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基于高阶幂的单快拍LDACS系统波达方向估计
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作者 王磊 高翔 +1 位作者 胡潇潇 刘海涛 《西北工业大学学报》 EI CAS CSCD 北大核心 2024年第2期362-367,共6页
L波段数字航空通信系统(L band digital aeronautical communication system,LDACS)是未来航空宽带通信重要的基础设施之一,针对LDACS信号容易受到相邻波道大功率测距仪(distance measuring equipment,DME)信号干扰的问题,提出了联合正... L波段数字航空通信系统(L band digital aeronautical communication system,LDACS)是未来航空宽带通信重要的基础设施之一,针对LDACS信号容易受到相邻波道大功率测距仪(distance measuring equipment,DME)信号干扰的问题,提出了联合正交投影干扰抑制与单快拍稀疏分解的波达方向(direction of arrival,DOA)估计方法。通过子空间投影抑制DME干扰,然后使用单快拍数据构建伪协方差矩阵,对伪协方差矩阵求高阶幂,之后进行奇异值分解,并利用约束条件求解稀疏解得到期望信号来向的估计值。所提方法使用高阶伪协方差矩阵降低了噪声影响,仅用单快拍就可以准确估计LDACS信号的入射方向。仿真结果表明,改进单快拍高级幂(improved single snapshot high order power,ISS-HOP)L1-SVD算法的估计精度优于ISS-HOP-MUSIC算法。该方法可以有效抑制DME干扰,提高OFDM接收机性能。 展开更多
关键词 L波段数字航空通信系统 测距仪 波达方向估计 改进单快拍高阶幂算法
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基于卷积神经网络的飞机燃油消耗预测方法 被引量:2
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作者 赵元棣 王中义 《重庆交通大学学报(自然科学版)》 CAS CSCD 北大核心 2023年第8期125-131,共7页
针对绿色民航的发展目标,准确预测飞机燃油消耗具有重要意义。对飞机油耗问题进行研究分析,基于TensorFlow深度学习框架,使用卷积神经网络,建立飞机燃油消耗预测模型。将预测结果分别与现有的飞行计划、多层感知机神经网络模型对比,验... 针对绿色民航的发展目标,准确预测飞机燃油消耗具有重要意义。对飞机油耗问题进行研究分析,基于TensorFlow深度学习框架,使用卷积神经网络,建立飞机燃油消耗预测模型。将预测结果分别与现有的飞行计划、多层感知机神经网络模型对比,验证卷积神经网络模型的准确性,并进行10折交叉验证,验证模型的鲁棒性。结果表明:卷积神经网络模型预测结果的平均误差率为5.26%,明显优于现有的飞行计划的17.67%和多层感知机模型的7.69%,模型10折交叉验证的误差率方差为0.16%;基于卷积神经网络的飞机燃油消耗预测模型具有很好的准确性和鲁棒性,能够为航空公司提供更加准确的飞机携带燃油量,避免产生更大燃油消耗,可有效降低运营成本,实现绿色民航的节能目标。 展开更多
关键词 交通运输工程 绿色民航 飞机燃油预测 卷积神经网络 交叉验证
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4-D Trajectory Prediction and Dynamic Planning of Aircraft Taxiing Considering Time and Fuel 被引量:2
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作者 LI Nan ZHANG Lei +1 位作者 SUN Yu GAO Zheng 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第5期852-866,共15页
Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the ... Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the speed profile of the aircraft when turning,and the shortest taxi time does not necessarily bring the best taxi fuel consumption.In this paper,the number of turns is considered,and the improved A*algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths.By balancing taxi time and fuel consumption,a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft.Based on the 4-D trajectory prediction results,the conflict by the occupied time window in the taxiing area is detected.For the conflict aircraft,based on the priority comparison,the waiting or changing path is selected to solve the taxiing conflict.Finally,the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated.The experimental results show that the total taxi distance and turn time of the aircraft are reduced,and the fuel consumption is reduced.The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future. 展开更多
关键词 air transportation trajectory planning heuristic algorithm taxi time taxi fuel consumption
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