改进的主/被动传感器协同探测跟踪方法研究

An Improved Synergistic Detection and Tracking Algorithm for Active / Passive Sensors

针对主动传感器辅助的被动传感器跟踪系统,为了提升系统的跟踪精度,改进主动传感器工作控制的实时性和精确性,结合地空导弹武器跟踪系统中的"粗跟"与"精跟"模式,提出了一种改进的主/被动传感器协同探测跟踪方法。在主动传感器开机时,利用曲线拟合推理出目标的运动轨迹;关机后,利用拟合的"估计量测"值和滤波预测值产生新息残差,并将其作为评价因子,结合信息熵理论设计"粗跟"和"精跟"模式下的航迹质量评价准则。实现了主/被动传感器间的实时切换以及"粗跟"和"精跟"模式间的自适应切换,克服了被动传感器距离量测的不可观测性。采用Monte Carlo仿真,同跟踪门法作比较,结果验证了改进方法的合理性和优越性。

To improve the tracking precision of the active-sensor assisted passive sensor tracking system, and the real-time performance and accuracy of control for the active sensor, an improved synergistic detection and tracking algorithm was proposed based on the modes of ＂rough tracking＂ and ＂precise tracking＂ in ground-to-air missile defense tracking system. When active sensor is working, the target motion state in the future time is estimated by the method of curve fitting. When it is shut off, the result of ＂ estimated measurement＂ can be used with the filtering predicted value to produce the new rate residual, which can be taken as the evaluation factor. Moreover, the information entropy theory is introduced to design the evaluation rule of the track quality in the modes of the ＂rough tracking＂ and ＂precise tracking＂. The method not only achieved real-time switchover between the active/passive sensors and the self-adaptive switchover between the two modes, but also overcame the non-observability for passive sensor distance. The Monte Carlo simulation shows that the improved method is more rational than and superior to the method of ＂tracking door＂.