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The presented ranging update gives a robustness to outliers in the measurement data.
By comparing the blue solid and the red dashed-dotted lines, it is seen that when the position and ranging error covariances are of the same size, the suggested ranging update behaves like the Kalman update up to around three standard deviations, where it gracefully starts to neglect the range measurement.
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With slight modifications, the ranging updates can be used to incorporate information from many other information sources.
A solution to the latter problem has been presented in the marginalization and sample-based spatial separation constraint and ranging updates.
This has the effect that multiple ranging updates will not make the position error covariance collapse, which captures the fact that due to correlated errors, during standstill, multiple range measurements will contain a diminishing amount of information; and during motion, the range measurements should only 'herd' the dead reckoning.
Figure 7 Illustration of the suggested range update in two dimensions.
The radio has a wide range of parameter settings that provide flexibility for making tradeoffs such as transmission delay versus reliability and range update rate versus range accuracy.
The fundamental tradeoff between range accuracy and range update delay in a mobile environment is discussed and simulation results are presented.
The sampling-based range update with this likelihood function and u (i) from a square sampling lattice is illustrated in Figure7.
In addition, by comparing the blue dashed and the red dotted lines, it is seen that for smaller position error covariances, in contrast to the Kalman update, the suggested range update neglects ranging measurements with small errors (flat spot in the middle of the influence function).
And within each step, only vertices with range updates would send out messages to selected neighbors.
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