LAUSR

In this paper, we consider circular array design in the presence of a far-field or a near-field signal source. The location of the source is introduced to our optimization problem by its probability density function (PDF) as a priori information. We consider Bayesian Cramer–Rao bound as the cost function to be minimized to specify the best locations of the sensors on a circular boundary. In the far-field case, a closed form solution is derived for an arbitrary PDF of the bearing. In the near-field scenario, we divide the design problem into three categories: known source bearing, known source range, and the general case. We present some examples to exhibit the process of array design by the proposed method. Finally, we show the array optimized by the proposed method outperforms arrays with other configurations in source localization.