基于BSBL-BO算法的DME脉冲干扰抑制方法

针对测距仪(distance measure equipment, DME)信号干扰L频段数字航空通信系统1(L-band digital aeronautical communication system 1, L-DACS1)正交频分复用(orthogonal frequency-division multiplexing, OFDM)接收机的问题, 提出基于块稀疏贝叶斯学习-边界优化(block sparse bayesian learning-the bound optimization, BSBL-BO)算法的DME脉冲干扰抑制方法。首先, 利用OFDM接收机空子载波不传输有用信号的特点构造针对DME脉冲干扰信号的压缩感知模型; 然后基于BSBL-BO算法重构DME脉冲干扰信号; 最后在时域进行干扰消除。仿真结果表明, 该方法比已有的脉冲干扰抑制方法具有更高的重构精度和更快的运算速度, 进一步降低了OFDM接收机的误比特率, 提高了L-DACS1系统前向链路传输性能。

DME pulse interference suppression method based on BSBL-BO algorithm

In view of the problem of the distance measure equipment (DME) signal interferes with orthogonal frequency-division multiplexing (OFDM) receiver for L-band digital aeronautical communication system 1 (L-DACS1), a DME interference suppression method based on block sparse Bayesian learning-the bound optimization (BSBL-BO) algorithm is proposed. Firstly, considering that the empty subcarriers of OFDM receiver never transmit useful signals, the compressed sensing model for DME pulse interference signal is established. Then the DME pulse interference signal is reconstructed based on the BSBL-BO algorithm.Finally, the reconstructed DME pulse interference is eliminated in the time domain. The simulation results show that this method has higher reconstruction accuracy and faster operation speed than the existing pulse interference suppression methods, which can further reduce the bit error rate of OFDM receiver and improve the trans-mission performance of forward link in L-DACS1 system significantly.