This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a...This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a developed data processing algorithm for the HSCAT before launch. There were three test flights of the scatterometer, on January 15, 18 and 22, 2010, over the South China Sea near Lingshui, Hainan. The test flights successfully generated simultaneous airborne scatterometer normalized radar cross section(NRCS), ASCAT wind, and ship-borne-measured wind datasets, which were used to analyze HSCAT performance. Azimuthal dependence of the NRCS relative to the wind direction was nearly cos(2w), with NRCS minima at crosswind directions, and maxima near upwind and downwind. The NRCS also showed a small difference between upwind and downwind directions, with upwind crosssections generally larger than those downwind. The dependence of airborne scatterometer NRCS on wind direction and speed showed favorable consistency with the NASA scatterometer geophysical model function(NSCAT GMF), indicating satisfactory HSCAT performance.展开更多
针对先进高性能飞行器对高精度大气数据的测控需求,研发设计了一套适用于亚声速飞行器的嵌入式大气数据传感(flush air data sensing,FADS)系统。该系统首先基于数值建模技术建立了FADS系统模型的压力数据库,并针对建模数据精度及风洞...针对先进高性能飞行器对高精度大气数据的测控需求,研发设计了一套适用于亚声速飞行器的嵌入式大气数据传感(flush air data sensing,FADS)系统。该系统首先基于数值建模技术建立了FADS系统模型的压力数据库,并针对建模数据精度及风洞试验校准数据分析了Ma=0.2~0.4对应的压力误差限;其次,开发了攻角实时解算算法,并集成到工程原理样机中;最后基于风洞试验和飞行试验对FADS系统的实时解算算法及样机进行了系统评估,并通过事后模型算法对攻角进行重新解算以评估攻角实时解算算法的可靠性。结果表明:(1)与机载惯性导航系统等其他独立测试系统解算的数据相比,飞行试验中FADS系统采用的攻角实时解算方法精度整体较好,攻角误差小于1°,在关键段小于0.5°;基于不同模型建立的FADS系统攻角解算方法得到的攻角数值基本一致,证实了开发的实时解算算法的可靠性。(2)基于风洞试验及飞行试验数据对算法误差限的考核结果显示,飞行试验初始阶段实时解算的攻角值产生波动是压力输入波动误差限较大造成的,高空低速时的压力波动幅值大是实时解算攻角值偏差较大的主要原因;建立的FADS系统的攻角解算方法在算法误差限范围内的压力波动对攻角解算值影响较小,但超过算法误差限的压力波动对攻角解算值影响显著。高空低速飞行器FADS系统对测压传感器精度水平及工程实施水平要求较高,在实际工程应用中应尽量保证测压传感器的精度水平。展开更多
针对亚声速飞行器对高精度飞行参数的测控需求,研发了一套亚声速嵌入式大气数据传感(flush air data sensing,FADS)系统,集成工程样机,并通过风洞试验及飞行试验进行系统考核评估。基于计算流体动力学(computational fluid dynamics,CFD...针对亚声速飞行器对高精度飞行参数的测控需求,研发了一套亚声速嵌入式大气数据传感(flush air data sensing,FADS)系统,集成工程样机,并通过风洞试验及飞行试验进行系统考核评估。基于计算流体动力学(computational fluid dynamics,CFD)方法首先建立FADS系统压力数据库,并通过风洞试验考核了模型算法在低亚声速时的误差限;其次,集成融合实时解算算法的FADS工程原理样机;最后通过飞行试验考核了工程样机的工程适用性。结果表明:(1)与机载的其他独立测试系统相比,FADS攻角实时解算精度高,攻角偏差≤1°,关键段攻角偏差≤0.5°;事后重建的攻角数据与飞行试验FADS系统实时解算数据一致,证实FADS实时攻角解算方法可靠;(2)风洞及飞行试验校核数据表明,FADS实时攻角输出数据在飞行试验初始段的波动是由输入压力波动较大导致,特别是在高空低速段,输入压力波动幅值超过算法的误差限,导致实时攻角解算数值波动较大;(3)CFD仿真结果表明,输入压力波动位于算法误差限内对攻角输出精度影响较小,超过算法误差限的压力幅值波动对实时攻角输出精度影响极大。高空低速飞行器FADS系统对压力传感器等硬件精度及工程实现水平要求较高,应尽量保证工程实施精度。展开更多
为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model...为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model,ARIMA)模型预测无人机试飞俯仰角故障数据。结果表明,ARIMA预测结果:平均绝对误差(mean absolute error,MAE)为0.35,均方根误差(root mean square error,RMSE)为0.73,平均绝对百分比误差(mean absolute percentage error,MAPE)为23.80%;LSTM模型预测结果:MAE=0.49,RMSE=0.74,MAPE=45.20%;注意力机制+LSTM模型预测结果:MAE=0.17,RMSE=0.53,MAPE=18.93%。可见注意力机制+LSTM模型比其余两种模型更适合于试飞俯仰角的数据预测,以上3种方法对无人机故障数据预测都具有实际意义,有效的预测可以推进自动飞行器和移动机器人的异常检测或外国直接投资研究的最新进展,以进一步提高自动和远程飞行操作的安全性。展开更多
基金Supported by the National Natural Science Foundation of China(No.41106152)the National Science and Technology Support Program of China(No.2013BAD13B01)+3 种基金the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)the International Science&Technology Cooperation Program of China(No.2011DFA22260)the National High Technology Industrialization Project(No.[2012]2083)the Marine Public Projects of China(Nos.201105032,201305032,201105002-07)
文摘This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a developed data processing algorithm for the HSCAT before launch. There were three test flights of the scatterometer, on January 15, 18 and 22, 2010, over the South China Sea near Lingshui, Hainan. The test flights successfully generated simultaneous airborne scatterometer normalized radar cross section(NRCS), ASCAT wind, and ship-borne-measured wind datasets, which were used to analyze HSCAT performance. Azimuthal dependence of the NRCS relative to the wind direction was nearly cos(2w), with NRCS minima at crosswind directions, and maxima near upwind and downwind. The NRCS also showed a small difference between upwind and downwind directions, with upwind crosssections generally larger than those downwind. The dependence of airborne scatterometer NRCS on wind direction and speed showed favorable consistency with the NASA scatterometer geophysical model function(NSCAT GMF), indicating satisfactory HSCAT performance.
文摘针对先进高性能飞行器对高精度大气数据的测控需求,研发设计了一套适用于亚声速飞行器的嵌入式大气数据传感(flush air data sensing,FADS)系统。该系统首先基于数值建模技术建立了FADS系统模型的压力数据库,并针对建模数据精度及风洞试验校准数据分析了Ma=0.2~0.4对应的压力误差限;其次,开发了攻角实时解算算法,并集成到工程原理样机中;最后基于风洞试验和飞行试验对FADS系统的实时解算算法及样机进行了系统评估,并通过事后模型算法对攻角进行重新解算以评估攻角实时解算算法的可靠性。结果表明:(1)与机载惯性导航系统等其他独立测试系统解算的数据相比,飞行试验中FADS系统采用的攻角实时解算方法精度整体较好,攻角误差小于1°,在关键段小于0.5°;基于不同模型建立的FADS系统攻角解算方法得到的攻角数值基本一致,证实了开发的实时解算算法的可靠性。(2)基于风洞试验及飞行试验数据对算法误差限的考核结果显示,飞行试验初始阶段实时解算的攻角值产生波动是压力输入波动误差限较大造成的,高空低速时的压力波动幅值大是实时解算攻角值偏差较大的主要原因;建立的FADS系统的攻角解算方法在算法误差限范围内的压力波动对攻角解算值影响较小,但超过算法误差限的压力波动对攻角解算值影响显著。高空低速飞行器FADS系统对测压传感器精度水平及工程实施水平要求较高,在实际工程应用中应尽量保证测压传感器的精度水平。
文摘针对亚声速飞行器对高精度飞行参数的测控需求,研发了一套亚声速嵌入式大气数据传感(flush air data sensing,FADS)系统,集成工程样机,并通过风洞试验及飞行试验进行系统考核评估。基于计算流体动力学(computational fluid dynamics,CFD)方法首先建立FADS系统压力数据库,并通过风洞试验考核了模型算法在低亚声速时的误差限;其次,集成融合实时解算算法的FADS工程原理样机;最后通过飞行试验考核了工程样机的工程适用性。结果表明:(1)与机载的其他独立测试系统相比,FADS攻角实时解算精度高,攻角偏差≤1°,关键段攻角偏差≤0.5°;事后重建的攻角数据与飞行试验FADS系统实时解算数据一致,证实FADS实时攻角解算方法可靠;(2)风洞及飞行试验校核数据表明,FADS实时攻角输出数据在飞行试验初始段的波动是由输入压力波动较大导致,特别是在高空低速段,输入压力波动幅值超过算法的误差限,导致实时攻角解算数值波动较大;(3)CFD仿真结果表明,输入压力波动位于算法误差限内对攻角输出精度影响较小,超过算法误差限的压力幅值波动对实时攻角输出精度影响极大。高空低速飞行器FADS系统对压力传感器等硬件精度及工程实现水平要求较高,应尽量保证工程实施精度。
文摘为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model,ARIMA)模型预测无人机试飞俯仰角故障数据。结果表明,ARIMA预测结果:平均绝对误差(mean absolute error,MAE)为0.35,均方根误差(root mean square error,RMSE)为0.73,平均绝对百分比误差(mean absolute percentage error,MAPE)为23.80%;LSTM模型预测结果:MAE=0.49,RMSE=0.74,MAPE=45.20%;注意力机制+LSTM模型预测结果:MAE=0.17,RMSE=0.53,MAPE=18.93%。可见注意力机制+LSTM模型比其余两种模型更适合于试飞俯仰角的数据预测,以上3种方法对无人机故障数据预测都具有实际意义,有效的预测可以推进自动飞行器和移动机器人的异常检测或外国直接投资研究的最新进展,以进一步提高自动和远程飞行操作的安全性。
