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Extended Targets Modelling and Block Agnostic Sparse Reconstruction in Through-the-Wall Radar Imaging: A Different Perspective

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dc.creator Abdalla, Abdi T
dc.creator Alkhodary, Mohammad
dc.creator Muqaibel, Ali
dc.date 2020-01-07T13:32:54Z
dc.date 2020-01-07T13:32:54Z
dc.date 2019
dc.date.accessioned 2021-05-03T13:17:01Z
dc.date.available 2021-05-03T13:17:01Z
dc.identifier 2307-1885
dc.identifier http://hdl.handle.net/20.500.11810/5349
dc.identifier.uri http://hdl.handle.net/20.500.11810/5349
dc.description A common target model in through-the-wall radar (TWRI) imaging literature obeys the point target (PT) assumption in which a target is hypothesized to occupy a single pixel. Unlike PTs, the received signal reflected from extended target (ET) is an integration of the scattered signals from various parts of the same target. For high resolution images, a generalized model is needed to encompass the ETs. In this paper, we suggest a different but realistic ET reconstruction approach based on agnostic block sparsity. The algorithm does not impose any assumption on the length, number, or the distribution of the blocks. Results based on MATLAB simulation and experimental data show the effectiveness of the proposed reconstruction approach. The applications of the suggested approach are found in civil, rescue, surveillance, and security enforcement sectors, where an accurate tracking of large targets behind walls is vital.
dc.description This work is funded by the National Plan for Science, Technology and Innovation (Maarifah), King Abdul Aziz City for Technology, through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM), The Kingdom of Saudi Arabia, award number 15-ELE4651-04
dc.language en_US
dc.publisher Academic Publication Council-Kuwait University
dc.subject COMPRESSIVE SENSING
dc.subject RADAR IMAGING
dc.subject RADAR TARGET RECOGNITION
dc.title Extended Targets Modelling and Block Agnostic Sparse Reconstruction in Through-the-Wall Radar Imaging: A Different Perspective
dc.type Journal Article, Peer Reviewed


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