17 July 1998 Optimum geometry selection for sensor fusion
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Abstract
A relative sensors-to-target geometry measure-of-merit (MOM), based on the Geometric Dilution of Precision (GDOP) measure, is developed. The method of maximum likelihood estimation is introduced for the solution of the position location problem. A linearized measurement model-based error sensitivity analysis is used to derive an expression for the GDOP MOM. The GDOP MOM relates the sensor measurement errors to the target position errors as a function of sensors-to-target geometry. In order to illustrate the efficacy of GDOP MOM for fusion systems, GDOP functional relationships are computed for bearing-only measuring sensors-to-target geometries. The minimum GDOP and associated specific target-to-sensors geometries are computed and illustrated for both two and three bearing-only measuring sensors. Two and three-dimensional plots of relative error contours provide a geometric insight to sensor placement as a function of geometry induced error dilution. The results can be used to select preferred target- to-sensor(s) geometries for M sensors in this application. The GDOP MOM is general and is readily extendable to other measurement-based sensors and fusion architectures.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ivan Kadar, "Optimum geometry selection for sensor fusion", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327141; https://doi.org/10.1117/12.327141
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