基于Keystone变换的高速运动目标检测方法研究

发布时间：2018-05-07 06:12

本文选题：越距离单元走动 + Keystone变换　；参考：《南京大学学报(自然科学)》2014年01期

【摘要】：高速运动目标脉间存在越距离单元走动,且多普勒频谱混叠,脉间相参积累困难.利用长时间的信号积累,来提高微弱高速运动目标在低信噪比下的检测性能理论上是一种有效方法,但积累时间长,使得目标回波越距离单元走动,相参积累更加困难.进行速度提前预估计的方法,能很好提高检测性能,但增加了技术难度,并且需要长的检测时间.本文研究一种改进的Keystone变换方法,该方法是通过计算不同模糊系数时的所有回波脉冲峰值位置的方差,记录下方差最小时的模糊系数,利用该模糊系数,结合运用SINC函数插值实现的变换方法.该变换方法不受目标回波积累时间的限制,无需预先估计目标速度,可同时实现解多普勒模糊和补偿距离走动.仿真结果表明,与进行匹配滤波后相参积累的方法相比,结合最小方差法和Keystone变换的方法,能有效补偿距离走动,去除多普勒模糊,有效提高了高速运动目标回波脉冲积累的信噪比,改善了雷达的检测性能.
[Abstract]:There are moving units between high speed moving targets, and the Doppler spectrum is overlapped, so it is difficult to accumulate coherence between pulses. Using long time signal accumulation to improve the detection performance of weak high speed moving targets at low SNR is theoretically an effective method, but the long accumulation time makes it more difficult for the target echo to move over the range unit and the coherent accumulation becomes more difficult. The method of speed pre-estimation can improve the detection performance, but increase the technical difficulty and require a long detection time. In this paper, an improved Keystone transform method is studied. By calculating the variance of the peak position of all echo pulses with different fuzzy coefficients, the fuzzy coefficients with minimum variance are recorded, and the fuzzy coefficients are used. Combined with the transformation method realized by SINC function interpolation. This method is not limited by the time of target echo accumulation and does not need to estimate the target velocity in advance. It can simultaneously solve the Doppler ambiguity and compensate the range walk. The simulation results show that, compared with the coherent accumulation method after matched filtering, the minimum variance method and the Keystone transform method can effectively compensate the range walk and remove the Doppler ambiguity. The signal-to-noise ratio (SNR) of echo pulse accumulation of high speed moving target is improved effectively, and the detection performance of radar is improved.
【作者单位】：南京大学电子科学与工程学院;
【基金】：江苏省产学研联合创新资金——前瞻性联合研究项目(BY2012187)
【分类号】：TN957.51

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