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Parameter Estimation Based on Fractional Power Spectrum Density in Bistatic MIMO Radar System Under Impulsive Noise Environment

机译:脉冲噪声环境下基于分数功率谱密度的双基地MIMO雷达系统参数估计

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This paper takes an Alpha-stable distribution as the noise model to solve the parameter estimation problem of bistatic multiple-input multiple-output (MIMO) radar system in the impulsive noise environment. For a moving target, its echo often contains a time-varying Doppler frequency. Furthermore, the echo signal may be corrupted by a non-Gaussian noise. It causes the conventional algorithms and signal models degenerating severely in this case. Thus, this paper proposes a new signal model and a novel method for parameter estimation in bistatic MIMO radar system in the impulsive noise environment. It combines the fractional lower-order statistics (FLOS) and fractional power spectrum density (FPSD), for suppressing the impulse noise and estimating parameters of the target in fractional Fourier transform domain. Firstly, a new signal array model is constructed based on the -stable distribution model. Secondly, Doppler parameters are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of direction-of-departure and direction-of-arrival (DOA), including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method.
机译:本文以阿尔法稳定分布作为噪声模型,解决了脉冲噪声环境下双基地多输入多输出(MIMO)雷达系统的参数估计问题。对于运动目标,其回声通常包含随时间变化的多普勒频率。此外,回波信号可能会因非高斯噪声而损坏。在这种情况下,这会导致常规算法和信号模型严重退化。因此,本文提出了一种在脉冲噪声环境下双基地MIMO雷达系统中信号模型和参数估计的新方法。它结合了分数低阶统计量(FLOS)和分数功率谱密度(FPSD),用于抑制分数阶傅里叶变换域中的脉冲噪声和估计目标参数。首先,在稳定分布模型的基础上构造了一个新的信号阵列模型。其次,通过对FLOS-FPSD进行峰值搜索来联合估计多普勒参数。此外,提出了两种改进的航向和到达方向估计算法,包括基于MUSIC算法的分数功率谱密度(FLOS-FPSD-MUSIC)和分数低阶模糊度。基于ESPRIT算法(FLOS-FPSD-ESPRIT)的功能。仿真结果表明了该方法的有效性。

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