基于SoKT-NuFFT的高机动弱目标检测长时间相干集成

Lang Xia;Penghui Huang;Xiang-Gen Xia;Junli Chen;Peili Xi;Xiangcheng Wan;Jiaqi Wang
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引用次数: 0

摘要

本文提出了一种用于低信噪比环境下具有恒定径向抖动的弱目标检测的相干积分方法。该方法首先利用二阶梯形变换(SoKT)对目标径向加速度引起的二次距离偏移(QRM)进行校正。其次,构造速度-加速度匹配滤波器,消除目标径向速度和加速度项的残留。最后,通过慢时间非均匀快速傅里叶变换(NuFFT)实现相干积分。与传统方法相比,该方法能够以较低的计算复杂度获得相当的累积性能。仿真和实测实验验证了该方法在低信噪比环境下的有效性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-Time Coherent Integration for High Maneuvering Weak Target Detection Based on SoKT-NuFFT
This letter proposes a coherent integration approach for weak target detection with constant radial jerk in a low signal-to-noise ratio (SNR) environment. In the proposed approach, the second-order keystone transform (SoKT) is first employed to correct the quadratic range migration (QRM) induced by the radial acceleration of a target. Next, a velocity-jerk matched filter is constructed to eliminate the residual target radial velocity and jerk terms. Finally, the coherent integration is achieved through nonuniform fast Fourier transform (NuFFT) along the slow time. Compared with the conventional methods, the proposed approach can obtain comparable accumulation performance with a lower computational complexity. The simulation and real-measurement experiments are conducted to demonstrate the effectiveness and reliability of the proposed approach in low SNR environments.
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