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由于实际组合导航系统很可能受到非高斯噪声的影响,而传统的故障检测方法对非高斯噪声情况讨论较少。基于粒子滤波的故障检测技术非常适合处理非线性、非高斯问题,并且有效地克服了传统方法的不足,但是普通的粒子滤波器存在粒子“退化”等问题。为此,本文提出了一种基于UPF滤波器的导航系统故障检测方法,通过在普通粒子滤波中引入UKF产生建议分布及重采样的方法,有效抑制了普通粒子滤波器粒子“退化”的问题。并针对噪声的非高斯特性,将似然检测方法与粒子滤波可以估计似然函数的特点相结合,提出了一种基于UPF的故障检测方法。通过GPS/SINS组合导航系统在噪声服从瑞利分布情况下的故障检测仿真实例,表明此方法适用于在非高斯噪声情况下的导航系统故障检测。
Since the actual integrated navigation system is likely to be affected by non-Gaussian noise, the conventional fault detection method discusses less non-Gaussian noise. Particle filter-based fault detection technology is very suitable for dealing with nonlinear and non-Gaussian problems, and effectively overcome the shortcomings of the traditional methods, but the ordinary particle filter particle “degradation ” and other issues. Therefore, this paper presents a method of fault detection in navigation system based on UPF filter. By introducing UKF to generate the proposed distribution and resampling in ordinary particle filter, the particle “degenerate ” of ordinary particle filter is effectively suppressed problem. Aiming at the non-Gaussian noise characteristics, a new method of fault detection based on UPF is proposed by combining the likelihood detection method with the particle filter to estimate the likelihood function. The simulation example of fault detection in GPS / SINS integrated navigation system under Rayleigh noise distribution shows that the proposed method is suitable for the navigation system fault detection in the case of non-Gaussian noise.