摘要
针对混合运动模式下目标数量及目标运动速度范围等多项先验信息缺乏状况下的复杂航迹起始问题,提出一种基于最大置信度的多目标检测算法。该算法借鉴动态规划技术中的能量积累思想,并充分利用了传感器信号强度信息。在粗起始阶段利用扩展搜索算法生成候选航迹,并利用模型粗匹配的方法将候选航迹大致分为直线运动及曲线运动两种类型。在航迹确认阶段,采用基于信号强度信息的概率多假设跟踪算法,通过计算最优状态估计值获得量测点属于某一目标的最大置信度,并依据最大置信度确认目标量测。仿真实验结果表明,该方法实时性强,不仅能对多目标航迹准确起始,也可以有效避免概率多假设跟踪算法由于初值质量差而导致的错误跟踪现象。
A multiple targets detection algorithm based on maximum confidence is proposed to solve complicated multiple targets track initiation problem in the mode of hybrid motion with insufficient prior information,such as target number and target velocity interval.This algorithm effectively utilizes the signal intensity information of sensor depending on the principal of energy accumulation of dynamic programming.During the period of rough initiation,an extended search approach is utilized to generate candidate tracks,and these tracks are divided into rectilinear motion mode and curvilinear motion mode respectively according to model matching.Furthermore,the probabilistic multi-hypothesis tracking algorithm based on signal intensity information is utilized to obtain the maximum confidence through calculating optimal state estimation,and the target measurement is confirmed finally based on the maximum confidence in the period of track confirming.Simulation results show that the proposed algorithm has the capabilities of high real-time and accurate initiation for multi-target tracks.Moreover, it avoids the error tracking problem due to poor initial value in probabilistic multi-hypothesis tracking algorithm.
出处
《信号处理》
CSCD
北大核心
2012年第1期39-46,共8页
Journal of Signal Processing
基金
国家自然科学基金(61175027)的资助
关键词
最大置信度
扩展搜索
概率多假设跟踪
多目标
maximum confidence
extended search
probabilistic multi-hypothesis tracking
multiple targets
