雷达高速弱目标长时间积累方法研究

发布时间：2018-02-04 08:09

本文关键词： 高速弱目标长时间积累 Keystone变换 Radon-Fourier变换　出处：《哈尔滨工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：现代战争中，高速机动的低可探测目标对雷达的探测能力提出了严峻的挑战。信号的长时间积累是提高回波信噪比、改善雷达对高速运动弱目标探测能力的有效途径。针对脉冲多普勒雷达在凝视工作模式下，本文重点就目标匀速直线运动和匀加速直线运动回波模型的建立，回波跨距离单元走动和多普勒扩展现象的分析以及目标回波的长时间相参积累问题进行了研究。希望在未知目标运动参数的情况下，改善目标回波的积累效果，提高雷达对高速运动弱目标的检测性能。在匀速直线运动目标回波模型下，针对目标跨距离单元走动的现象，分别介绍了基于Keystone变换和基于Radon-Fourier变换的长时间积累算法；提出了基于Radon变换的多普勒模糊因子估计方法，通过仿真实验验证了方法的有效性。根据仿真实验得出结论：Keystone变换能够在目标运动参数未知的情况下实现包络补偿，但是在处理多目标问题时将比较复杂。Radon-Fourier变换通过对目标距离和速度的联合搜索，能够同时实现目标运动轨迹的提取和回波能量的积累，避免了多普勒模糊因子估计的问题，，但是需要注意盲速旁瓣问题。在匀加速直线运动目标回波模型下，针对目标的多普勒频率扩展现象，提出了基于Keystone变换和二次相位补偿的算法、基于二阶Keystone变换联合RFT处理的算法以及基于二阶广义Radon-Fourier变换的算法。针对多普勒调频率估计问题，分别介绍了基于Dechirping、改进的Chirp-Fourier变换以及分数阶傅里叶变换的方法，通过仿真实验验证了方法的有效性。根据仿真实验：基于Keystone变换的方法同样无法避免多普勒模糊因子估计的问题，在多目标情况下的应用受到限制；基于二阶Keystone变换联合RFT处理的方法，适用于多目标处理，但是在多普勒调频率估计时对信噪比要求较高；基于二阶广义RFT的方法能够通过目标距离、速度、加速度的三维搜索实现目标回波能量的相参积累，但是运算量较大，不适合工程实现。
[Abstract]:In modern warfare, the low detectable target with high speed maneuvering poses a severe challenge to radar detection ability. The long time accumulation of signal is to improve the signal to noise ratio (SNR) of echo. The effective way to improve the detection ability of radar to the weak target with high speed. In view of the staring mode of the pulsed Doppler radar, this paper focuses on the establishment of the echo model of the target with uniform linear motion and uniform acceleration linear motion. In this paper, the problem of echo traversing and Doppler spreading and the long time coherent accumulation of target echo are studied. It is hoped that the effect of target echo accumulation can be improved when the moving parameters of the target are unknown. The detection performance of radar for high speed moving weak target is improved. Under the echo model of the target with uniform velocity linear motion, the phenomenon of moving across the range unit of the target is studied. Long time accumulation algorithms based on Keystone transform and Radon-Fourier transform are introduced respectively. A Doppler fuzzy factor estimation method based on Radon transform is proposed. The effectiveness of the method is verified by simulation experiments. According to the simulation experiment, it is concluded that the envelope compensation can be realized when the moving parameters of the target are unknown. But when dealing with the multi-objective problem, it will be more complicated. Radon-Fourier transform can search the distance and velocity of the target through the joint search. It can simultaneously realize the extraction of target trajectory and the accumulation of echo energy, thus avoiding the problem of Doppler fuzzy factor estimation, but attention should be paid to the blind velocity sidelobe problem. Based on Keystone transform and quadratic phase compensation, an algorithm based on Keystone transform and quadratic phase compensation is proposed for the Doppler frequency spread phenomenon of the target with uniform acceleration linear moving target echo model. The algorithm based on the second order Keystone transform combined with RFT processing and the algorithm based on the second order generalized Radon-Fourier transform. The methods based on Dechirping, improved Chirp-Fourier transform and fractional Fourier transform are introduced respectively. The validity of the method is verified by simulation experiments. According to the simulation experiment, the method based on Keystone transform can not avoid the problem of Doppler fuzzy factor estimation. Applications in multi-objective situations are limited; The method based on second-order Keystone transform combined with RFT processing is suitable for multi-target processing, but the signal-to-noise ratio (SNR) is very high in Doppler frequency estimation. The method based on second-order generalized RFT can realize the coherent accumulation of target echo energy by 3D search of target distance, velocity and acceleration, but it is not suitable for engineering because of its large computation.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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