计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
22期
55-58,62
,共5页
周彦%欧阳宁烽%盛权%胡岚
週彥%歐暘寧烽%盛權%鬍嵐
주언%구양저봉%성권%호람
目标跟踪%扩展H¥滤波%扩展卡尔曼滤波%交互式多模型%LOS/NLOS混合环境%TOA-RSSI
目標跟蹤%擴展H¥濾波%擴展卡爾曼濾波%交互式多模型%LOS/NLOS混閤環境%TOA-RSSI
목표근종%확전H¥려파%확전잡이만려파%교호식다모형%LOS/NLOS혼합배경%TOA-RSSI
target tracking%extended H-infinity filter%extended Kalman filter%interacting multiple model%LOS/NLOS hybrid environment%TOA-RSSI
针对视距(Line-of-sight,LOS)和非视距(None-line-of-sight,NLOS)混合环境中的运动目标跟踪问题,提出一种基于TOA(到达时间)与RSSI(接收信号强度)测量融合的交互式多模型(Interacting Multiple Model,IMM)鲁棒跟踪算法。目标与基站之间的LOS、NLOS传输分别用扩展卡尔曼滤波(EKF)和扩展H¥滤波(EHF)进行匹配,并采用马尔可夫过程对模型间的转换进行描述。Monte Carlo仿真结果表明,与单纯TOA测量跟踪相比,该算法具有较高的定位精度和较好的跟踪稳定性,且计算复杂度相当,具有较好的可实现性。
針對視距(Line-of-sight,LOS)和非視距(None-line-of-sight,NLOS)混閤環境中的運動目標跟蹤問題,提齣一種基于TOA(到達時間)與RSSI(接收信號彊度)測量融閤的交互式多模型(Interacting Multiple Model,IMM)魯棒跟蹤算法。目標與基站之間的LOS、NLOS傳輸分彆用擴展卡爾曼濾波(EKF)和擴展H¥濾波(EHF)進行匹配,併採用馬爾可伕過程對模型間的轉換進行描述。Monte Carlo倣真結果錶明,與單純TOA測量跟蹤相比,該算法具有較高的定位精度和較好的跟蹤穩定性,且計算複雜度相噹,具有較好的可實現性。
침대시거(Line-of-sight,LOS)화비시거(None-line-of-sight,NLOS)혼합배경중적운동목표근종문제,제출일충기우TOA(도체시간)여RSSI(접수신호강도)측량융합적교호식다모형(Interacting Multiple Model,IMM)로봉근종산법。목표여기참지간적LOS、NLOS전수분별용확전잡이만려파(EKF)화확전H¥려파(EHF)진행필배,병채용마이가부과정대모형간적전환진행묘술。Monte Carlo방진결과표명,여단순TOA측량근종상비,해산법구유교고적정위정도화교호적근종은정성,차계산복잡도상당,구유교호적가실현성。
To attack the problem of target tracking in LOS/NLOS hybrid environments, a robust Interactive Multiple model(IMM) approach based on fused Time of Arrival(TOA)and Received Signal Strength Indicator(RSSI)measurements is proposed in this paper. Extended Kalman Filter(EKF)and Extended H-infinity Filter(EHF)is respectively used to describe the LOS and NLOS transmission, which is modeled by a Markov process. Monte Carlo simulation results show the practice and effectiveness of the proposed algorithm. It has higher positioning accuracy and better tracking stability with similar computing complex compared with the TOA based approach.