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:我们考虑使用历史根源集合论估计技术的协同轴承估计问题。我们称此方法为凸组合椭球(CCE)方法,并展示它提供比众所周知的协方差相交(CI)方法更少保守的协方差估计。CCE方法不会引入之前估计中不存在的额外不确定性。使用我们提出的协同轴承估计方法,轴承测量的非线性被捕捉为不确定性椭球,从而避免了线性化或通过采样过程进行近似的需求。进行模拟以评估使用提议的(CCE)和典型的(CI)方法的协同轴承估计解的相对性能。