Impact of motion and channel parameters on the estimation of transmitter position in robotic networks

In this paper we study the impact of the motion of a mobile robot as well as the underlying parameters of the channel on the estimation of the transmitter position in a networked robotic operation. We consider the case that the robot gathers a number of received signal strength (RSS) measurements from a fixed transmitter along its trajectory and use them to estimate the position of the transmitter. We first mathematically characterize two metrics for the estimation performance of the transmitter position: 1) the Cramer-Rao lower bound (CRLB) and 2) the error covariance matrix of a least square (LS) estimator. We then mathematically analyze the impact of the positions of the channel measurements as well as the underlying channel parameters, such as shadowing power, correlation distance, multipath power, and path loss slope, on each metric individually. Motivated by our analysis, we then utilize a motion planning strategy to improve the estimation quality of the transmitter position. Our simulation results confirm our theoretical analysis.