Radar Multiple-Object Tracking Performance Evaluation Model Based on Multiple-Dimensional System and Combined Weight
Aiming to address issues such as the reliance on a single evaluation index for radar multi-target track-ing and the bias caused by using only one specific type of association algorithm and weight calculation,a comprehensive radar multiple-object tracking evaluation model is proposed in this paper.The model is based on macro and fine multi-dimensional index system,and incorporates both subjective and objective weight.Firstly,two types of indexes are intro-duced to analyze the target tracking results from the perspectives of overall track dimension and fine changes in point tracks.Secondly,for different data association methods,soft and hard decisions are employed to match targets with actual tracks and calculate each index value accordingly.Finally,to ensure comprehensive evaluation results,subjective weights and objective weights for indicators are determined using G1 sequence method and CRITIC method respectively.Then,these weights are fused into combined weights through least square method before being applied in an optimiza-tion model to obtain final multiple-object tracking evaluation results.The experimental findings demonstrate that this model can flexibly and comprehensively evaluate multiple-object tracking performance across various scenarios includ-ing sparse and dense environments.
macro and fine indicatorscombined weightdata associationsoft and hard decisions
万方数据
维普
