机动目标跟踪误差CRLB计算与分析

克拉美-罗下限(CRLB)作为参数估计所能达到的最低误差限,常被用来衡量算法估计性能的优劣程度。以转弯机动为例,研究了有源(主动)和无源(被动)两种观测条件下目标跟踪CRLB计算的一般方法,并通过矩阵理论分析了目标机动可能引起的CRLB突变的原因,为机动目标跟踪的算法性能评估提供了有效手段。最后给出了仿真算例。

CRLB Calculation and Analysis for Maneuvering Target Tracking

As a lower bound on mean square error of parameter estimate, the Cramér-Rao lower bound (CRLB) is generally used to decide to what degree a suboptimal estimate method is close to its optimal fashion. With the assumption of coordinated turn maneuver, a generic approach for target tracking CRLB calculation was investigated under the conditions of active and passive measurement, and the essential reason for possible CRLB's sudden increase caused by maneuver was also analyzed from the perspective of matrix theory, which provides an effective measurement for performance assessment of estimate methods used in maneuvering target tracking. Finally, simulation example for CRLB calculation was presented.