The random noises of multi-sensor and the environment make observations uncertain and correlative, so the performance of fusion algorithms is reduced by using observations directly. To solve this problem, a multi-laye...The random noises of multi-sensor and the environment make observations uncertain and correlative, so the performance of fusion algorithms is reduced by using observations directly. To solve this problem, a multi-layer track fusion algorithm based on supporting degree matrix is proposed. Combined with the track fusion algorithm based on filtering step by step, it uses multi-sensor observations to establish supporting degree matrix and realize multi-layer fusion. Simulation results show its estimation precision is higher than the original algorithm and is increased by 20% around. Therefore, it solves the problem of target tracking further in the distributed track fusion system.展开更多
基金Supported by the Aviation Science Funds (20090580013)the Fundamental Research Funds for the Central Universities (ZYGX2009J092)
文摘The random noises of multi-sensor and the environment make observations uncertain and correlative, so the performance of fusion algorithms is reduced by using observations directly. To solve this problem, a multi-layer track fusion algorithm based on supporting degree matrix is proposed. Combined with the track fusion algorithm based on filtering step by step, it uses multi-sensor observations to establish supporting degree matrix and realize multi-layer fusion. Simulation results show its estimation precision is higher than the original algorithm and is increased by 20% around. Therefore, it solves the problem of target tracking further in the distributed track fusion system.
