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本文介绍了低数据率边跟踪边扫描(TWS)工作的连续自适应两维卡尔曼跟踪滤波器,该滤波器可提高跟踪机动目标的能力。跟踪滤波器检测每个坐标上的航迹残差(残差是跟踪质量的度量值),并将其归一化为单位方差,然后在单极(siogle-pole).滤波器内滤波。当单极滤波器输出幅度Z超过门限Z_1时,Z以连续的方式改变卡尔曼滤波模型中的机动噪声谱密度q。其作用是增加了滤波器的增益并抑制了由于机动目标引起的跟踪滤波器所产生的偏差。利用适当尺寸的目标门限可以提高维持跟踪的概率。如果在机动飞行过程中没有高置信度,q随Z变化的工作特性可确保跟踪器的增益不变。
This article describes the continuous adaptive two-dimensional Kalman tracking filter for low-data-rate edge-tracking (TWS) operation that enhances the ability to track maneuvering targets. The tracking filter detects the track residual at each coordinate (the residual is a measure of the tracking quality) and normalizes it to the unit variance, which is then filtered in a siogle-pole filter. When the monopole filter output amplitude Z exceeds the threshold Z_1, Z changes the spectral spectral density q of the motor noise in the Kalman filter model in a continuous manner. Its role is to increase the gain of the filter and suppress the deviation caused by the tracking filter due to the maneuvering target. Using a properly sized target threshold can increase the probability of maintaining a track. If there is no high confidence in the maneuver flight, q changes with Z operating characteristics to ensure that the tracker gain unchanged.