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Particle filter based distributed detection under unknown non Gaussian noise

机译:未知非高斯噪声下基于粒子滤波的分布式检测

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In this study, a new robust distributed detection scheme that operates under non Guassian noise with unknown parameters is developed. Particle filters are utilized for the estimation of unkown noise parameters and the threshold values for the distibuted detection is optimized using particle swarm optimization, leading to a scheme based on particle filtering methods. The probability of error values obtained by using the porposed method are compared with theoretical values and promising results are observed.
机译:在这项研究中,开发了一种新的鲁棒的分布式检测方案,该方案可在参数未知的非高斯噪声下工作。利用粒子滤波器估计未知的噪声参数,并使用粒子群优化技术优化分布式检测的阈值,从而得出基于粒子滤波方法的方案。将使用多孔方法获得的误差值的概率与理论值进行比较,并观察到了有希望的结果。

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