Abstract: Shipborne high-frequency surface wave radar’s platform motion causes broadening of first-order sea clutter, increasing the difficulty of sea clutter suppression and consequently degrading target detection performance. To address the issue of suppressing broadened sea clutter in shipborne high-frequency surface wave radar, this paper proposes a reduced-dimension space-time joint method based on adaptive Localized Processing Region (LPR) for sea clutter suppression. The method first adaptively selects the LPR based on the output Signal-to-Clutter-plus-Noise Ratio (SCNR), constructing a reduced-dimension transformation matrix to reduce the dimensionality of time-domain data, making it applicable to more scenarios. Subsequently, covariance matrix estimation is performed to compute optimal weights, improving target SCNR and thereby achieving suppression of broadened sea clutter. Finally, simulations and real-world data validate the effectiveness of the proposed method. The results demonstrate that the proposed method outperforms traditional sea clutter suppression techniques under various conditions, significantly enhancing target Doppler detection accuracy. The average SCNR improvement reaches approximately 30 dB, effectively improving the sea clutter suppression performance of shipborne high-frequency surface wave radar.