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      Frequency Diverse Array Radar Signal Processing via Space-Range-Doppler Focus (SRDF) Method

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          Abstract

          To meet the urgent demand of low-observable moving target detection in complex environments, a novel method of Frequency Diverse Array (FDA) radar signal processing method based on Space-Rang-Doppler Focusing (SRDF) is proposed in this paper. The current development status of the FDA radar, the design of the array structure, beamforming, and joint estimation of distance and angle are systematically reviewed. The extra degrees of freedom provided by FDA radar are fully utilizsed, which include the Degrees Of Freedom (DOFs) of the transmitted waveform, the location of array elements, correlation of beam azimuth and distance, and the long dwell time, which are also the DOFs in joint spatial (angle), distance, and frequency (Doppler) dimensions. Simulation results show that the proposed method has the potential of improving target detection and parameter estimation for weak moving targets in complex environments and has broad application prospects in clutter and interference suppression, moving target refinement, etc..

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 April 2018
          : 7
          : 2
          : 183-193
          Affiliations
          [1 ] (Naval Aviation University, Yantai 264001, China)
          Article
          b83b5622a86b43ddaba863b75e665766
          10.12000/JR18018
          398747df-1f7b-49a2-a72d-7e6f10f95837

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          History
          Categories
          Technology (General)
          T1-995

          Remote sensing,Electrical engineering
          Frequency Diverse Array (FDA) radar,Space-Range-Doppler Focus (SRDF),Low-observable target,Moving target detection,Clutter suppression,High-resolution sparse representation

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