雷达低速目标检测方法研究

发布时间：2018-03-31 00:21

本文选题：低速目标　切入点：Kalmus　出处：《西安电子科技大学》2014年硕士论文

【摘要】：现代的空中威胁除了传统的各类轰炸机、歼击机、弹道导弹等高速或高机动目标外,还增加了无人机、武装直升机等低速目标,形成了新一轮的空中威胁,对雷达提出了低速目标探测的要求。由于低速目标一般在低空飞行,必须考虑杂波对检测的影响。杂波强度一般都很大,所以雷达在检测目标之前必须先抑制杂波。由于低速目标在多普勒域与杂波存在严重的交叠,传统的频域滤波处理在抑制杂波的同时也抑制目标信号从而难以提高信杂比,这就是低速目标难以检测的原因。针对这一问题,本文对各种低速目标检测方法进行了研究和分析。本文首先介绍了传统的低速目标检测方法,即Kalmus滤波器和杂波图检测方法。Kalmus滤波器能抑制杂波的同时尽可能的保留低频分量,有效提高低速目标的信杂比。本文通过比较它与FIR滤波器的性能,通过仿真验证了Kalmus滤波器确实更加适合低速目标检测。杂波图检测技术是利用了杂波在时间上满足准平稳性通过所谓的时域CFAR来检测目标,本文分析了其检测性能,并结合Kalmus滤波器给出了一种雷达低速目标检测方案。接着本文研究了一些现代信号处理方法,包括AR谱估计、Capon谱估计、超分辨方法和经验模态分解方法,并通过仿真分析了它们的性能和缺陷。与基于傅氏变换的经典谱分析方法相比,现代谱估计方法有望获得更高频率分辨率,另外经验模态分解是一种数据自适应的信号分析方法。接着本文重点研究了悬停直升机的检测方法,悬停直升机是一种典型的低速目标,它的主旋翼回波具有特殊性质。通过分析主旋翼回波信号模型,讨论了直升机主旋翼回波检测对雷达性能的要求,同时给出了时域双门限检测方法并分析了该方法的检测性能。最后介绍了直升机主旋翼回波的长时间积累方法并分析了其性能。
[Abstract]:Modern air threats, in addition to traditional high-speed or high-mobility targets such as bombers, fighter planes, ballistic missiles, and so on, have also increased the number of low-speed targets such as drones and helicopter gunships, thus forming a new round of air threats. The requirement of low speed target detection is put forward for radar. Since the low speed target usually flies at low altitude, the influence of clutter on detection must be considered. Therefore, radar must suppress clutter before detecting target. Because there is a serious overlap between low speed target and clutter in Doppler domain, the traditional frequency domain filter can suppress clutter and suppress target signal at the same time, so it is difficult to improve the signal-to-clutter ratio. This is the reason why it is difficult to detect low speed target. In order to solve this problem, various low speed target detection methods are studied and analyzed in this paper. Firstly, the traditional low speed target detection method is introduced in this paper. That is, Kalmus filter and clutter detection method. Kalmus filter can suppress clutter while keeping low frequency component as much as possible, and effectively improve the signal-to-clutter ratio of low speed target. This paper compares its performance with that of FIR filter. The simulation results show that the Kalmus filter is more suitable for low speed target detection. The clutter detection technique uses the clutter to satisfy the quasi-stationarity in time and uses the so-called time domain CFAR to detect the target. In this paper, the detection performance is analyzed. A low speed target detection scheme based on Kalmus filter is presented. Then some modern signal processing methods are studied, including AR spectrum estimation, superresolution method and empirical mode decomposition method. Compared with the classical spectrum analysis method based on Fourier transform, the modern spectrum estimation method is expected to obtain higher frequency resolution. In addition, empirical mode decomposition (EMD) is a data adaptive signal analysis method. Secondly, the detection method of hovering helicopter is studied, which is a typical low-speed target. Its main rotor echo has special properties. By analyzing the main rotor echo signal model, the radar performance requirements of helicopter main rotor echo detection are discussed. At the same time, the time domain double threshold detection method is presented and its detection performance is analyzed. Finally, the long time accumulation method of helicopter main rotor echo is introduced and its performance is analyzed.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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