一种用于杂波中机动目标跟踪的自适应关联波门设计方法

A Method to Design Adaptive Correlating Gate for Maneuvering Target Tracking in Clutter

针对传统关联波门设计方法在应用于机动目标跟踪时容易引起失跟现象的问题，提出一种新的自适应关联波门设计方法。该方法在综合交互多模型概率数据关联算法的基础上进行关联波门设计，当波门内不存在有效量测时，首先以最大机动水平对应的模型误差协方差对关联波门进行适当扩大，确保量测点迹进入波门。然后假定目标的机动能力已知，在目标运动状态的预测范围内利用观测信息寻找最小均方误差意义下的最优波门中心。该方法可以从根本上改善关联概率，从而降低失跟率，提高目标跟踪精度。仿真结果表明，与传统关联波门设计方法相比，该方法的失跟率降低了30％～40％，而且目标机动时的跟踪精度提高了20％～30％。实测数据同样验证了该方法的有效性。

A novel method to design adaptive correlating gate is proposed to solve the problem that the traditional correlating gate design method is easy to cause tracking loss when it is applied in the case of tracking a maneuvering target. The correlating gate is designed based on the comprehensive IMM-PDA algorithm. If there are no validated measurements in the correlating gate, the covariance of model errors with maximal maneuvering level is used to appropriatlely enlarge the gate to guarantee validated measurements existing in the gate. Then it is assumed that the target maneuvering ability is known, and the information of measurements is used to find the optimal gate centre among the predictive range of target motion in the sense of minimizing the mean square error. Since the method fundamentally improves the association probability, the tracking loss probability is decreased and the tracking accuracy is improved. Simulation results and comparisons with the traditional correlating gate design methods show that the tracking loss probability of the proposed method is reduced by 30%-40% and the maneuvering tracking accuracy is improved by 20%-30%. The effectiveness of the proposed method is also verified by the raw radar data.