A data loss detection method based on new particle filter

This paper aims at the situation of the random losses of detection data that happens in engineering applications under the nonlinear circumstance, and proposes a detection method of data loss based on the particle filter (PF) based on organizational evolution particle swarm optimization (OEPSO-PF). The evolutional operations are acted on organizations directly in the algorithm. The algorithm carries out an iterative optimization for the system state value through the cooperation and competition among samples, it not only guarantees the diversity of solutions in populations, but also has a strong search capability. The simulation result shows that the proposed algorithm in this paper improves the accuracy rate of data loss detection. It has high application value due to its better tracking performance with high data lose rate under the complex condition.