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Detection of Multiple Movers Based on Single Channel Source Separation of Their Micro-Dopplers | IEEE Journals & Magazine | IEEE Xplore

Detection of Multiple Movers Based on Single Channel Source Separation of Their Micro-Dopplers


Abstract:

Studies have demonstrated the usefulness of micro-Doppler signatures for classifying dynamic radar targets such as humans, helicopters, and wind turbines. However, these ...Show More

Abstract:

Studies have demonstrated the usefulness of micro-Doppler signatures for classifying dynamic radar targets such as humans, helicopters, and wind turbines. However, these classification works are based on the assumption that the propagation channel consists of only a single moving target. When multiple targets move simultaneously in the channel, the micro-Dopplers, in their radar backscatter, superimpose thereby distorting the signatures. In this paper, we propose a method to detect multiple targets that move simultaneously in the propagation channel. We first model the micro-Doppler radar signatures of different movers using dictionary learning techniques. Then, we use a sparse coding algorithm to separate the aggregate radar backscatter signal from multiple targets into their individual components. We demonstrate that the disaggregated signals are useful for accurately detecting multiple targets.
Published in: IEEE Transactions on Aerospace and Electronic Systems ( Volume: 54, Issue: 1, February 2018)
Page(s): 159 - 169
Date of Publication: 14 August 2017

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