The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condit...The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.展开更多
Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communic...Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communication of UAVs in denial environments with substantial electromagnetic interference,a systematic solution is proposed based on a deep learning algorithm for target detection and visible light for UAV tracking.Considering the cost and computational power limitations on the hardware,the you only look once(YOLO)v4-Tiny model is used for static target detection of the UAV model.For UAV tracking,and a light tracker that can adjust the angle of emitted light and focus it on the target is used for dynamic tracking processing.Thus,achieving the primary conditions of UAV optical communication with good secrecy is also suitable for dynamic situations.The UAV tracker positions the UAV model by returning the coordinates and calculating the time delay,and then controls the spotlight to target the UAV.In order to facilitate the deployment of deep learning models on hardware devices,the lighter and more efficient model is selected after comparison.The trained model can achieve 99.25%accuracy on the test set.The dynamic target detection can reach 20 frames per second(FPS)on a computer with an MX520 graphics processing unit(GPU)and 6 GB of random access memory(RAM).Dynamic target detection on a Jetson Nano can reach 5.4 FPS.展开更多
基金supported by the National Natural Science Foundation of China(62101099)the Chinese Postdoctoral Science Foundation(2021M690558,2022T150100,2018M633352,2019T120825)+3 种基金the Young Elite Scientist Sponsorship Program(YESS20200082)the Aeronautical Science Foundation of China(2022Z017080001)the Open Foundation of Science and Technology on Electronic Information Control Laboratorythe Natural Science Foundation of Sichuan Province(2023NSFSC1386)。
文摘The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.
文摘Unmanned aerial vehicles(UAV)are applied widely and profoundly in various fields.Moreover,high-precision positioning and tracking in multiple scenarios are the core requirements for UAV usage.To ensure stable communication of UAVs in denial environments with substantial electromagnetic interference,a systematic solution is proposed based on a deep learning algorithm for target detection and visible light for UAV tracking.Considering the cost and computational power limitations on the hardware,the you only look once(YOLO)v4-Tiny model is used for static target detection of the UAV model.For UAV tracking,and a light tracker that can adjust the angle of emitted light and focus it on the target is used for dynamic tracking processing.Thus,achieving the primary conditions of UAV optical communication with good secrecy is also suitable for dynamic situations.The UAV tracker positions the UAV model by returning the coordinates and calculating the time delay,and then controls the spotlight to target the UAV.In order to facilitate the deployment of deep learning models on hardware devices,the lighter and more efficient model is selected after comparison.The trained model can achieve 99.25%accuracy on the test set.The dynamic target detection can reach 20 frames per second(FPS)on a computer with an MX520 graphics processing unit(GPU)and 6 GB of random access memory(RAM).Dynamic target detection on a Jetson Nano can reach 5.4 FPS.
