For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.How...For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.展开更多
This paper proposes a novel unmanned aerial vehicle(UAV)-based illegal radio station(IRS) localization scheme, where the transmit power of the IRS, the channel model and the noise model are unknown to the UAV. A direc...This paper proposes a novel unmanned aerial vehicle(UAV)-based illegal radio station(IRS) localization scheme, where the transmit power of the IRS, the channel model and the noise model are unknown to the UAV. A direction-aware Q-learning algorithm is developed to process received signal strength(RSS) values collected by a directional antenna, as well as directions corresponding to the RSS values. This algorithm determines the direction the UAV flies towards and thereby finds the IRS. The proposed scheme is compared to two baseline schemes. One baseline locates the IRS by a UAV equipped with an omnidirectional antenna, where conventional Q-learning is exploited to process the measured RSS and determine the UAV's trajectory. The other baseline locates the IRS by a directional-antenna UAV, where the UAV flies towards the direction with respect to the maximum RSS value. Numerical results show that, especially for a low receive SNR, the proposed scheme can outperform the two baselines in terms of the localization efficiency, providing a smoother trajectory for the UAV.展开更多
The wireless communication systems based on Unmanned Aerial Vehicles(UAVs) have found a wide range of applications recently. In this paper, we propose a new three-dimensional(3 D) non-stationary multiple-input multipl...The wireless communication systems based on Unmanned Aerial Vehicles(UAVs) have found a wide range of applications recently. In this paper, we propose a new three-dimensional(3 D) non-stationary multiple-input multiple-output(MIMO) channel model for the communication links between the UAV and mobile terminal(MT). The new model originates the traditional geometry-based stochastic models(GBSMs) but considers the non-stationary propagation environment due to the rapid movements of the UAV, MT, and clusters. Meanwhile, the upgrade time evolving algorithms of time-variant channel parameters, i.e., the path number based on birth-death processes of clusters, path delays, path powers, and angles of arrival and departure, are developed and optimized. In addition, the statistical properties of proposed GBSM including autocorrelation function(ACF), cross-correlation function(CCF), and Doppler power spectrum density(DPSD) are investigated and analyzed. Simulation results demonstrate that our proposed model provides a good agreement on the statistical properties with the corresponding derived theoretical ones, which indicates its usefulness for the performance evaluation and validation of the UAV based communication systems.展开更多
构建基于无人机基站(Unmanned Aerial Vehicle Base Station, UBS)的空地网络是解决移动通信网络覆盖等问题的重要途径。区别于地面移动通信网络,空地网络需要对UBS位置和用户关联进行联合优化。针对上述问题,首先通过构建二进制无线电...构建基于无人机基站(Unmanned Aerial Vehicle Base Station, UBS)的空地网络是解决移动通信网络覆盖等问题的重要途径。区别于地面移动通信网络,空地网络需要对UBS位置和用户关联进行联合优化。针对上述问题,首先通过构建二进制无线电地图(Binary Radio Map, BRM)使得UBS能够有效获取整个任务区域中用户位置关联的信道知识,在此基础上提出基于BRM的离线多UBS部署与用户关联联合规划方法。该方法以最大化网络效用函数为目标,通过互嵌套的启发式UBS部署位置搜索和基于匹配博弈的UBS-用户匹配实现UBS位置和用户关联的离线优化。在复杂城市环境下,相比于参考方案,所提方法可使得用户和速率性能提升10%~40%。展开更多
基金supported in part by the National Natural Science Foundations of China(Nos.61304223,61673209,61533008)the Aeronautical Science Foundation(No.2016ZA 52009)the Fundamental Research Funds for the Central Universities(No.NJ20160026)
文摘For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.
基金supported by China NSF Grants(61631020)Fundamental Research Funds for the Central Universities(NP2018103,NE2017103,NC2017003)
文摘This paper proposes a novel unmanned aerial vehicle(UAV)-based illegal radio station(IRS) localization scheme, where the transmit power of the IRS, the channel model and the noise model are unknown to the UAV. A direction-aware Q-learning algorithm is developed to process received signal strength(RSS) values collected by a directional antenna, as well as directions corresponding to the RSS values. This algorithm determines the direction the UAV flies towards and thereby finds the IRS. The proposed scheme is compared to two baseline schemes. One baseline locates the IRS by a UAV equipped with an omnidirectional antenna, where conventional Q-learning is exploited to process the measured RSS and determine the UAV's trajectory. The other baseline locates the IRS by a directional-antenna UAV, where the UAV flies towards the direction with respect to the maximum RSS value. Numerical results show that, especially for a low receive SNR, the proposed scheme can outperform the two baselines in terms of the localization efficiency, providing a smoother trajectory for the UAV.
基金supported by the National Key Scientific Instrument and Equipment Development Project(Grant No.2013YQ200607)China NSF Grants(Grant No.61631020)+1 种基金Aeronautical Science Foundation of China(Grant No.2017ZC52021)Open Foundation for Graduate Innovation of NUAA(Grant No.kfjj20170405 and kfjj20180408)
文摘The wireless communication systems based on Unmanned Aerial Vehicles(UAVs) have found a wide range of applications recently. In this paper, we propose a new three-dimensional(3 D) non-stationary multiple-input multiple-output(MIMO) channel model for the communication links between the UAV and mobile terminal(MT). The new model originates the traditional geometry-based stochastic models(GBSMs) but considers the non-stationary propagation environment due to the rapid movements of the UAV, MT, and clusters. Meanwhile, the upgrade time evolving algorithms of time-variant channel parameters, i.e., the path number based on birth-death processes of clusters, path delays, path powers, and angles of arrival and departure, are developed and optimized. In addition, the statistical properties of proposed GBSM including autocorrelation function(ACF), cross-correlation function(CCF), and Doppler power spectrum density(DPSD) are investigated and analyzed. Simulation results demonstrate that our proposed model provides a good agreement on the statistical properties with the corresponding derived theoretical ones, which indicates its usefulness for the performance evaluation and validation of the UAV based communication systems.
文摘构建基于无人机基站(Unmanned Aerial Vehicle Base Station, UBS)的空地网络是解决移动通信网络覆盖等问题的重要途径。区别于地面移动通信网络,空地网络需要对UBS位置和用户关联进行联合优化。针对上述问题,首先通过构建二进制无线电地图(Binary Radio Map, BRM)使得UBS能够有效获取整个任务区域中用户位置关联的信道知识,在此基础上提出基于BRM的离线多UBS部署与用户关联联合规划方法。该方法以最大化网络效用函数为目标,通过互嵌套的启发式UBS部署位置搜索和基于匹配博弈的UBS-用户匹配实现UBS位置和用户关联的离线优化。在复杂城市环境下,相比于参考方案,所提方法可使得用户和速率性能提升10%~40%。
