水声高精度定位的后置处理技术
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摘要
为了对水下目标进行精确的定位和跟踪,需要对实时解算出的点轨迹作后置处理。本文分别从空间数据和时间数据两方面进行后置处理。空间数据即对点轨迹进行滤波平滑提高定位精度;时间数据处理即对测量的时延数据进行后置处理,包括专家系统从干扰数据中挑选出直达声脉冲,修正声线弯曲引起的定位误差两方面。
在空间数据处理方面,卡尔曼滤波应用于水声定位系统的后置处理是很有效的。卡尔曼滤波实质是递归滤波的方法,采用线性无偏最小方差准则以得到过程的最优估计,具有适用于多输入、多输出、非平稳随机过程等许多优点,因而得到广泛应用。在高斯分布条件下,卡尔曼滤波是最小方差估计,是一切估计中最好的估计。结果表明将卡尔曼滤波器用于定位轨迹的滤波,可有效提高目标位置测量的精度。
时延数据的准确对于保证水声定位的良好性能是关键的。时延估计的研究已经取得了相当成功的进展,互相关时延估计可以达到1ms的精度(不考虑多普勒影响),说明时延估计已足够精确,对时延估计进行滤波处理来提高定位精度意义不大,需要考虑的是多途效应和声线弯曲产生的时延与直线距离的关系。
对于水下声学定位系统,由于其原理是通过测量从声源到各接收阵元的声脉冲间的时延(时延差)工作的,由于界面反射的影响,当直达声与各种海面、海底反射声同时存在时,是否能够给出正确的直达声时延值将直接影响到定位精度,甚至导致解算不出目标轨迹。由于高精度定位的要求,我们采取了硬件方法和软件方法来挑选出直达声,达到准确定位的目的。
在挑选出直达声之后,由于海洋中沿深度方向存在声速梯度,导致声线发生弯曲,使得声波的行进距离大于发射点和接收点的直线距离。为提高定位精度,必须进行声线修正。本文在研究了射线声学理论和水声信道的基础上,采用平均声速法、迭代方法和查表法三种方法进行声线修正来尝试提高定位精度。
最后给出了仿真和试验结果。
In order to locate and track an underwater moving target accurately, it is required to post process the real-time working-out trajectory. Spacial and temporal post processing methods are introduced respectively in this paper. Spacial post processing is used to improve position accuracy by filtering real-time tracking output. Temporal methods accurate the trajectory by post processing the real-time time delay output. Two kinds of methods are mainly used in temporal post processing, including expert system for selecting the pulses of direct path in case of multi-path environment and correcting the errors caused by the bending rays.
On spacial data processing, Kalman filter can be used validly for post processing in underwater acoustic positioning systems. Kalman filter is defined as a recursive filtering method. It is an optimal estimator under the linear and unprejudiced least mean square error rule. It can be applied in multi input-output and non-steady random process. Kalman filter is the least mean square error estimator in Gaussian noisy processes, which is an optimal estimator in all. Kalman filter can improve the target's location metrical precision in effect.
The preciseness of time-delay is the key for good location performance in underwater acoustic positioning system. Research on time delay estimation has made successful improvement. Cross-correlation time delay estimator can achieve precision below 1 ms, which is accurate enough (not considering the impact of Doppler). It is more important to consider time delay errors caused by the multi-path effect and the bending of the sound rays than the errors caused by estimators (which is decided by the bend width).
Underwater acoustic positioning system locates by measuring the time-delays or time-delay differences of distance pulses from the target to the receiving buoys. The influence on the interfacial reflections is essential to select the direct pulses correctly for proper operation. We select direct pulses by both hardware method and software method to improve position accuracy.
After selecting direct pulses, in an underwater channel, sound rays usually propagate along a bending curve because of ununiform of the sound velocity, which would cause great range error in positioning system. So the correction of sound velocity must be considered carefully for a better position accuracy. By studying the ray theory and underwater acoustic channel, mean velocity of sound、recursion method and table-look-up method are used to correct the bending of sound rays for a better positioning accuracy.
Finally, simulation and experiment results are given.
在空间数据处理方面,卡尔曼滤波应用于水声定位系统的后置处理是很有效的。卡尔曼滤波实质是递归滤波的方法,采用线性无偏最小方差准则以得到过程的最优估计,具有适用于多输入、多输出、非平稳随机过程等许多优点,因而得到广泛应用。在高斯分布条件下,卡尔曼滤波是最小方差估计,是一切估计中最好的估计。结果表明将卡尔曼滤波器用于定位轨迹的滤波,可有效提高目标位置测量的精度。
时延数据的准确对于保证水声定位的良好性能是关键的。时延估计的研究已经取得了相当成功的进展,互相关时延估计可以达到1ms的精度(不考虑多普勒影响),说明时延估计已足够精确,对时延估计进行滤波处理来提高定位精度意义不大,需要考虑的是多途效应和声线弯曲产生的时延与直线距离的关系。
对于水下声学定位系统,由于其原理是通过测量从声源到各接收阵元的声脉冲间的时延(时延差)工作的,由于界面反射的影响,当直达声与各种海面、海底反射声同时存在时,是否能够给出正确的直达声时延值将直接影响到定位精度,甚至导致解算不出目标轨迹。由于高精度定位的要求,我们采取了硬件方法和软件方法来挑选出直达声,达到准确定位的目的。
在挑选出直达声之后,由于海洋中沿深度方向存在声速梯度,导致声线发生弯曲,使得声波的行进距离大于发射点和接收点的直线距离。为提高定位精度,必须进行声线修正。本文在研究了射线声学理论和水声信道的基础上,采用平均声速法、迭代方法和查表法三种方法进行声线修正来尝试提高定位精度。
最后给出了仿真和试验结果。
In order to locate and track an underwater moving target accurately, it is required to post process the real-time working-out trajectory. Spacial and temporal post processing methods are introduced respectively in this paper. Spacial post processing is used to improve position accuracy by filtering real-time tracking output. Temporal methods accurate the trajectory by post processing the real-time time delay output. Two kinds of methods are mainly used in temporal post processing, including expert system for selecting the pulses of direct path in case of multi-path environment and correcting the errors caused by the bending rays.
On spacial data processing, Kalman filter can be used validly for post processing in underwater acoustic positioning systems. Kalman filter is defined as a recursive filtering method. It is an optimal estimator under the linear and unprejudiced least mean square error rule. It can be applied in multi input-output and non-steady random process. Kalman filter is the least mean square error estimator in Gaussian noisy processes, which is an optimal estimator in all. Kalman filter can improve the target's location metrical precision in effect.
The preciseness of time-delay is the key for good location performance in underwater acoustic positioning system. Research on time delay estimation has made successful improvement. Cross-correlation time delay estimator can achieve precision below 1 ms, which is accurate enough (not considering the impact of Doppler). It is more important to consider time delay errors caused by the multi-path effect and the bending of the sound rays than the errors caused by estimators (which is decided by the bend width).
Underwater acoustic positioning system locates by measuring the time-delays or time-delay differences of distance pulses from the target to the receiving buoys. The influence on the interfacial reflections is essential to select the direct pulses correctly for proper operation. We select direct pulses by both hardware method and software method to improve position accuracy.
After selecting direct pulses, in an underwater channel, sound rays usually propagate along a bending curve because of ununiform of the sound velocity, which would cause great range error in positioning system. So the correction of sound velocity must be considered carefully for a better position accuracy. By studying the ray theory and underwater acoustic channel, mean velocity of sound、recursion method and table-look-up method are used to correct the bending of sound rays for a better positioning accuracy.
Finally, simulation and experiment results are given.
引文
[1]JI.M.布列霍夫斯基.海洋声学.科学出版社.1983.
[2]惠俊英,生雪莉.水下声信道.第二版.北京:国防工业出版社,1992:1-29页
[3]G.C.Carter.Coherence and Time Delay Estimation.An Applied Tutorial for Research,Development,Test and Evaluation Engineers.New York:IEEE.1993
[4]A.H.Quazi.An Overview on the time delay estimate in active and passive systems for target localization.IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-29.P527-533.June.1981
[5]A.O.Hero,S.C.Schwartz.A new generalized cross correlator,IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-33.P38-45.Feb.1985
[6]B.M.Bell,T.E.Ewart.Separating multipaths by global optimization of a multidimensional matched filter.IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-34.P1029-1037.Oct.1986
[7]I.P.Kirsteins.High resolution time delay estimation,in Proc.ICASSP'87.P451-454.Apr.1987
[8]I.P.Kirsteins,A.H.Quazi.Exact Maximum Likelihood Time Delay Estimation for Deterministic Signals.in Proceedings of EUSIPCO88.Sep.1988
[9]R.J.Vaccaro.C.S.Ramalingam,D.W.Tufts.Least-square time-delay estimation for transient signals in a multipath environment.J.Acoust.Soc.Amer.vol.92.P210-219.July.1992
[10]Y.Bian,D.Last.Eigen-decomposition techniques for Loran-C skwave estimation.IEEE Trans.Aerosp.Electron.Syst.vol.33.Pl17-124.Jan.1997
[11]I.P.Kirsteins.High resolution time delay estimation,in Proc.ICASSP'87.P451-454.Apr.1987
[12]I.P.Kirsteins,A.C.Kot.Performance analysis of a high resolution time delay estimation algorithm,in Proc.ICASSP'90,P2767-2770,Apr.1990
[13]R.O.Schmidt.Multiple emitter location and signal parameter estimation.IEEE Trans.Antennas Propagat.vol.AP-34.P276-280.Mar.1986
[14]张群飞,黄建国,保铮.用子空间旋转不变法同时估计水下目标的距离和方位.声学学报.1999.24(4).400-406页
[15]T.K.Moon.The expectation-maximization algorithm.IEEE Signal Processing Mag.P47-60.Nov.1996
[16]M.Feder,E.Weinstein.Parameter estimation of superimposed signals using the EM algorithm.IEEE Trans.Acoust,Speech,Signal Processing.vol.36.P477-489.Apr.1988
[17]M.R.Azimi-Sadjadi,S.Charleston.A New Time Delay Estimation in Subbands for Resolving Multiple Specular Reflections.IEEE Tans.Signal Processing.vol.46.P3398-3403.Dec.1998
[18]Renbiao Wu,Jian Li.Time-Delay Estimation via Optimizing Highly Oscillatory Cost Functions.IEEE Journal of Oceanic Engineering.vol.23.P235-243.July.1998
[19]王燕,梁国龙.一种适用于长基线水声定位系统的声线修正方法.哈尔滨工程大学学报.2002,10:32-34页
[20]Optimal signal processing of passive sonar range and bearing estimation.J.A.S.A.Vol-58,No.1.1972:12P
[21]An application of Kalman filtering to underwater tracking.AD/A039466.1976:45-47P
[22]An application of Kalman filtering to torpedo tracking.AD/A092303.1980:127-130P
[23]Improved extended Kalman filter design for passive tracking.IEEE Trans.Vol.AC-25,No.4.1980:5P
[24]Kalman filter behavior in beatings-only tracking application.IEEE Trans.Vol.AES-15,No.1,1979:11P
[25]Real time Kalman filtering for torpedo range tracking.AD/A064896.1978:96P
[26]S.N.Gupta and S.M.Ahn.Closed-form Solution of Target Tracking Filters with Discrete Measurements.IEEE Trans.on Aerospace and Electronic Systems.Vol.AES-19,No.4,July.1983:532-538P
[27]樊羚珂.卡尔曼滤波在被动测距声呐中的应用.哈尔滨船舶工程学院学报,Vol.7,No.2,1996.6:58-69页
[28]焦阳.无源测距的扩展卡尔曼滤波.声学学报,Vol.7,No.6,1987.6
[29]水下噪声源声跟踪与自适应卡尔曼滤波.海洋技术,1988.3
[30]吴秋平,万德钧等.车载GPS/DR组合导航系统的研究及其滤波算法.东南大学学报,Vol.27,No.2,1997:56-59页
[31]李凡.几种典型的自适应航迹跟踪滤波算法的介绍和比较研究.导航.No.2.1998:80-85页
[32]周东华等.一种带多重次优渐消因子的扩展卡尔曼滤波器.自动化学报.Vol.17,No,6,1991:680-695页
[33]房建成,万德钧.GPS动态定位的强跟踪卡尔曼滤波研究.东南大学学报,Vol.27,No.2,1997:60-66页
[34]保谦,张平.卡尔曼滤波在罗兰C系统中的应用.导航,No.4,1991:98-106页
[35]秦永元等.卡尔曼滤波与组合导航原理.西北工业大学出版社.1998.2:33-35页,128-129页,136-138页
[36]梁国龙.非同步水声定位系统及其后置处理.哈尔滨船舶工程学院硕士学位论文,1990:44-57页
[37]陈春玉译.卡尔曼滤波及数据平滑在鱼雷跟踪中的应用.ADA121917(美),1982.10:104-111页
[38]项楚琪,田坦.离散估计导论.哈尔滨船舶工程学院出版社,1989
[39]王燕.非合作目标精确定位技术研究.哈尔滨工程大学博士学位论文,2006:50页
[40]惠俊英编著.水下声信道.国防工业出版社,1992:20页
[41]刘伯胜,雷家煜.水声学原理。哈尔滨工程大学出版社,1993:101-102页,109-113页
[42]田坦,刘国枝,孙大军.声呐技术.哈尔滨工程大学出版社,2000:252-253 页
[43]王燕,梁国龙.一种适用于长基线水声定位系统的声线修正方法.哈尔滨工程大学学报,2002.10:32-34页
[44]李迎春,吴德明.短基线平面阵形双曲面定位系统的声线修正.声学学报,1992(9):340-344页
[45]范敏毅.水下声信道的仿真与应用研究.哈尔滨工程大学博士学位论文,2000
[46]张光普.导航、定位、通信一体化系统总体技术研究.哈尔滨工程大学博士学位论文.2007
[47]付进.长基线定位系统信号处理关键技术研究.哈尔滨工程大学博士学位论文.2007
[48]赵羽.界面反射对水下目标定位的影响分析.哈尔滨工程大学硕士学位论文.2001:10-12页
[49]生雪莉.被动式三维水声定位技术研究.哈尔滨工程大学硕士学位论文.2001:37-38页
[50]王逸林.水下目标跟踪系统声学信号处理.哈尔滨工程大学硕士学位论文,2002
[51]侯自强,李贵斌.声呐信号处理一原理与设备.海洋出版社.1986:387-389页
[2]惠俊英,生雪莉.水下声信道.第二版.北京:国防工业出版社,1992:1-29页
[3]G.C.Carter.Coherence and Time Delay Estimation.An Applied Tutorial for Research,Development,Test and Evaluation Engineers.New York:IEEE.1993
[4]A.H.Quazi.An Overview on the time delay estimate in active and passive systems for target localization.IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-29.P527-533.June.1981
[5]A.O.Hero,S.C.Schwartz.A new generalized cross correlator,IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-33.P38-45.Feb.1985
[6]B.M.Bell,T.E.Ewart.Separating multipaths by global optimization of a multidimensional matched filter.IEEE Trans.Acoust,Speech,Signal Processing.vol.ASSP-34.P1029-1037.Oct.1986
[7]I.P.Kirsteins.High resolution time delay estimation,in Proc.ICASSP'87.P451-454.Apr.1987
[8]I.P.Kirsteins,A.H.Quazi.Exact Maximum Likelihood Time Delay Estimation for Deterministic Signals.in Proceedings of EUSIPCO88.Sep.1988
[9]R.J.Vaccaro.C.S.Ramalingam,D.W.Tufts.Least-square time-delay estimation for transient signals in a multipath environment.J.Acoust.Soc.Amer.vol.92.P210-219.July.1992
[10]Y.Bian,D.Last.Eigen-decomposition techniques for Loran-C skwave estimation.IEEE Trans.Aerosp.Electron.Syst.vol.33.Pl17-124.Jan.1997
[11]I.P.Kirsteins.High resolution time delay estimation,in Proc.ICASSP'87.P451-454.Apr.1987
[12]I.P.Kirsteins,A.C.Kot.Performance analysis of a high resolution time delay estimation algorithm,in Proc.ICASSP'90,P2767-2770,Apr.1990
[13]R.O.Schmidt.Multiple emitter location and signal parameter estimation.IEEE Trans.Antennas Propagat.vol.AP-34.P276-280.Mar.1986
[14]张群飞,黄建国,保铮.用子空间旋转不变法同时估计水下目标的距离和方位.声学学报.1999.24(4).400-406页
[15]T.K.Moon.The expectation-maximization algorithm.IEEE Signal Processing Mag.P47-60.Nov.1996
[16]M.Feder,E.Weinstein.Parameter estimation of superimposed signals using the EM algorithm.IEEE Trans.Acoust,Speech,Signal Processing.vol.36.P477-489.Apr.1988
[17]M.R.Azimi-Sadjadi,S.Charleston.A New Time Delay Estimation in Subbands for Resolving Multiple Specular Reflections.IEEE Tans.Signal Processing.vol.46.P3398-3403.Dec.1998
[18]Renbiao Wu,Jian Li.Time-Delay Estimation via Optimizing Highly Oscillatory Cost Functions.IEEE Journal of Oceanic Engineering.vol.23.P235-243.July.1998
[19]王燕,梁国龙.一种适用于长基线水声定位系统的声线修正方法.哈尔滨工程大学学报.2002,10:32-34页
[20]Optimal signal processing of passive sonar range and bearing estimation.J.A.S.A.Vol-58,No.1.1972:12P
[21]An application of Kalman filtering to underwater tracking.AD/A039466.1976:45-47P
[22]An application of Kalman filtering to torpedo tracking.AD/A092303.1980:127-130P
[23]Improved extended Kalman filter design for passive tracking.IEEE Trans.Vol.AC-25,No.4.1980:5P
[24]Kalman filter behavior in beatings-only tracking application.IEEE Trans.Vol.AES-15,No.1,1979:11P
[25]Real time Kalman filtering for torpedo range tracking.AD/A064896.1978:96P
[26]S.N.Gupta and S.M.Ahn.Closed-form Solution of Target Tracking Filters with Discrete Measurements.IEEE Trans.on Aerospace and Electronic Systems.Vol.AES-19,No.4,July.1983:532-538P
[27]樊羚珂.卡尔曼滤波在被动测距声呐中的应用.哈尔滨船舶工程学院学报,Vol.7,No.2,1996.6:58-69页
[28]焦阳.无源测距的扩展卡尔曼滤波.声学学报,Vol.7,No.6,1987.6
[29]水下噪声源声跟踪与自适应卡尔曼滤波.海洋技术,1988.3
[30]吴秋平,万德钧等.车载GPS/DR组合导航系统的研究及其滤波算法.东南大学学报,Vol.27,No.2,1997:56-59页
[31]李凡.几种典型的自适应航迹跟踪滤波算法的介绍和比较研究.导航.No.2.1998:80-85页
[32]周东华等.一种带多重次优渐消因子的扩展卡尔曼滤波器.自动化学报.Vol.17,No,6,1991:680-695页
[33]房建成,万德钧.GPS动态定位的强跟踪卡尔曼滤波研究.东南大学学报,Vol.27,No.2,1997:60-66页
[34]保谦,张平.卡尔曼滤波在罗兰C系统中的应用.导航,No.4,1991:98-106页
[35]秦永元等.卡尔曼滤波与组合导航原理.西北工业大学出版社.1998.2:33-35页,128-129页,136-138页
[36]梁国龙.非同步水声定位系统及其后置处理.哈尔滨船舶工程学院硕士学位论文,1990:44-57页
[37]陈春玉译.卡尔曼滤波及数据平滑在鱼雷跟踪中的应用.ADA121917(美),1982.10:104-111页
[38]项楚琪,田坦.离散估计导论.哈尔滨船舶工程学院出版社,1989
[39]王燕.非合作目标精确定位技术研究.哈尔滨工程大学博士学位论文,2006:50页
[40]惠俊英编著.水下声信道.国防工业出版社,1992:20页
[41]刘伯胜,雷家煜.水声学原理。哈尔滨工程大学出版社,1993:101-102页,109-113页
[42]田坦,刘国枝,孙大军.声呐技术.哈尔滨工程大学出版社,2000:252-253 页
[43]王燕,梁国龙.一种适用于长基线水声定位系统的声线修正方法.哈尔滨工程大学学报,2002.10:32-34页
[44]李迎春,吴德明.短基线平面阵形双曲面定位系统的声线修正.声学学报,1992(9):340-344页
[45]范敏毅.水下声信道的仿真与应用研究.哈尔滨工程大学博士学位论文,2000
[46]张光普.导航、定位、通信一体化系统总体技术研究.哈尔滨工程大学博士学位论文.2007
[47]付进.长基线定位系统信号处理关键技术研究.哈尔滨工程大学博士学位论文.2007
[48]赵羽.界面反射对水下目标定位的影响分析.哈尔滨工程大学硕士学位论文.2001:10-12页
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