基于APC算法的旁瓣抑制技术研究

发布时间：2018-05-16 10:07

本文选题：脉冲压缩 + 距离旁瓣抑制　；参考：《国防科学技术大学》2014年硕士论文

【摘要】：现代隐身技术的飞速发展和超低空突防技术的大量运用,使得目标的RCS降低或者信杂比降低,高分辨技术是检测低RCS或者低信杂比目标的有效途径。脉冲压缩和合成宽带为两种主要的形成高分辨距离像的技术,由于不能获得较为理想的低距离旁瓣,可能会出现弱小目标被强目标的高距离旁瓣掩盖的情况。本文研究利用自适应脉冲压缩技术(APC)减少高分辨成像过程中的距离旁瓣,以提高弱小目标的检测能力。论文工作如下:第二章首先介绍了传统的脉冲压缩和匹配滤波器原理,并分析了匹配滤波器常用的几种窗函数旁瓣抑制性能;然后针对LFM信号波形,介绍了基于最小均方误差(MMSE)准则的自适应脉冲压缩(APC)算法的基本原理和步骤。仿真结果表明,相比于传统的加窗抑制旁瓣方法,APC算法旁瓣抑制能力更强,能够提高信号的距离分辨率,更好地检测强目标旁瓣掩盖下的弱小目标。第三章构建了频率步进(SF)雷达的APC算法的模型,并推导了基于RMMSE准则的SF的APC算法和步骤。仿真试验表明,APC算法能够有效抑制IFFT成像处理的高距离旁瓣,比加窗处理的距离旁瓣抑制效果更好,且避免了主瓣展宽的缺点,提高了在邻近多目标场景中弱小目标的检测性能;针对运动目标场景,分析了目标运动的速度补偿精度要求,推导了运动目标的频率步进雷达APC算法。仿真试验表明,APC算法对于运动目标的成像效果同样优于IFFT变换和加窗处理。第四章根据空时自适应处理(STAP)的方法,将距离像上的APC算法扩展到空间-距离域(Space-Range),介绍了空间-距离域二维的自适应脉冲压缩算法(SR-APC),来同时抑制方位像和距离像上的旁瓣,通过仿真实验表明,SR-APC算法能够较好地抑制方位像旁瓣和距离像旁瓣,在邻近多目标的二维成像中,更好地分辨出弱小目标。在此基础上,提出一种降维的SR-APC算法,在旁瓣抑制能力有限下降的前提下,减少算法的计算量。
[Abstract]:With the rapid development of modern stealth technology and the extensive application of ultra-low altitude penetration technology, the RCS or signal-to-clutter ratio of target is reduced. High resolution technology is an effective way to detect low RCS or low signal-to-clutter ratio targets. Pulse compression and synthetic wideband are two main techniques to form high resolution range profile. Because we can not obtain ideal low range sidelobe, the dim target may be masked by high range sidelobe of strong target. In this paper, the adaptive pulse compression technique (APC) is used to reduce the range sidelobes in high resolution imaging to improve the detection ability of small and weak targets. The main work of this paper is as follows: in chapter 2, the traditional pulse compression and matched filter principle are introduced, and several kinds of window function sidelobe suppression performance of matched filter are analyzed, and then the waveform of LFM signal is analyzed. The basic principle and steps of adaptive pulse compression (APC) algorithm based on minimum mean square error (MMSE) criterion are introduced. The simulation results show that compared with the traditional windowed sidelobe suppression method, the sidelobe suppression ability of the APC algorithm is stronger, the range resolution of the signal can be improved, and the weak target under the sidelobe masking can be better detected. In chapter 3, the APC algorithm model of frequency stepping SF) radar is built, and the APC algorithm and steps of SF based on RMMSE criterion are deduced. The simulation results show that the proposed algorithm can effectively suppress the high range sidelobe of IFFT imaging, which is more effective than the windowed sidelobe suppression, and avoids the shortcoming of the main lobe broadening. The detection performance of small and weak targets in adjacent multi-target scenes is improved, and the accuracy requirement of velocity compensation for moving targets is analyzed, and the frequency stepping radar APC algorithm of moving targets is deduced. The simulation results show that the algorithm is better than IFFT transform and windowing. In chapter 4, according to the method of space-time adaptive processing (STAP), the APC algorithm on range profile is extended to Space-Rangen in space-distance domain. An adaptive pulse compression algorithm in space-range domain is introduced, which can suppress both azimuth image and sidelobe in range image. The simulation results show that the SR-APC algorithm can suppress the sidelobe of azimuth image and the sidelobe of range image, and can better distinguish small and weak targets in the 2-D imaging of adjacent multi-targets. On this basis, a dimensionally reduced SR-APC algorithm is proposed to reduce the computational complexity of the algorithm under the condition that the sidelobe suppression capacity is limited.
【学位授予单位】：国防科学技术大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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