Cognitive Design of Radar Waveform and the Receive Filter for Multitarget Parameter Estimation

  • Yu YaoEmail author
  • Junhui Zhao
  • Lenan Wu


This research work considers waveform design for an adaptive radar system. The aim is to achieve enhanced feature extraction performance for multiple extended targets. There are two scenarios to consider: multiple extended targets separated in range and multiple extended targets close in range. We propose a waveform optimization scheme based on Kalman filtering by minimizing the mean square error of separated target scattering coefficient estimation and a waveform optimization approach by minimizing the mean square error of closed power spectrum density estimation. A convex cost function is established, and the optimal solution can be obtained using the existing convex programming algorithm. With subsequent iterations of the algorithm, the simulation results demonstrate an improvement in the estimation of target parameters from the dynamic scene, such as target scattering coefficient and power spectrum density, while maintaining relatively lower computational complexity.


Kalman filtering Target scattering coefficient estimation Power spectrum density estimation Waveform optimization Multiple extended targets 

Mathematics Subject Classification

15A69 81P40 90C3 



This work was supported by the national Natural Science Foundation of China (61761019, 61861017, 61861018, 61862024) and the Natural Science Foundation of Jiangxi Province (Jiangxi Province natural Science Fund) (20181BAB211014, 20181BAB211013), and Foundation of Jiangxi Educational Committee of China (GJJ170414).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.East China Jiaotong UniversityNanchangChina
  2. 2.Southeast UniversityNanjingChina

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