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Long-Time Coherent Integration for Maneuvering Target Detection Based on ITRT-MRFT

机译:基于ITRT-MRFT的机动目标检测长时间连贯集成

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摘要

Long-time coherent integration can effectively improve the radar detection ability of a maneuvering target. However, with the increasing of integration time, radial velocity and radial acceleration of the moving target result in linear range migration (LRM), range curvature (RC), and Doppler frequency migration (DFM) of the received signal. These may degrade detection performance seriously. To solve these problems, an efficient coherent accumulation method based on improved time reversal transform (ITRT) and modified radon Fourier transform (MRFT) is proposed in this paper. Different from conventional methods, this approach firstly eliminates the acceleration effects by ITRT. It can remove RC and DFM simultaneously via multiplying its slow-time reversed conjugate data in range-frequency and azimuth-time domains. Then by employing a new Doppler filter bank (DFB), MRFT realizes the echoes spatial temporal decoupling as well as the coherent integration in searching-velocity and Doppler-frequency domains. The major advantages of the proposed method are that RC and DFM can be rectified without parameter estimation, and computational complexity can be optimized by the new FFT-based filter bank. In addition, due to the nonlinearity of ITRT operation, the influence of cross terms of multiple targets on detection performance is also discussed. Several simulations are provided to demonstrate the effectiveness of our approach.
机译:长期连贯的集成可以有效地提高机动目标的雷达检测能力。然而,随着积分时间的增加,移动目标的径向速度和径向加速导致接收信号的线性范围迁移(LRM),范围曲率(RC)和多普勒频率迁移(DFM)。这些可能严重降低检测性能。为了解决这些问题,本文提出了一种基于改进的时间反转变换(ITRT)和改进的氡傅里叶变换(MRFT)的高效相干累积方法。与传统方法不同,这种方法首先消除了ITRT的加速效应。它可以同时通过将其慢速反转的共轭数据乘以范围频率和方位 - 时域中的慢速颠倒数据来移除RC和DFM。然后通过采用新的多普勒滤波器组(DFB),MRFT实现了回声空间时间去耦以及搜索速度和多普勒频率域中的相干积分。所提出的方法的主要优点是RC和DFM可以在没有参数估计的情况下整流,并且可以通过基于新的FFT滤波器组优化计算复杂性。另外,由于ITRT操作的非线性,还讨论了多个目标对检测性能的横向术语的影响。提供了几种模拟以证明我们方法的有效性。

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