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Radar high speed small target detection based on keystone transform and linear canonical transform

机译:基于Keystone变换和线性规范变换的雷达高速小目标检测

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摘要

High speed small target detection is a challenging problem for ground-based radar due to its maneuverability and low radar cross section (RCS). The range migration (RM) and Doppler frequency migration (DFM) will occur during the coherent integration period, which makes it difficult to improve the coherent integration ability and radar detection performance. In this study, a novel algorithm based on Keystone transform (KT) and linear canonical transform (LCT) for high speed small target detection with narrowband radar is proposed. Firstly, it employs KT to eliminate RM. Thereafter, the LCT is applied to compensate DFM and realize coherent integration for the target in the LCT domain. Two typical forms of LCT are given for easy realization and good detection performance. Finally, the constant false alarm ratio (CFAR) detector is performed to confirm a target and motion parameters are then estimated. Moreover, in order to realize fast compensation for velocity ambiguity effect, an improved method is proposed based on coarse and fine search. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can acquire a close detection performance but with relatively low computational cost. Simulation results are provided to demonstrate the validity of proposed method.
机译:由于其机动性和低雷达横截面(RCS),高速小目标检测是基于地基雷达的具有挑战性问题。在连贯的集成期间将发生范围迁移(RM)和多普勒频率迁移(DFM),这使得难以提高连贯的集成能力和雷达检测性能。在该研究中,提出了一种基于梯形变换(KT)和线性规范变换(LCT)的新型算法,用于高速小目标检测,具有窄带雷达。首先,它采用KT来消除RM。此后,应用LCT以补偿DFM并实现LCT域中目标的相干积分。给出了两种典型的LCT,用于易于实现和良好的检测性能。最后,执行常量误报例(CFAR)检测器以确认目标,然后估计运动参数。此外,为了实现对速度模糊效应的快速补偿,提出了一种基于粗略和精细搜索的改进方法。与广义氡傅里叶变换(GRFT)相比,所提出的方法可以获得密切的检测性能,但计算成本相对较低。提供了仿真结果以证明所提出的方法的有效性。

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