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  • 标题:Frequency Diverse Array Radar Cramér-Rao Lower Bounds for Estimating Direction, Range, and Velocity
  • 本地全文:下载
  • 作者:Yongbing Wang ; Wen-Qin Wang ; Huaizong Shao
  • 期刊名称:International Journal of Antennas and Propagation
  • 印刷版ISSN:1687-5869
  • 电子版ISSN:1687-5877
  • 出版年度:2014
  • 卷号:2014
  • DOI:10.1155/2014/830869
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Different from phased-array radar, frequency diverse array (FDA) radar offers range-dependent beampattern and thus provides new application potentials. But there is a fundamental question: what estimation performance can achieve for an FDA radar? In this paper, we derive FDA radar Cramér-Rao lower bounds (CRLBs) for estimating direction, range (time delay), and velocity (Doppler shift). Two different data models including pre- and postmatched filtering are investigated separately. As the FDA radar has range-angle coupling, we use a simple transmit subaperturing strategy which divides the whole array into two subarrays, each uses a distinct frequency increment. Assuming temporally white Gaussian noise and linear frequency modulated transmit signal, extensive simulation examples are performed. When compared to conventional phased-array radar, FDA can yield better CRLBs for estimating the direction, range, and velocity. Moreover, the impacts of the element number and frequency increment are also analyzed. Simulation results show that the CRLBs decrease with the increase of the elements number and frequency increment.
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