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Design of Spectrally Compatible Waveforms With Low Auto- and Cross-Correlation-Weighted Integrated Sidelobe Levels

  • School of Electronics and Information Engineering, Harbin Institute of Technology
  • Ministry of Industry and Information Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Low-correlation sidelobes are critical for spectrally compatible waveforms in multiple-input multiple-output (MIMO) radar systems. This study presents a novel algorithm for designing spectrally compatible waveforms for MIMO radar with low auto- and cross-correlation sidelobes to enhance weak target detection capability. We adopt the minimum auto- and cross-correlation-weighted integrated sidelobe level (ACWISL) as the objective function. Under spectral and constant modulus constraints, we formulate a nondeterministic polynomial time (NP)-hard problem. To solve this problem, we combine the block successive upper-bound minimisation (BSUM) and majorisation-minimisation (MM) algorithms to develop the BSUM-MM algorithm. The original problem is decomposed into several independent subproblems, which are iteratively solved using the MM algorithm. We also employ the fast Fourier transform (FFT) to significantly accelerate the calculation. Simulation results demonstrate that the proposed algorithm is superior in terms of computational efficiency and sidelobe performance.

Original languageEnglish
Article numbere70024
JournalIET Radar, Sonar and Navigation
Volume19
Issue number1
DOIs
StatePublished - 1 Jan 2025
Externally publishedYes

Keywords

  • array signal processing
  • radar
  • radar signal processing
  • radar waveforms
  • signal processing
  • waveform analysis

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