Generalized Fractional Matched Filtering and its Applications

Peeyush Sahay, Ameya Anjarlekar, S. Jain, P. Radhakrishna, V. Gadre
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引用次数: 4

Abstract

Time domain matched filtering is a classic method used in radar and sonar applications to maximize signal to noise ratio (SNR) gain, estimate time delay, and improve range resolution. Fractional Fourier transform, and fractional Fourier domain matched filtering are used extensively to overcome the drawbacks of time domain matched filtering and are shown to have improved performance for a linear chirp. This paper presents a generalized fractional matched filtering (GFMF) for estimating higher order chirp parameters with known time delay. It is shown to provide SNR gain equivalent to time domain matched filtering. As an application of GFMF, a novel method to minimize SNR gain degradation due to the range-Doppler coupling effect of quadratic chirps is presented. For a higher order chirp with unknown time delay, another method using generalized fractional envelope correlator (GFEC) is proposed, which performs joint estimation of time delay and higher order chirp parameters using a double quadratic chirp.
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广义分数匹配滤波及其应用
时域匹配滤波是雷达和声纳应用中用于最大化信噪比(SNR)增益、估计时延和提高距离分辨率的经典方法。分数阶傅里叶变换和分数阶傅里叶域匹配滤波被广泛用于克服时域匹配滤波的缺点,并被证明对线性啁啾具有改善的性能。提出了一种用于估计已知时滞的高阶啁啾参数的广义分数匹配滤波(GFMF)方法。它的信噪比增益相当于时域匹配滤波。作为GFMF的一种应用,提出了一种新的方法来减小二次啁啾的距离-多普勒耦合效应造成的信噪比增益下降。针对具有未知时滞的高阶啁啾,提出了一种基于广义分数包络相关器(GFEC)的方法,该方法利用双二次啁啾对时间延迟和高阶啁啾参数进行联合估计。
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