针对测距仪(distance measure equipment，DME)信号严 重干扰L频段数字航空通信系统(L-band digital aviation communication system，L-DACS)前向链路接收机的问题，提出基于相关稀疏变分贝叶斯(correla-ted sparse variational Bayesian，cSVB)算法的DME脉冲干扰抑制方法。所提方法利用L-DACS系统正交频分复用(orthogonal frequency division multiplexing，OFDM)接收机的空子载波信息构建接收信号的压缩感知方程;然后，根据cSVB算法进行三层次贝叶斯信号建模，最后选择了两种变体算法重构DME干扰信号，并将其从时域接收信号中去除。理论分析与仿真结果表明，所提出的干扰抑制方法可以充分利用信号先验信息，进一步降低DME干扰信号估计的归一化均方误差，有效改善L-DACS系统的误码性能，提高传输可靠性。
DME pulse interference suppression method based on cSVB algorithm
To solve the problem that the distance measure equipment(DME)signal seriously interferes with the forward link receiver of L-band digital aviation communication system(L-DACS),a DME pulse interference suppression method based on correlated sparse variational Bayesian(cSVB)algorithm is proposed.In this method,the empty subcarrier information of the orthogonal frequency division multiplexing(OFDM)receiver of L-DACS system is used to construct the compressed sensing equation of the received signal.Then,three-level Bayesian signal modeling is carried out according to the cSVB algorithm.Finally,two variant algorithms are selected to reconstruct DME interference signal and remove it from the received signal in the time domain.Theoretical analysis and simulation results show that the proposed interference suppression method can make full use of prior information and further reduce the normalized mean square error of DME interference signal estimation,effectively improve the error performance of L-DACS system,and enhance the transmission reliability.
L-band digital aviation communication system(L-DACS)distance measure equipment(DME)block sparse Bayesianvariational Bayesian inference
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