Particle filter based distributed detection under unknown non Gaussian noise

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.