Research on co-design of sparse optimization and target localization for flank arrays

As a typical configuration for sonar systems on unmanned underwater vehicle (UUV), the flank conformal array still faces multiple engineering challenges. This study addresses two critical issues in existing flank array applications: platform self-noise interference and miniaturization constraints. We propose a holistic workflow for the co-design of sparse optimization and target localization in engineering-oriented conformal flank arrays. For the first time, this approach systematically integrates three key aspects: platform self-noise suppression (via array placement optimization), sparse element design, and target localization performance assurance, resolving the traditional disconnect between these isolated design stages.First, fluid-structure interaction simulations reveal the distinct spatial distribution patterns of flow-induced noise and structural vibration noise on UUV platforms, enabling optimal array placement decisions. Subsequently, an adaptive sparse optimization method for flank arrays is developed using an improved genetic algorithm. By dynamically adjusting crossover/mutation probabilities, this approach reduces the number of array elements while maintaining bearing estimation accuracy. Finally, virtual array interpolation technology is innovatively applied to target localization with sparse flank arrays, effectively mitigating mainlobe broadening and sidelobe elevation caused by sparsification. Validation through simulations and lake trials demonstrates that the proposed method achieves reduced array elements while maintaining spatial spectra with lower peak sidelobe levels and narrower -3dB beamwidths. This research provides theoretical underpinnings and practical engineering insights for compact sonar system design in next-generation underwater platforms.