We consider the problem of collaborative bearing estimation using a method with historic roots in set theoretic estimation techniques. We refer to this method as the Convex Combination Ellipsoid (CCE) method and show that it provides a less conservative covariance estimate than the well known Covariance Intersection (CI) method. The CCE method does not introduce additional uncertainty that was not already present in the prior estimates. Using our proposed approach for collaborative bearing estimation, the nonlinearity of the bearing measurement is captured as an uncertainty ellipsoid thereby avoiding the need for linearization or approximation via sampling procedures. Simulations are undertaken to evaluate the relative performance of the collaborative bearing estimation solution using the proposed (CCE) and typical (CI) methods.

翻译：本文考虑利用一种具有集合估计技术历史根源的方法来解决协作方位估计问题。我们将此方法称为凸组合椭球（CCE）方法，并证明它相比著名的协方差交集（CI）方法能提供更不保守的协方差估计。CCE方法不会引入先验估计中原本不存在的额外不确定性。采用我们提出的协作方位估计方法，方位测量的非线性被表示为不确定性椭球，从而避免了通过采样过程进行线性化或近似的需要。我们进行了仿真实验，以评估使用所提出的CCE方法和典型CI方法的协作方位估计解决方案的相对性能。