基于EBSBL-BO算法的L-DACS系统干扰抑制方法

L-DACS System Interference Suppression Based on EBSBL-BO Algorithm

L频段数字航空通信系统(L-band digital aviation communication system,L-DACS)是未来面向航路阶段的空地数据链路,其工作频段部署在两个测距仪(distance measure equipment,DME)工作频段之间,为了消除测距仪产生的高功率脉冲信号对L-DACS系统前向链路正交频分复用接收机的干扰,本文提出基于扩展稀疏贝叶斯-边界优化(extended block sparse Bayesian learning-boundary optimization,EBSBL-BO)算法的高功率DME脉冲干扰抑制方法。首先,利用L-DACS系统正交频分复用接收机的空子载波建立DME干扰信号压缩感知模型;然后,基于EBSBL-BO算法对DME信号进行重构;最后将高功率DME脉冲信号在时域消除。仿真结果显示:本文算法与其他稀疏贝叶斯重构算法相比,本文算法DME脉冲信号重构精度更高,正交频分复用接收机误码率更低,可有效改善L-DACS系统正交频分复用接收性能。

L-band digital aviation communication system(L-DACS)is the future air-ground data link for the route stage.The working frequency band of L-DACS is set up between two channels of distance measure equipment(DME).In order to eliminate the interference of the high-power pulse signal generated by the DME on the orthogonal frequency-division multiplexing receiver of the L-DACS forward link,this article proposes a high-power DME pulse interference signal suppression method based on extended block sparse Bayesian learning-boundary optimization(EBSBL-BO)algorithm.Firstly,the compressed sensing model of the DME interference signal is constructed using the empty sub-carriers signals of the orthogonal frequency division multiplexing receiver of the L-DACS.Then the high-power pulse signal recoverd according to the EBSBL-BO algorithm.Finally,the reconstructed high-power DME pulse signals are removed in the time domain.Compared with other sparse Bayesian reconstruction algorithms,the algorithm proposed in this paper has higher reconstruction accuracy of DME pulse signal and lower bit error rate of OFDM receiver,which can further reduce bit error rate of orthogonal frequency-division multiplexing receiver and enhance the receiving performance of the L-DACS effectively.