Radio-frequency Interference Detection Algorithm for L-band Phased Array Microwave Radiometer
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摘要:
目前，微波辐射计均面临严重的射频干扰(RFI)问题，尤其在低频段。针对一种用于获取海洋盐度和土壤湿度的L波段相控阵微波辐射计，该文提出一种射频干扰检测算法。首先，简单介绍了该L波段相控阵微波辐射计系统；随后，详细介绍该射频干扰算法，其主要包括RFI初标识、RFI滑动窗口1次标识、RFI滑动窗口2次标识和RFI扩展标识等4个步骤；最后，采用该算法对L波段相控阵微波辐射计的实验数据进行处理。实验结果均表明：该算法能够较好地检测出射频干扰异常数据，检测性能较好。
Abstract:At present, microwave radiometers suffer from serious Radio Frequency Interference (RFI), especially in low frequency. In this paper, a radio frequency detection algorithm is proposed for L-band phased array radiometer, which is used to measure the sea surface salinity and soil moisture. First, the L-band phased array radiometer is introduced in briefly. Secondly, the radio frequency detection algorithm is introduced in details, which consists of the raw RFI flag, the RFI first moving–averaged window flag, the RFI second moving–averaged window flag and the expanded RFI flag. Finally, the experimental data obtained by the L-band phased array radiometer is processed with the proposed RFI detection algorithm. The results indicate that the proposed detection RFI algorithm can effectively detect the RFI contaminated abnormal data, and exhibits good detected ability.
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表 3 观测角33°时的Kurtosis值
波束5 波束6 波束7 波束8 波束9 原始数据的$\kappa $值 284.47 254.83 19.50 214.60 129.08 RFI后的$\kappa $值 2.84 2.91 2.83 2.85 2.73 
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表 4 观测角51°时的Kurtosis值
波束5 波束6 波束7 波束8 波束9 原始数据的$\kappa $值 587.64 362.80 163.46 158.29 123.89 RFI后的$\kappa $值 2.57 2.58 2.91 2.73 2.70
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