Contains many articles of influential domestic and international literaturethe in the field of information fusion in recent years,

Filename	Size	Update
information fusion\1983 (IEEE Trans)Sonar tracking of multiple targets using joint probabilistic data association.pdf
..................\2002 (IEEE Trans.Signal Processing)sequential monte carlo methods for multiple targets tracking and data fusion.pdf
..................\A new centralized sensor fusion-tracking methodology based on particle filtering for power-aware systems.pdf
..................\Bearings-Only Tracking Based on Multiple Sensor Measurements and Generalized Particle Filtering.pdf
..................\Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion.pdf
..................\Comparison of two-sensor tracking methods based on state vector fusion and measurement fusion.pdf
..................\factored particle filtering for data fusion and situation assessments in urban environments.pdf
..................\Integrated detection and tracking of multiple objects with a network of acoustic sensors.pdf
..................\Multisensor particle filter cloud fusion for multitarget tracking.pdf
..................\On improving the accuracy and reliability of GPS INS-based direct sensor georeferencing.pdf
..................\Optimal multi-sensor fusion target tracking with correlated measurement noises.pdf
..................\particle filtering for multisensor data fusion with switching observation models	applications to land vehicle positioning.pdf
..................\Practical fusion of quantized measurements via particle filtering.pdf
..................\real-time fusion of multimodal tracking data.pdf
..................\state-vector fusion\Decentralized Sensor Fusion with Distributed Particle Filters.pdf
..................\Target tracking using delayed measurements with implicit constraints.pdf
..................\信息融合系统中目标跟踪技术研究.kdh
..................\目标跟踪与多传感器信息融合若干问题研究.nh
..................\目标跟踪与多传感器信息融合若干问题研究_.caj
..................\state-vector fusion
information fusion

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