Application of federated particle filter fusion and fault tolerance in integrated navigation system

In multi-sensor integrated navigation systems with non-linear subsystems and non-Gaussian noise, errors, even failures, exist in global state estimation obtained by federated Kalman filter. χ
²
residual test and χ
²
state test are invalid in nonGaussian models. Since likelihood function can be estimated by particle filter (PF), by combining PF with federated Kalman filter, this paper proposes a likelihood detection method based on federated PF technology. The method is applied in JIDS/SINS/GPS integrated navigation system (INS). Simulation in non-Gaussian noise environment shows that the method is effective in fault detection, isolation and recovery. It improves positioning precision and reliability in INS.