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Quadratic Frequency Modulation Signals Parameter Estimation Based on Product High Order Ambiguity Function-Modified Integrated Cubic Phase Function

机译:基于乘积高阶模糊函数-修正积分三次相函数的二次调频信号参数估计

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In inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, the multi-component quadratic frequency modulation (QFM) signals are more suitable model for azimuth echo signals. The quadratic chirp rate (QCR) and chirp rate (CR) cause the ISAR imaging defocus. Thus, it is important to estimate QCR and CR of multi-component QFM signals in ISAR imaging system. The conventional QFM signal parameter estimation algorithms suffer from the cross-term problem. To solve this problem, this paper proposes the product high order ambiguity function-modified integrated cubic phase function (PHAF-MICPF). The PHAF-MICPF employs phase differentiation operation with multi-scale factors and modified coherently integrated cubic phase function (MICPF) to transform the multi-component QFM signals into the time-quadratic chirp rate (T-QCR) domains. The cross-term suppression ability of the PHAF-MICPF is improved by multiplying different T-QCR domains that are related to different scale factors. Besides, the multiplication operation can improve the anti-noise performance and solve the identifiability problem. Compared with high order ambiguity function-integrated cubic phase function (HAF-ICPF), the simulation results verify that the PHAF-MICPF acquires better cross-term suppression ability, better anti-noise performance and solves the identifiability problem.
机译:在用于复杂运动目标的逆合成孔径雷达(ISAR)成像系统中,例如在海浪中起伏的船只和高机动飞机中,多分量二次调频(QFM)信号更适合用于方位回波信号。二次线性调频率(QCR)和线性调频率(CR)导致ISAR成像散焦。因此,重要的是在ISAR成像系统中估计多分量QFM信号的QCR和CR。常规的QFM信号参数估计算法存在交叉项问题。为了解决这个问题,本文提出了乘积高阶模糊函数修正的积分立方相位函数(PHAF-MICPF)。 PHAF-MICPF采用具有多尺度因子的相位微分运算和改进的相干积分立方相位函数(MICPF),将多分量QFM信号转换为时间二次线性调频率(T-QCR)域。通过将与不同比例因子相关的不同T-QCR域相乘,可以提高PHAF-MICPF的交叉项抑制能力。此外,乘法运算可以提高抗噪性能并解决可识别性问题。仿真结果表明,与高阶模糊函数积分三次相函数(HAF-ICPF)相比,PHAF-MICPF具有更好的跨项抑制能力,更好的抗噪性能,解决了可识别性问题。

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