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Non-searching coherent integration method for maneuvering target detection by using non-uniformly resampling technique

机译:使用非均匀重采样技术进行目标检测的非搜索相干积分方法

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摘要

It is well known that, long-time integration improves the detection performance of radar system, which is however limited by the range migration (RM) and Doppler frequency migration (DFM) caused by target's high velocity and acceleration. To solve this problem, this paper proposed a three-dimensional modified cross correlation function (3DMCCF) method for maneuvering radar targets. In this method, we define a new cross correlation function under a designing frame based on non-uniformly resampling technique. By using the new function, the target's RM and DFM can be eliminated at the same time. The resulting signal is a three-dimensional complex sinusoid. Finally the integration is achieved efficiently by performing inverse fast Fourier transforms (IFFTs) and fast Fourier transforms (FFTs). The proposed method can work in low signal to noise ratio (SNR) environment and is applicable for multi-target scene. Compared with the generalized Radon Fourier transform (GRFT) and the Radon Lv's distribution (RLVD) algorithms, the proposed method is free from searching approach and has lower computational complexity. The effectiveness of the proposed method is demonstrated by simulations and real-data processing. (C) 2019 Elsevier Inc. All rights reserved.
机译:众所周知,长时间集成改善了雷达系统的检测性能,然而由目标高速和加速度引起的范围迁移(RM)和多普勒频率迁移(DFM)的限制。为了解决这个问题,本文提出了一种用于操纵雷达靶的三维改进的互相关函数(3DMCCF)方法。在该方法中,我们在基于非均匀重采样技术的设计帧下定义了一种新的互相关功能。通过使用新功能,可以同时消除目标的RM和DFM。得到的信号是三维复杂正弦曲线。最后,通过执行逆快速傅里叶变换(IFFTS)和快速傅里叶变换(FFT),有效地实现了集成。所提出的方法可以在低信噪比(SNR)环境中工作,并且适用于多目标场景。与广义氡傅里叶变换(GRFT)和Radon LV的分布(RLVD)算法相比,所提出的方法没有搜索方法并且具有较低的计算复杂性。通过模拟和实数据处理证明了该方法的有效性。 (c)2019 Elsevier Inc.保留所有权利。

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