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Parameter estimation of linear and quadratic chirps by employing the fractional fourier transform and a generalized time frequency transform

机译：通过采用分数傅里叶变换和广义时频变换线性和二次啁啾的参数估计

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SHISHIR B SAHAY; T MEGHASYAM; RAHUL K ROY; GAURAV POONIWALA; SASANK CHILAMKURTHY; VIKRAM GADRE;
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年度 2015
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1. Parameter estimation of linear and quadratic chirps by employing the fractional fourier transform and a generalized time frequency transform [J] . Sahay Shishir B., Meghasyam T., Roy Rahul K., Sadhana: Academy Proceedings in Engineering Science . 2015,第4期

机译：利用分数阶傅里叶变换和广义时频变换的线性和二次线性调频参数估计
2. Parameter estimation of linear and quadratic chirps by employing the fractional fourier transform and a generalized time frequency transform [J] . Shishir B Sahay, T Meghasyam, Rahul K Roy, Sadhana . 2015,第4期

机译：利用分数阶傅里叶变换和广义时频变换的线性和二次线性调频参数估计
3. Fractional Fourier transform based underwater multi-targets direction-of-arrival estimation using wideband linear chirps [J] . Yin Jing-wei, Guo Kun, Han Xiao, Applied Acoustics . 2020,第Deca期

机译：基于宽带线性啁啾的基于分数傅立叶变换的水下多目标的到达方向估计
4. A novel generalized time-frequency transform inspired by the Fractional Fourier Transform for higher order chirps [C] . Sahay Shishir, Pande Deepak, Wing Naval, 2012 International Conference on Signal Processing and Communications . 2012

机译：受分数阶傅里叶变换启发的新颖的广义时频变换，用于高阶chi
5. Acoustic seabed and target classification using fractional Fourier transform and time-frequency transform techniques. [D] . Barbu, Madalina. 2006

机译：使用分数阶傅里叶变换和时频变换技术进行海床声和目标分类。
6. Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform [O] . Xinqun Liu, Tao Li, Xiaolei Fan, 2019

机译：基于随机样本共识和分数阶傅里叶变换的奈奎斯特折叠接收机截获的LFM信号的奈奎斯特区指数和线性调频率估计
7. Novel Parameter Estimation Method for Chirp Signals Using Bowtie Chirplet and Discrete Fractional Fourier Transform [O] . Ahmed Mostayed, Saurav Zaman, Khan Sajib, 2015

机译：基于Bowtie Chirplet和离散分数傅里叶变换的Chirp信号参数估计新方法

Parameter estimation of linear and quadratic chirps by employing the fractional fourier transform and a generalized time frequency transform

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