机载脉冲多普勒雷达在测量数据丢失下的多目标跟踪

摘要

针对于多目标在机载多普勒盲区测量数据丢失下的跟踪问题,提出了一种鲁棒无偏转换自适应门限的CPHD (Robust Unbiased Converted Measurements-Adaptive Gating-Cardinalized Probability Hypothesis Density,RUCM-AG-CPHD)算法.该算法首先对目标测量信息进行无偏转换,并将无偏转换得到的噪声协方差矩阵做解耦;然后设计增益调节矩阵提高滤波器在目标量测数据丢失下的鲁棒性;最后采用自适应门限去除不相关的量测信息,同时保证检测到新出现的目标,从而有效地降低了算法的计算复杂度.仿真结果表明该算法的有效性和可行性,可以更加准确的估计出目标在盲区内测量信息丢失下的目标个数和状态,且计算量相对于传统的CPHD算法减少了8.6％.%The algorithm of robust unbiased converted measurements and adaptive gating based on cardinalized probability hypothesis density (RUCM-AG-CPHD) is proposed for multiple targets tracking problem under the Doppler blind zone with missing measurements.Firstly,the target measurements are unbiasedly converted,and the noise covariance matrix is decoupled.Then the gain adjustment matrix is designed to improve the robustness of filter in the loss of target measurements.Finally,the adaptive gating is used to remove the irrelevant measurements,and the detection of new targets is guaranteed,so as to effectively reduce the computational complexity of the algorithm.Simulation results demonstrate the validness and feasibility of the proposed algorithm.The number and state of the targets under the loss of measurements in the blind zone can be estimated more accurately,and the calculation amount of RUCM-AG-CPHD is reduced by 8.6％ compared with traditional CPHD algorithm.