智能子弹对声目标CACEMD-VDAKF跟踪算法研究  

Study on CACEMD-VDAKF tracking algorithm of acoustic target for brainpower submunition

作　　者：刘亚雷[1] 顾晓辉[1] 

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《仪器仪表学报》2011年第4期748-755,共8页Chinese Journal of Scientific Instrument

摘　　要：为了研究智能反坦克子弹药(BAT)对声目标机动检测与跟踪的问题,推导了适合智能子弹药系统的MUSIC估计算法,并计算了声信号的空间方位谱及功率谱,提出了一种针对信号几何窗口的变量——当前平均改变能量(current average change energy,CACE),利用该变量推导了基于当前平均改变能量的机动检测算法,将此算法与机动目标跟踪变维自适应Kalm an滤波模型相结合,得到了基于当前平均改变能量的机动检测与变维自适应Kalm an滤波算法(CACEMD-VDAKF);通过半实物仿真实验,计算了目标在不同运动状态下的空间功率谱和方位谱,证实了该算法对声信号处理的可行性,MATLAB仿真结果验证了CACEMD-VDAKF算法对二维声目标跟踪的有效性及稳定性。In order to study the sound-source bearing maneuver detection and tracking problem of Brainpower Antitank Submunition（BAT）,a MUSIC estimate algorithm suitable for BAT system is deduced,with which the spatial orientation spectrum and power spectrum of the acoustic signal are calculated.Current average change energy（CACE） is proposed for the signal geometric window;and a maneuvering detection algorithm based on CACE is deduced.This algorithm is combined with maneuvering target variable dimension adaptive Kalman filtering model,then the CACE-based maneuvering detection and variable dimension adaptive Kalman filtering algorithm（CACEMD-VDAKF） is obtained.The spatial orientation spectrum and power spectrum are calculated with loop simulation,which confirms the feasibility of the intelligent signal processing.Finally,MATLAB simulation results confirm the effectiveness and stability of the CACEMD-VDAKF algorithm for two-dimensional target tracking.

关 键 词：机动检测 正交多尺度小波分析理论 MUSIC估计算法 当前平均改变能量 智能反坦克子弹药 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]