Optimal sensor placement in range based localization for linear arrays

This paper investigates the linear separation requirements for range sensors in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyze the sensor-target geometry in terms of the Cramer-Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear spacial distribution.