多雷达/声呐场景下的去相关无偏量测转换模型

Decorrelated unbiased measurement conversion model for situation of multiple radars or sonars

多雷达/声呐跟踪场景中,笛卡尔坐标系由于测量转换过程中依赖相同的估计状态,不同雷达/声呐量测转换的误差常是相关的。文中充分考虑这一相关性,给出了两维及三维笛卡尔坐标系下的去相关无偏量测转换模型,及计算互相关性的解析形式,并采用相对的估计性能评估准则来验证所提算法的性能。仿真示例表明,考虑互相关后滤波性能明显优于经典无偏量测转换方法。

When tracking with multiple radars or sonars in Cartesian coordinates,the errors of converted measurements are correlated across radar or sonar stations due to their dependency on the same estimation state.In this paper,this cross⁃correlation is fully considered,a closed form of the cross⁃covariance across radars or sonars is presented for both 2D and 3D Cartesian coordinates,and the analytical form of cross⁃correlation is calculated.Two relative estimation performance evaluation metrics are then adopted to illustrate the performance of the algorithm.The simulation results show that the filtering performance of this method considering cross⁃correlation is obviously superior to the original unbiased conversion in most cases.