Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those ...Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those methods are largely restricted due to nonnegligible residual frequency.This paper proposes a new dual-channel method for fast acquisition of long PN-code.In the proposed method,both non-overlapping local PNcode blocks are employed to correlate with input sample block;the detection process is eased through finding the maximum value among correlation results and verification is made with all the full and partial peaks taken into account.False alarm probabilities from analysis of the verification process are derived.Both theoretical and Monte Carlo simulations reveal that,with respect to acquisition probability and mean acquisition time under the same false alarm rate,dual-channel method has advantage over zero-padding and XFAST based folding methods under certain false alarm probabilities.展开更多
文摘由传统机器学习方法组成的空气质量预测模型得到了普遍应用,但是此类模型对于数据有效性,特别是时空相关数据的选取仍旧存在不足。针对深度学习输入数据有效性问题进行研究,提出了一种基于时空相似LSTM的预测模型(spatial-temporal similarity LSTM model,STS-LSTM),以便在时间和空间层面选取更加有效的数据。STS-LSTM分为前序、中序和后序三个模块,前序模块为时空相似选择输入模块,提出了格兰杰因果权重动态时间折叠(Granger causal index weighted dynamic time warping,GCWDTW)算法,用于选取具有更高时空相似性的数据;中序模块使用LSTM作为深度学习网络进行训练;后序模块根据目标站点特征选择不同的输出组合进行集成。STS-LSTM整体模型在空气质量预测误差上较现有算法提升了8%左右,经过有效性选取的数据对于模型精度达到了最高21%的提升。实验结果表明,对于有效数据的选取该算法取得了显著效果,将数据输入输出方法作为应用型深度学习网络的一部分,可以有效提升深度学习网络的最终效果。
文摘Long PN-code acquisition is a difficult and time-consuming task due to long code period.To accelerate acquisition,folding methods like XFAST are widely used.In highdynamic environment however,the application of those methods are largely restricted due to nonnegligible residual frequency.This paper proposes a new dual-channel method for fast acquisition of long PN-code.In the proposed method,both non-overlapping local PNcode blocks are employed to correlate with input sample block;the detection process is eased through finding the maximum value among correlation results and verification is made with all the full and partial peaks taken into account.False alarm probabilities from analysis of the verification process are derived.Both theoretical and Monte Carlo simulations reveal that,with respect to acquisition probability and mean acquisition time under the same false alarm rate,dual-channel method has advantage over zero-padding and XFAST based folding methods under certain false alarm probabilities.
