POSITION ESTIMATION USING MULTIPLICATIVE MEASUREMENT MODEL
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Three novel correction measurement models are presented for vision-based proximity navigation by multiplicative measurement model. They are derived from the statistic characteristics of the measurements. The full correction model is to move original measurement farther away from estimate within the plane defined by measurement and estimate. Such movement decreases the component of noise on the plane of estimate and true direction. Multiple correction and single correction are directly utilizing the form and expectation of multiplicative measurement model. Numerical tests demonstrate that the first model is very significant, the second one is effective under certain circumstances, and the last one usually can be ignored.