天波超视距雷达扩展综合概率数据关联算法

Extended Integrated Probabilistic Data Association Algorithm for Target Tracking of Sky-wave Over-the-horizon Radar

考虑到天波超视距雷达径向速率量测与径向距离量测之间的关系以及径向速率量测精度较高的特点,提出了一种天波超视距雷达扩展IPDA算法。该算法利用当前时刻径向速率、径向距离的预测值和相应的量测构造出运动一致性因子,并推导了一致性因子的概率密度函数。在此基础上,利用一致性因子和马氏距离计算回波与目标的互属概率,从而减小异常点的影响、提高估计的精度。天波超视距雷达目标跟踪仿真结果表明:扩展IPDA算法在起始快速性、航迹起始概率、跟踪精度和稳定跟踪率等方面优于IPDA算法,同时其计算量只略大于IPDA算法的计算量。

Taking into account the relation between the measurement of range rate and range, along with the high precision characteristic of range rate measurement, an extended IPDA algorithm for skywave over-the-horizon radar is presented in this paper. This algorithm constructs movement consistency factor using current time range rate, range prediction value and corresponding measurement, and deduces the density function of consistency factor. Then, the constructed consistency factor and Mahalanobis Distance are used to compute the probability that the measurement originated from the target, which could relieve the effect of outliers and improve the estimation accuracy. Simulation results of sky-wave over-the- horizon radar show that the extended IPDA algorithm is superior to the IPDA algorithm in respect of fast initiation, probability of track initiation, tracking precision and steady-tracking rate but only with slightly larger computation.