DAI Shu-xian, ZHANG Yu-jin, PENG Dong-sheng, et al. Target tracking and localization algorithm for UAV based on RPCCA[J]. 2019, (4): 132-134+138. DOI: 10.13873/J.1000-9787(2019)04-0132-03.
基于RPCCA的无人机目标跟踪定位算法
摘要
针对目前无人机(UAV)对于行人目标的识别准确度不高
数据传输不稳定并且易受干扰和现有无人机目标跟踪系统一般是利用卫星信号进行定位
传输数据成本较高且具有一定的局限性的问题
提出了基于正则化成对约束组件分析的无人机目标跟踪定位算法
利用正则化成对约束组件分析实现了无人机对目标的准确识别
利用WiFi进行大数据稳定、实时的传输
与基于卫星的定位算法可以形成互补
在此基础上
利用扩频通信进行重要数据的准确传输
改善了系统的抗干扰性能。实验结果表明:该算法不仅可以有效地识别与跟踪目标
而且可以实时传输无人机的位姿参数与目标检测结果。
Abstract
Aiming at the problem that at present
identification accuracy of the unmanned aerial vehicle( UAV)for pedestrian is not high
data transmission is unstable
and it is susceptible to interference and the existing UAV target tracking system generally uses satellite signals for positioning
and the cost of data transmission is high
and has limitations
a target tracking and localization algorithm for UAV based on regularized pairwise constraint component analysis is proposed. Regularized paired constraint component analysis realizes the accurate identification of the target by the UAV
and realizes stable and real-time transmission of big data by using Wi Fi
complement with satellite-based positioning algorithm. On this basis
the spread spectrum communication( SSC) is used to accurately transmit important data
which improves the anti-interference performance of the system. The experimental results show that the algorithm can not only effectively identify and track target
but also transmit the attitude parameters and target detection results of the UAV in real-time.