The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detecti...The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.展开更多
Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross...Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross-correlation demodulation scheme,referred to as CICCD,yielded a set of single short signals based on the prior information of AIS,after the frequency,code rate and modulation index were estimated.It demodulates the corresponding short codes according to the maximum peak of cross-correlation,which is simple and easy to implement.Numerical simulations show that the bit error rate of proposed algorithm improves by about 40% compared with existing ones,and about 3 dB beyond the standard AIS receiver.In addition,the proposed demodulation scheme shows the satisfying performance and engineering value in mixing AIS environment and can also perform well in low signal-to-noise conditions.展开更多
Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. ...Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.展开更多
文摘The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.
基金Project(9140C860304) supported by the National Defense Key Laboratory Foundation of China
文摘Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross-correlation demodulation scheme,referred to as CICCD,yielded a set of single short signals based on the prior information of AIS,after the frequency,code rate and modulation index were estimated.It demodulates the corresponding short codes according to the maximum peak of cross-correlation,which is simple and easy to implement.Numerical simulations show that the bit error rate of proposed algorithm improves by about 40% compared with existing ones,and about 3 dB beyond the standard AIS receiver.In addition,the proposed demodulation scheme shows the satisfying performance and engineering value in mixing AIS environment and can also perform well in low signal-to-noise conditions.
文摘Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.
文摘针对传统的神经网络模型因超参数众多,在实验中比对最优参数组合效率低下导致误差较大和反应速度慢的问题。本文提出一种基于北方苍鹰优化(Northern Goshawk Optimization,NGO)算法和双向门控循环单元神经网络(Bidirectional Gated Recurrent Unit, Bi-GRU)的船舶轨迹预测模型NGO-Bi-GRU(Northern Goshawk Optimization Bidirectional Gated Recurrent Unit)。利用NGO对Bi-GRU模型的学习率、隐藏节点和正则化系数进行寻优,然后将寻优得到的网络超参数代入Bi-GRU进行船舶轨迹预测。将该模型与长短时记忆神经网络(Long Short Term Memory, LSTM)和门控循环单元神经网络模型(Gated Recurrent Unit, GRU)以及使用该算法优化的长短期神经网络模型进行实验对比,将均方误差、均方根误差、平均绝对误差作为评价标准。结果表明,NGO-Bi-GRU模型在经度和纬度预测上误差较小、精确度较高且数值波动更加稳定。
