随着现代软件无线电技术的飞速发展,战场电磁信号环境从地面、空中、海上到太空,信号密度大,频谱宽,变换复杂,并且多功能数字雷达的多种工作方式和多种波形变换,雷达反侦察、抗干扰能力不断增强,传统的雷达信号分选跟踪方法面临着严峻的挑战。文中分析了几种传统的信号分选方法,从复杂电磁环境信号中,分析盲信号分选、聚类神经网络分选、脉内细微特性分选法,从信号分选的参数上进行多参数联合分选,并且通过多信号模拟器进行实验仿真,在分选的基础上进行跟踪处理,信号参数稳定、效果良好。

With the rapid development of modern software radio technology, the battlefield electromagnetic signal environment is from the ground, air, sea and even in space. With the density signals, the wide spectrum, complex transform, and a variety of operating mode and multi-function digital radar waveform, and the anti-reconnaissance, anti-jamming continuously enhanced, the traditional method for radar signals tracking and sorting is faced with severe challenges. Several traditional methods of signal sorting are analyzed. The blind signals, sorting clustering neural network, the slight characteristics of pulse sorting method are analyzed in the signal from a complex electromagnetic environment, multi-parameter signal from the sorting parameters are combined sorted and simulated through multi-signal simulator, track processing ,which are shown to be stable and effective.