相控阵雷达与频谱无人机监测平台的数据处理与融合

Data Processing and Fusion of Phased Array Radar and Spectrum UAV Monitoring Platforms

为了提升安防系统对于无人机的侦测能力,以相控阵雷达、频谱无人机侦测系统为硬件基础,提出了雷达去噪算法以及多源异构数据融合算法来提升无人机侦测系统的有效性及准确性。其中,提出了基于批号库更新策略的雷达去噪算法,该算法解决了相控阵雷达系统的侦测结果存在噪声点的问题,使得侦测结果更清楚、准确。针对雷达和频谱侦测目标坐标存在误差,将雷达系统侦测到的距离信息与频谱系统侦测到的角度信息相结合,提出了多源异构数据融合算法,解决了相控阵雷达和频谱系统数据融合的问题。通过实地无人机的放飞实验,证明了所提出方法的有效性。

In order to improve the detection capability of existing security systems for UAVs,this paper proposes a radar denoising algorithm and a multi-source heterogeneous data fusion algorithm to improve the effectiveness and accuracy of UAV detection systems based on phased-array radar and spectrum UAV detection systems.This paper proposes a radar denoising algorithm based on the batch number library update strategy,the algorithm solves the problem that the detection results of the phased array radar system have noise points,making the detection results clearer and more accurate.In order to reduce error in the target coordinates detected by radar and spectrum,the distance information detected by the radar system is combined with the angle information detected by the spectrum system,thus a multi-source heterogeneous data fusion algorithm is proposed to solve the problem of data fusion between phased array radar and spectrum system.The effectiveness of the proposed method is proved by the field UAV release experiment.