Abstract: A novel Kalman filter-based scheme utilizing the output of RF transponders is proposed to estimate the navigational states of a Mars microrover. The novelty of the scheme stems from (a) the use of pseudo-measurements that are a nonlinear function of range measurements such that the measurement model is linear and the resulting Kalman filter globally convergent, (b) the measurements of the sums and the differences in the ranges so as to reduce the sensitivity to the measurement noise and (c) optimization of RF element locations to ensure that the state estimation error is minimized resulting in the estimation accuracy being linear in the true states. Both bias and random errors are considered to account for the error sources such as sensor bias, faults, multi-path, and sensor noise.!10
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