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This letter presents a mean-square error lower bound for state estimation of nonlinear stochastic systems under given differentiable state constraints. Its recursive formulation permits incorporation of random process and measurement… Click to show full abstract
This letter presents a mean-square error lower bound for state estimation of nonlinear stochastic systems under given differentiable state constraints. Its recursive formulation permits incorporation of random process and measurement errors and is shown to be a generalization of the known lower bound for unconstrained problems. The bound is evaluated for the example of locating a ground vehicle from noisy measurements of its horizontal position and velocity incorporating a roadmap.
Keywords:
cram rao;
bound state;
bound;
lower bound;
rao lower
Journal Title: IEEE Signal Processing Letters
Year Published: 2017
Link to full text (if available)
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Journal Title: IEEE Signal Processing Letters
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!