准随机跳频信号最大旁瓣抑制及其神经网络实现

MAXIMUM SIDELOBE SUPPRESSION FOR QUASI-RANDOM STEP FREQUENCY SIGNAL AND ITS NEURAL NETWORK IMPLEMENTATION

高频雷达工作在电磁环境十分恶劣的短波段,为避开干扰严重的频段,采用一种准随机跳频信号。这种信号经匹配处理后距离旁瓣很高,严重影响了雷达的性能。该文详细地分析了这种信号,提出一种距离旁瓣处理技术,并采用神经网络来实现优化计算.仿真表明算法具有较好的数值稳定性,能有效地抑制最大旁瓣。

Operating in the heavy congested SW band, HF radars use a quasi-random step frequency signal to avoid the interference bands. However, the sidelobe of this signal after matching processing is very high, thus would greatly debase the radar's performance. In this paper, a range sidelobe processing technique is proposed on a basis of delicate signal analysis and a NN based algorithm is applied to realize the optimization computing. Simulation results demonstrate this method could successfully suppress the maximum sidelobe with good numerical stability.