A closed-loop strategy for cognitive radar based on the estimation of clutter power spectrum

Chen Yang; Wei Yang; Weidong Jiang; Yongxiang Liu

doi:10.1117/12.3023206

28 March 2024 A closed-loop strategy for cognitive radar based on the estimation of clutter power spectrum

Chen Yang, Wei Yang, Weidong Jiang, Yongxiang Liu

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 1309110 (2024) https://doi.org/10.1117/12.3023206
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

To address the limitations of traditional radar in time-varying and complex environments, a novel closed-loop structure for cognitive radar is introduced in this paper. The proposed system begins by estimating the power spectrum density of clutter using a clutter inversion algorithm. Next it predicts the upcoming clutter information using an autoregression model and a clutter prior information matrix as input. Finally, it employs a water-filling method and a time-synthesis algorithm to design an optimal spectrum and a constant modulus transmit sequence utilizing the prediction clutter priori information. Moreover, experimental results using real-measured data under varying parameters demonstrate that the proposed strategy outperforms traditional radar process.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chen Yang, Wei Yang, Weidong Jiang, and Yongxiang Liu "A closed-loop strategy for cognitive radar based on the estimation of clutter power spectrum", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 1309110 (28 March 2024); https://doi.org/10.1117/12.3023206

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KEYWORDS

Clutter

Signal processing

Design

Radar

Autoregressive models

Data modeling

Matrices

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