PPT-Radar Imaging with Compressed Sensing

Yang Lu April 2014 Imperial College London Outline Introduction to Synthetic Aperture Radar SAR Background of Compressed Sensing Reconstruct Radar Image by CS methods Introduction to SAR . Our goal is to develop a sensor array that will allow the PackBot to navigate autonomously through foliage such as tall grass while avoiding obstacles and building a map of the terrain We plan to use UWB radars in conjunction with other sensors such unibonnde Abstract Compressed sensing seeks to recover a sparse vector from a small number of linear and nonadaptive measurements While most work so far focuses on Gaussian or Bernoulli random measurements we investigate the use of partial random cir 4D Flow Reconstruction using . Divergence-free Wavelet Transform. Frank Ong. 1. , Martin Uecker. 1. , Umar Tariq. 2. , Albert Hsiao. 2. , Marcus Alley. 2. , Shreyas Vasanawala. 2. and Michael Lustig. RADAR => . RA. dio . D. etection . A. nd . R. anging. Radar Remote Sensing. Active remote sensing system using 1 cm to 1m wavelengths (microwaves).. Microwave Atmospheric Window. Radar Systems. . MIMO Radar. Chun-Yang Chen and P. P. Vaidyanathan. California Institute of Technology. Electrical Engineering/DSP Lab. Asilomar 2008. Outline. Review of the background. Compressed sensing . [. Donoho. monostatic. and . bistatic. radar observations of the Moon made at a wavelength of 68 cm (440.2 MHz) with the Millstone MISA radar . transceiving. and the Arecibo Gregorian system receiving are presented. These images were generated so as to calibrate both the HPLA (High-Power Large Aperture) systems while simultaneous tracking the respective sub-radar points on the Moon. The delay‐Doppler mapping technique along with appropriate Ephemeris data from JPL Horizons . Hyperspectral Imaging. AUTO3160 – Optics. Staffan Järn. Introduction. Measurement of object properties on the earth’s surface using data acuired from aircraft and satellites. Passive remote sensing. Compressed Sensing. Mobashir. . Mohammad. Aditya Kulkarni. Tobias Bertelsen. Malay Singh. Hirak. . Sarkar. Nirandika. . Wanigasekara. Yamilet Serrano . Llerena. Parvathy. . Sudhir. Introduction. Mobashir. Student : . Shenghan. TSAI. Advisor : . Hsuan. -Jung Su and . Pin-. Hsun. Lin. Date : M. ay 02, . 2014. 1. Outline. Introduction. Signal---Sparse and Compressible. . - . Sparse & Compressible. Credit to: Weile Wang. Gustav Klimt (1862-1918), . Der Park. With materials from Drs. Jeff Dozier (UCSB), Howard Zebker (Stanford), Jacob van Zyl (JPL), Alan Strahler (Boston U.), Ralph Dubayah (U. Maryland), Michael Lefsky (U. Colorado), Guoqing Sun (U. Maryland), and many others.. RA. dio . D. etection . A. nd . R. anging. Radar Remote Sensing. Active remote sensing system using 1 cm to 1m wavelengths (microwaves).. Microwave Atmospheric Window. Radar Systems. . AIRSAR - Flies in DC-8 with C, L, and P bands. Active Remote Sensing: RADAR I. Dr. Mathias (Mat) Disney. UCL Geography. Office: 113, Pearson Building. Tel: 7670 0592. 1. Email: mdisney@ucl.geog.ac.uk. www.geog.ucl.ac.uk/~mdisney. 2. OVERVIEW . OF NEXT 2 LECTURES. Feasibility using In Situ Data from SEAC4RS and TC4. Jay Mace. Measurement . Provided by: . Simone . Tanelli. , Paul Lawson and Co., . Svetla. . Hristova-Veleva. , Steve . Durden. , Paul Bui. Convective Turret Penetrated during SEAC4RS by the DC8. Slide . 1. Authors:. Tony Xiao Han, Huawei, et al. Name. Affiliation. Address. Phone. Email. Tony Xiao Han. Huawei Technologies Co. Ltd. F1, Huawei Base, Shenzhen, China. Tony.hanxiao@huawei.com . Rui Du.