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Lett."],"published-print":{"date-parts":[[2026,7,1]]},"abstract":"<jats:p>We propose and experimentally demonstrate a photonic-assisted adaptive\n\t\t\t\t\tspatial filter (PASF) utilizing a Hooke\u2013Jeeves-based LCMV (HJ-LCMV)\n\t\t\t\t\toptimization. By integrating a gradient-free direct search with the\n\t\t\t\t\tLCMV framework, the system adaptively adjusts optical weights based on\n\t\t\t\t\treal-time feedback to compensate for hardware non-idealities, thereby\n\t\t\t\t\tachieving interference suppression while preserving foundational\n\t\t\t\t\tbeamforming characteristics. Outdoor field tests using a 28-element\n\t\t\t\t\tlinear array at 10\u2009GHz and 16\u2009GHz achieve null-steering depths of\n\t\t\t\t\t53.3\u2009dB and 41.2\u2009dB, respectively. The system also demonstrates the\n\t\t\t\t\tcapability to form a wide null localized around the optimized\n\t\t\t\t\tfrequency. 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All rights, including\n\t\t\t\t\tfor text and data mining (TDM), Artificial Intelligence (AI) training,\n\t\t\t\t\tand similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}