解放军理工大学学报(自然科学版)
解放軍理工大學學報(自然科學版)
해방군리공대학학보(자연과학판)
JOURNAL OF PLA UNIVERSITY OF SCIENCE AND TECHNOLOGY(NATURAL SCIENCE EDITION)
2015年
4期
305-309
,共5页
朱会杰%王新晴%芮挺%李艳峰%刘天帅
硃會傑%王新晴%芮挺%李豔峰%劉天帥
주회걸%왕신청%예정%리염봉%류천수
正交匹配追踪%子空间追踪%方波%滤波
正交匹配追蹤%子空間追蹤%方波%濾波
정교필배추종%자공간추종%방파%려파
orthogonal matching pursuit%subspace pursuit%square wave%de-noising
为了克服常规滤波方法对方波信号滤波能力的不足,实现对方波信号的精确滤波,提出了一种改进的匹配追踪算法。针对方波信号特征,构建了与方波信号匹配而对噪声不敏感的方波原子;基于正交匹配追踪,并吸收子空间追踪的回溯思想,改进了最优原子选择方法;鉴于有用信号与噪声信号的能量差异,使用了一种自适应迭代停止标准,能准确找到有用信号和噪声的临界点,解决噪声能量未知的预估问题。对不同信噪比下的仿真方波信号进行滤波,经实测验证,所提方法在信噪比和均方误差方面都优于常规去噪算法,且保留了方波的特征,适用于方波信号的滤波。
為瞭剋服常規濾波方法對方波信號濾波能力的不足,實現對方波信號的精確濾波,提齣瞭一種改進的匹配追蹤算法。針對方波信號特徵,構建瞭與方波信號匹配而對譟聲不敏感的方波原子;基于正交匹配追蹤,併吸收子空間追蹤的迴溯思想,改進瞭最優原子選擇方法;鑒于有用信號與譟聲信號的能量差異,使用瞭一種自適應迭代停止標準,能準確找到有用信號和譟聲的臨界點,解決譟聲能量未知的預估問題。對不同信譟比下的倣真方波信號進行濾波,經實測驗證,所提方法在信譟比和均方誤差方麵都優于常規去譟算法,且保留瞭方波的特徵,適用于方波信號的濾波。
위료극복상규려파방법대방파신호려파능력적불족,실현대방파신호적정학려파,제출료일충개진적필배추종산법。침대방파신호특정,구건료여방파신호필배이대조성불민감적방파원자;기우정교필배추종,병흡수자공간추종적회소사상,개진료최우원자선택방법;감우유용신호여조성신호적능량차이,사용료일충자괄응질대정지표준,능준학조도유용신호화조성적림계점,해결조성능량미지적예고문제。대불동신조비하적방진방파신호진행려파,경실측험증,소제방법재신조비화균방오차방면도우우상규거조산법,차보류료방파적특정,괄용우방파신호적려파。
To overcome the shortcomings of conventional filter methods for square wave signals,and realize precise de-noising for square wave signals,an improved matching pursuit algorithm was proposed.Firstly, the square atom,which matches with square wave signals and is insensitive to noises,was constructed spe-cially based on the features of square wave signals.Secondly,an improved best atom selecting algorithm combined with the backtracking algorithm of subspace pursuit was applied based on orthogonal matching pursuit.In addition,in view of the different energy distributions between the true signal and noises,an a-daptive iterative stop criterion was put forward,which can find precise critical point between the true sig-nal and noises,and so the estimation problem of the unknown noise energy is solved.In the filtering of the simulated square wave signal with different signal to noise ratios,the method is superior in both of signal to noise ratio and mean square error to the conventional de-noising methods.Validated by measured square wave signals,the algorithm reserves more features of square waves compared with the conventional de-noi-sing approaches,and it is appropriate for the de-noising of square wave signals.