Currently, target recognition primarily relies on imaging-based approaches to identify images. However, this method fails to adequately meet application requirements in many cases. For instance, distant small targets may occupy only a few pixels or even a single pixel. Alternatively, system size and power constraints may necessitate single-point detection. Therefore, novel approaches for single-point target recognition based on new dimensional features are urgently needed. This paper innovatively proposes a novel approach for single-point target recognition based on the orbital angular momentum (OAM) feature spectrum. This method modulates the transmitted signal with new-dimensional information in the OAM domain. Target recognition is then achieved by analyzing the proportion of each OAM mode component (i.e. the OAM feature spectrum) within the single-point echo signal. Finally, simulation and test validation demonstrate that the new-dimensional features derived from the OAM feature spectrum effectively enable the recognition of typical targets with periodic structures, such as propellers.
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Zhao et al. (2025) studied this question.
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