1 Multi-Sensor Optimal Data Fusion for INS/GPS/SAR Integrated Navigation System Shesheng Gao a , Yongmin Zhong b , Xueyuan Zhang a , Bijan Shirinzadeh c a School of Automation, Northwestern Polytechnical University, Xi’an 710072, China b Department of Mechanical Engineering, Curtin University of Technology, Australia c Department of Mechanical and Aerospace Engineering, Monash University, Australia Abstract INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is formulated to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to achieve the global optimal state estimation under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems developed by using the proposed methodology have a better performance than INS/GPS integrated systems. Key words: integrated navigation system, data fusion, decentralized fusion and global optimal fusion.