Kangkang Li
Kangkang Li has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Chao Cheng
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China
1 shared publication - Haodong Sun
Weiqiao-UCAS (Binzhou) Science and Technology Co., Ltd., Binzhou 256600, China
1 shared publication - Jianping Yuan
Binzhou Institute of Technology, Binzhou 256606, China
1 shared publication - Mengbi Wang
Center for Aerospace Integration Technology, Binzhou Institute of Technology, Binzhou 256600, China
1 shared publication - Zhongjing Ren
School of Mechanical Engineering, Shandong University, Jinan 250061, China
1 shared publication
Latest Publications
- Open Access
Bearing-Only Three-UAV Cooperative Target Localization with Adaptive Weighting and Configuration Optimization
This paper addresses bearing-only three-dimensional target localization using three cooperative UAVs under observation inconsistency and degraded geometry. A weighted point-to-line least-squares localization model is established to fuse multiple line-of-sight (LOS) observations derived from image measurements, camera calibration, and UAV poses. To handle unreliable measurements without ground truth, a reliability assessment mechanism is developed by combining geometric stability indicators with observation consistency metrics, enabling weak geometry and abnormal observations to be identified online. Based on this assessment, an adaptive optimization framework is introduced to perform residual-driven adaptive weighting and configuration optimization, thereby suppressing unreliable LOS measurements and improving the conditioning of cooperative geometry. Simulation results under four representative scenarios show that the proposed method consistently improves localization accuracy and robustness. The mean localization error is reduced from 0.545 m to 0.260 m under abnormal observations, from 0.355 m to 0.081 m under degraded geometry, and from 0.711 m to 0.280 m when both effects occur simultaneously. Statistical evaluations including RMSE, standard deviation, maximum error, confidence intervals, and box-plot analysis further demonstrate that the proposed framework effectively reduces error dispersion and improves robustness.
Open AccessBearing-Only Three-UAV Cooperative Target Localization with Adaptive Weighting and Configuration Optimization
This paper addresses bearing-only three-dimensional target localization using three cooperative UAVs under observation inconsistency and degraded geometry. A weighted point-to-line least-squares localization model is established to fuse multiple line-of-sight (LOS) observations derived from image measurements, camera calibration, and UAV poses. To handle unreliable measurements without ground truth, a reliability assessment mechanism is developed by combining geometric stability indicators with observation consistency metrics, enabling weak geometry and abnormal observations to be identified online. Based on this assessment, an adaptive optimization framework is introduced to perform residual-driven adaptive weighting and configuration optimization, thereby suppressing unreliable LOS measurements and improving the conditioning of cooperative geometry. Simulation results under four representative scenarios show that the proposed method consistently improves localization accuracy and robustness. The mean localization error is reduced from 0.545 m to 0.260 m under abnormal observations, from 0.355 m to 0.081 m under degraded geometry, and from 0.711 m to 0.280 m when both effects occur simultaneously. Statistical evaluations including RMSE, standard deviation, maximum error, confidence intervals, and box-plot analysis further demonstrate that the proposed framework effectively reduces error dispersion and improves robustness.