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A Higher-Order Singular Value Decomposition-Based Radio Frequency Interference Mitigation Method on High-Frequency Surface Wave Radar

机译:基于高阶奇异值的基于奇异值的高频表面波雷达的射频干扰缓解方法

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Recently, high-frequency surface wave radar (HFSWR) has been widely applied in ocean surface dynamic parameter measurement. However, the radar echoes backscattered from ocean surface tend to be contaminated by the external radio frequency interference (RFI), and the mitigation of RFI becomes an intractable problem, especially for wide beam HFSWR. The HFSWR measured data are multichannel. The higher-order singular value decomposition (HOSVD) is an effective method to improve the accuracy of subspace estimation by exploiting this multidimensional structure. In this article, we develop an RFI mitigation method based on the HOSVD algorithm and orthogonal subspace projection. Simulations indicate that, compared with the previous orthogonal subspace projection RFI cancellation schemes, the proposed method has significant advantages in keeping the desired signals while suppressing the interference. The proposed method is applied to the experimental data of the HFSWR with severe RFI. The ocean surface currents inverted from the RFI-mitigated data agree reasonably with the tidal features in the radar detection area. After RFI mitigation, the performance of the HFSWR system is significantly improved on the effective current detection range and precision.
机译:最近,高频表面波雷达(HFSWR)已广泛应用于海面动态参数测量。然而,从海洋表面反向散射的雷达回声往往被外部射频干扰(RFI)污染,并且RFI的缓解成为难以处理的问题,特别是对于宽光束HFSWR。 HFSWR测量数据是多通道。高阶奇异值分解(HOSVD)是通过利用这种多维结构来提高子空间估计准确性的有效方法。在本文中,我们开发了基于Hosvd算法和正交子空间投影的RFI缓解方法。模拟表明,与先前的正交子空间投影RFI取消方案相比,所提出的方法在保持所需信号时具有显着的优点,同时抑制干扰。该提出的方法应用于HFSWR的实验数据,具有严重的RFI。从RFI缓解数据反转的海洋表面电流合理地与雷达检测区域中的潮汐特征相加。在RFI缓解之后,对有效电流检测范围和精度显着提高了HFSWR系统的性能。

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