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A processing strategy for lidar signals based on established concepts of Kalman filtering is described. Features of relevance to lidar include use of stochastic and non-stationary system models, the need for non-linear and multi-dimensional models in many applications, and the ability to 'self-tune' the filter in response to data input in the absence of a vriori information.
Barry J. Rye
"Kalman Filtering In Lidar", Proc. SPIE 1181, 5th Conf on Coherent Laser Radar: Technology and Applications, (12 December 1989); https://doi.org/10.1117/12.963771
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Barry J. Rye, "Kalman Filtering In Lidar," Proc. SPIE 1181, 5th Conf on Coherent Laser Radar: Technology and Applications, (12 December 1989); https://doi.org/10.1117/12.963771