随机噪声雷达的脉冲压缩方法研究

文中针对传统的匹配滤波算法在进行脉冲压缩时存在的高距离旁瓣问题,提出了将卡尔曼滤波法和Pisarenko法应用于随机噪声雷达的脉冲压缩。在建立随机噪声雷达系统模型的基础上,详细论述了卡尔曼滤波法和Pisarenko法在该系统脉冲压缩中的实现方法。通过仿真试验对这两种方法的脉冲压缩性能进行了对比分析。结果表明,卡尔曼滤波法和Pisarenko法都能够在不牺牲分辨率的基础上有效地改善随机噪声雷达的脉冲压缩性能,降低脉冲压缩的

Study on Pulse Compression Methods for Random Noise Radar

Applying traditional matched filter to pulse compression leads to high range sidelobes.In this paper,performance of the Kalman filter and pisarenko for pulse compression in random noise radar are discussed.With the model of random noise radar system,this paper shows the realization of Kalman filter and Pisarenko in pulse compression in this system,and compares these two methods by computer simulation.The results demonstrate that both methods can improve the pulse compression of random noise radar without sacrificing resolution.