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THE WHALE ALGORITHM OPTIMIZED SUPPORT VECTOR MACHINE FOR CHANNEL QUALITY CONTROL OF GNSS VECTOR TRACKING LOOP

摘要


For the Global Navigation Satellite System (GNSS) Vector Tracking Loop (VTL), the primary drawback is that the presence of low-quality signals or even a fault in one channel (signal blockage) will affect all channels, and possibly lead to receiver instability or loss of lock on all available satellites. Motivated by this problem, this paper introduced a Whale Algorithm optimized Support Vector Machine (WA-SVM) to monitor the running state of the vector tracking loop channels. The WA was employed to optimize the parameters of the SVM for higher accuracy of classification. In this method, a type of sub-filter was designed for each channel, and the innovative sequences from the sub-filter were employed as the input vector of the WA-SVM. The output was the state of the corresponding channel (negative: faulty and positive: nor- mal). The state variables of each local filter corresponding to the channel were the pseudo-range error and pseudo-range rate error, the measurement information were the code loop discriminator outputs and the frequency discriminator outputs. A trajectory with random pseudo-range and pseudo-range rate interference and low-quality signal was generated by a GPS signal simulator to validate the effectiveness of the method. The results demonstrated the WA-SVM method could quickly and effectively detect channel abnormality, which could keep the vector tracking loop working well.

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