用于ADS-B解交织的高增益稳健PA算法

A Robust and High Gain Algorithm for Separating Overlapped ADS-B Signal Based on PA

广播式自动相关监视(Automatic Dependent Surveillance-Broadcast,ADS-B)是基于全球卫星定位系统的航空器运行监视技术,由于ADS-B信号随机接入的广播方式和不断增加的空域流量,不可避免会带来信号交织问题,造成解码信息错误或丢失。本文基于正交投影(Project Algorithm,PA),利用天线阵带来的信号处理增益,提出了一种高增益稳健的解交织算法:首先利用PA估计源信号的导向矢量,然后结合Capon波束形成算法,提高解交织信号的输出信噪比,考虑导向矢量的估计误差,本文将稳健波束形成(Robust Capon Beamforming,RCB)算法应用于此,从而进一步提高解交织算法的稳健性。仿真和实采数据结果均验证了本文所提算法能够较稳健地提高解交织信号的输出信噪比。

Automatic Dependent Surveillance-Broadcast(ADS-B)is the monitoring technology of aircraft based on the global positioning system.Due to the random access of ADS-B signal and the increasing of airspace traffic,signal overlapping was inevitable.Overlapped signal would seriously affect the decoding of ADS-B signals,resulting in erroneous decoding information or loss.In this paper,a robust and high gain algorithm of overlapped signal processing based on Project Algorithm(PA)was proposed,which used gain from array antennas.Firstly,the steering vector of source signals were estimated by PA.Then,combining the Capon beamforming algorithm,the output SNR of the separated signal is improved.In addition,considering the estimation error of the steering vector,this paper applied the Robust Capon Beamforming(RCB)algorithm to further improve the robustness of the separation algorithm.Through simulation and test experiments,it is verified that the proposed algorithm can improve the output SNR of the signal more robust.