火控雷达技术
火控雷達技術
화공뢰체기술
Fire Control Radar Technology
2015年
3期
37-40,50
,共5页
张燕%柳超%李云鹏
張燕%柳超%李雲鵬
장연%류초%리운붕
Singer 模型%自适应渐消%机动目标%跟踪
Singer 模型%自適應漸消%機動目標%跟蹤
Singer 모형%자괄응점소%궤동목표%근종
Singer model%adaptive fading kalman filter%maneuvering target%track
Singer 模型使用标准卡尔曼滤波器对机动目标进行跟踪，当系统模型不准确或噪声统计特性不确定时，容易引起滤波发散或跟踪精度下降等问题。针对这种情况，本文提出了一种采用自适应渐消卡尔曼滤波的 Singer 模型算法(AKF Singer)，通过引入渐消因子来抑制滤波器的记忆长度，自适应的调整新息权重和滤波器增益，从而避免发散。仿真结果表明，本文所提算法能够有效抑制滤波发散，相比于传统 Singer 模型，具有更好的跟踪稳定性和更高的跟踪精度。
Singer 模型使用標準卡爾曼濾波器對機動目標進行跟蹤，噹繫統模型不準確或譟聲統計特性不確定時，容易引起濾波髮散或跟蹤精度下降等問題。針對這種情況，本文提齣瞭一種採用自適應漸消卡爾曼濾波的 Singer 模型算法(AKF Singer)，通過引入漸消因子來抑製濾波器的記憶長度，自適應的調整新息權重和濾波器增益，從而避免髮散。倣真結果錶明，本文所提算法能夠有效抑製濾波髮散，相比于傳統 Singer 模型，具有更好的跟蹤穩定性和更高的跟蹤精度。
Singer 모형사용표준잡이만려파기대궤동목표진행근종，당계통모형불준학혹조성통계특성불학정시，용역인기려파발산혹근종정도하강등문제。침대저충정황，본문제출료일충채용자괄응점소잡이만려파적 Singer 모형산법(AKF Singer)，통과인입점소인자래억제려파기적기억장도，자괄응적조정신식권중화려파기증익，종이피면발산。방진결과표명，본문소제산법능구유효억제려파발산，상비우전통 Singer 모형，구유경호적근종은정성화경고적근종정도。
Considering the divergence and poor precision due to inaccurate modeling of the system or noise, an a-daptive fading kalman filter based on singer model (AKF - Singer)is proposed. It adopts a fading factor to restrain the memory length of kalman filter. Simulation shows that the proposed algorithm can effectively restrain the diver-gence of filtering, and is more steady and more precise compared to traditional singer model.
