量测转换卡尔曼滤波在塔康导航中的应用

塔康导航系统是一种无线电测角测距系统，结合高程数据可以确定目标的三维位置。由于塔康导航的量测误差较大，导致其对目标位置的估计精度不高。为解决此问题，用基于量测转换的滤波跟踪技术实现非线性量测下的状态估计。针对塔康导航系统量测值的特点，首先在斜距值与高度所在平面内推导出量测转换的误差统计特性，并将其推广到三维空间，进而推导出塔康导航系统中的量测转换模型。基于所推导模型的卡尔曼滤波器用于塔康导航系统中的目标跟踪，取得良好的效果。与经典滤波算法的性能对比表明，由于严格基于量测值推导量测转换误差的统计特性，算法在滤波误差、置信度和计算量上优于其它算法，可在不同量测噪声水平下稳健滤波，有较好的全面性和鲁棒性。 

Application of Converted Measurements Kalman Filter for TACAN Navigation

TACAN is a wireless navigation system which can provide both range and azimuth measurement. Combining the measurements above with elevation measurement, a target’s three-dimensional position can be easily fixed. Despite the advantages above, the relatively large measurement error of TACAN system results in an inaccurate estimation of position. In an attempt to solve this problem, a filter scheme based on converted measurement modal is manipulated to realize accurate state estimation with nonlinear measurements. In according with the feature of TACAN measurements, the statistic error characteristic of converted measurement is firstly derived in the plane consists of range and elevation measurements. Based on the derivation above, the three-dimensional statistic error characteristic is deduced, which presents the final form of converted measurement modal for TACAN navigation system. A Kalman filter using proposed converted measurement modal is manipulated to estimate target state in TACAN navigation system and satisfied tracking performance is achieved. Comparative study with some state-of-the-art algorithms verifies the superiority of proposed algorithm because both the mean and covariance are conditioned strictly on measurement. The algorithm proposed in this paper is more accurate, credible and computational efficient over others for different tracking scenarios, which certifies its comprehensiveness and robustness.