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17 May 2006 A system approach to real world multi-sensor data fusion
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Abstract
Theoretically, fusion of measurements is optimal, and fusion of tracks is suboptimal. However, in the real world it frequently turns out that track fusion is superior to measurement fusion. The purpose of this paper is to explain the main reasons for this and to describe a measurement fusion algorithm that is robust in the real world. The two major reasons that measurement fusion fails to perform as well as expected in the real world are: (1) limited sensor resolution, and (2) residual sensor bias errors. Designing robust multi-sensor data fusion algorithms that work well in the real world requires understanding the physics of both sensor resolution and sensor bias errors.
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Fred Daum "A system approach to real world multi-sensor data fusion", Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350S (17 May 2006); https://doi.org/10.1117/12.665856
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