baltimore, MD, 2014-01-01 作者:  Sun, Bing;  Lopez, Juan;  Qiao, Zhijun 收藏  |  浏览/下载：3/0  |  提交时间：2020/01/06 Multiple-input multiple-output  compressive sensing  basis pursuit  total-variation minimization