An Efficient Adaptive Monopulse Estimation Algorithm Based on MPASTd Approach

نویسندگان

  • Jia Yu
  • Mingwei Shen
  • Di Wu
  • Daiyin Zhu
چکیده

In this paper, an improved adaptive monopulse scheme based on modified projection approximation subspace tracking deflation (MPASTd) approach is proposed. Owing to the fast convergence speed of MPASTd for recursively estimating the interference subspace, the proposed algorithm can obtain the formula for adaptive monopulse ratio calculation by a subspace projection. Therefore, it is able to accurately estimate the source location using less training data and reduce the computational complexity significantly. The effectiveness and fast convergence speed of the proposed method is verified by simulation results.

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تاریخ انتشار 2016