Approaches to Multisensor Data Fusion in Target Tracking: A Survey

By Duncan Smith, Sameer Singh. IEEE Transactions on Knowledge and Data Engineering, 2006

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Contact-aided invariant extended Kalman filtering for robot state estimation (2019, methodology): “Filtering methods involve estimating the robot’s current state (and potentially landmarks) using the set of all measurements up to the current time [2, 41, 73].”
Multisensor data fusion: A review of the state-of-the-art (2013, methodology): “For KF-based systems, the optimal KF approach exists that allows for maintaining cross covariance information between updates [3].”
Multimodal sensory fusion for soccer robot self-localization based on long short-term memory recurrent neural network (2017, neutral): “Depending on the complex work environments and various robot sensors, there are various approaches in sensor fusion system applied for robot self-localization (Kam et al. 1997; Fox et al. 2003; Thrun 2002; Smith and Singh 2006; Aguirre et al. 2016; Chen 2012; Luo and Chang 2012).”
Opinion Mining and Information Fusion: A survey (2016, methodology): “[150] comment on several methods for target tracking through sensor data fusion.”