Abstract

This paper investigates the linear separation requirements for Angle-of-Arrival (AoA) sensors, in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyse 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. Here we consider a situation where one sensor is fixed and the rest are free to be positioned in a linear array.

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