共查询到20条相似文献，搜索用时 31 毫秒
1.
The problem of estimating the shape of a towed array instrumented with either depth sensors, compasses, or both in a discrete-time state-space formulation is treated in a companion paper by D. A. Gray et al. (to appear), in which the state-space representation is derived from a dynamical model of the propagation of tow-point-induced motion down the array. A Kalman filter is derived to recursively estimate the shape of this towed array, and solutions to the Riccati equation are used to predict the mean square error of the Kalman filter array shape estimates. The present study investigates the performance of this Kalman filter approach as an array shape estimator using both simulated examples and sea trial data. Fundamental to the Kalman filter approach is the model that describes the dynamical behavior of the towed array. The results of an experimental program that was undertaken to validate this model are also presented 相似文献
2.
纯方位目标跟踪-直角坐标卡尔曼滤波算法 总被引：2，自引：1，他引：1
对于纯方位目标跟踪问题 ,在利用卡尔曼滤波算法进行处理时 ,首先要进行观测方程及状态方程的线性化处理 ,自然导致线性化误差 ,为减少它对目标跟踪的影响 ,该文利用衰减记忆的卡尔曼滤波算法 ,通过蒙特卡罗模拟仿真实验表明其跟踪效果在收敛速度和收敛率以及稳定性等方面有了较大的提高。 相似文献
3.
A model-based approach to solve a deep water ocean acoustic signal processing problem based on a state-space representation of the normal-mode propagation model is developed. The design of a model-based processor (MBP) for signal enhancement employing an array consisting of a large number of sensors for a deep ocean surveillance operation is discussed. The processor provides enhanced estimates of the measured pressure-field, modes, and residual (innovations) sequence indicating the performance or adequacy of the propagation model relative to the data. It is shown that due to the structure of the normal-mode model the state-space propagator is not only feasible for this large scale problem, but in fact, can be implemented by a set of decoupled parallel second-order processors, implying a real-time capability. In the paper we discuss the design and application of the processor to a realistic set of simulated pressure-field data developed from a set of experiments and sound speed parameters 相似文献
4.
The Marine Physical Laboratory has designed, fabricated, and taken to sea self-contained, freely drifting acoustic sensors which can measure signal propagation and ambient ocean noise in the 1-20-Hz band for up to 25-hour periods. The deployment of several freely drifting floats forms an array of sensors whose outputs can be combined after the experiment with a beamformer. A Kalman filter and a least-squares estimator have been developed to estimate float positions from travel-time measurements. Computer simulation is used to compare filter performance-under several deployment scenarios. Results show that the Kalman filter performs better than the least-squares filter when the floats are subjected to small-magnitude accelerations between measurements. Neither filter was sensitive to relatively major changes in deployment geometry as long as the sound-speed profile is known exactly 相似文献
5.
A system-theoretic approach is proposed to investigate the feasibility of reconstructing a sound velocity profile (SVP) from acoustical hydrophone measurements. A state-space representation of the normal-mode propagation model is used. It is shown that this representation can be utilized to investigate the so-called observability of the SVP from noisy measurement data. A model-based processor is developed to extract the required information, and it is shown that even in cases where limited SVP information is available, the SVP can be estimated using this approach. Based on this framework, investigations are made of model-based solutions to the sound velocity profile and related parameter estimation problems. In particular, a processor is designed that allows in situ recursive estimation of the sound velocity profile from simulated data 相似文献
6.
Observation bias correction with an ensemble Kalman filter 总被引：1，自引：0，他引：1
ELANA J. FERTIG SEUNG-JONG BAEK BRIAN R. HUNT EDWARD OTT ISTVAN SZUNYOGH JOSÉ A. ARAVÉQUIA EUGENIA KALNAY HONG LI JUNJIE LIU 《地球，A辑:动力气象学与海洋学》2009,61(2):210-226
This paper considers the use of an ensemble Kalman filter to correct satellite radiance observations for state dependent biases. Our approach is to use state-space augmentation to estimate satellite biases as part of the ensemble data assimilation procedure. We illustrate our approach by applying it to a particular ensemble scheme—the local ensemble transform Kalman filter (LETKF)—to assimilate simulated biased atmospheric infrared sounder brightness temperature observations from 15 channels on the simplified parameterizations, primitive-equation dynamics (SPEEDY) model. The scheme we present successfully reduces both the observation bias and analysis error in perfect-model simulations. 相似文献
7.
The towfish location and orientation problems that arise in using side-scan sonar to detect objects on the sea bottom are treated separately. Data which locate the towfish relative to the ship are usually deteriorated by multipath receptions and other effects. In order to overcome this serious degradation in the location measurements, a modified Kalman filter is proposed. An estimate of the state transition matrix for this filter is derived, and a means of switching between two Kalman gains is suggested. The feasibility of the proposed filter is justified by a case study. Improved estimates of towfish pitch and heading measurements are obtained by a separate system employing model identification and subsequent Kalman filtering. Application of these methods to data from similar towed side-scan sonar systems should yield significant gains in object location accuracy 相似文献
8.
《Oceanic Engineering, IEEE Journal of》2009,34(4):586-602
9.
MICHAEL K. TIPPETT STEPHEN E. COHN RICARDO TODLING DAN MARCHESIN 《地球，A辑:动力气象学与海洋学》2000,52(5):533-553
Ensemble and reduced‐rank approaches to prediction and assimilation rely on low‐dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time‐independent systems are used to identify factors that cause the steady‐state analysis error covariance to admit a low‐dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix , a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady‐state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time‐dependent systems. If much of the steady‐state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady‐state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting non‐modal transient growth. Failure to observe growing modes leads to increased steady‐state analysis error variances. Leading eigenvectors of the steady‐state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest‐order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady‐state analysis error covariance matrix. 相似文献
10.
一个稳态Kalman滤波风暴潮数值预报模式 总被引：4，自引：1，他引：4
利用Kalman滤波资料同化技术将海洋站水位观测资料融入二维线性风暴潮模式中,研制具有资料同化能力的风暴潮预报模式,改进风暴潮模式计算结果.通过在风暴潮模式的动量方程中加入模式噪声项来修正模式本身和气象强迫力的不确定性.确定性模式的输出通过带有观测噪声的观测方程与可利用的海洋站的潮位观测资料联系起来.假定初始的模式噪声和观测噪声满足均值为0的高斯分布,用迭代法得到计算区域的状态向量的稳态Kalman滤波,进而得到风暴潮模式输出的最优线性校正结果.利用这种资料同化技术,对1956年发生在东海的一次强风暴潮过程进行了后报试验,结果表明,该同化方法对短期风暴潮水位后(预)报有一定的改进. 相似文献
11.
ImUcrIONThe deterministic storm stirge nurnrical fOrecast Tnedel has played an imPOrtant role inroutine storm surge real-time fOrecast. But somtimes the error of forecast is still large by usingdeterministic medels (Je1esnianshi et al., l992). The source of these errors mainly comesfrom (1 ) errors of wind stress and medel's open boundary, (2) non--optimized medel param-eter, (3) error of model equations, (4) error of medel's numrical methed, etc. The effec-ti ve methed to solve this probl… 相似文献
12.
This study proposes a method for identification of the nonlinear dynamic model of an AUV while some states are unmeasured; hence, it concentrates on a nonlinear “state and parameter estimation” issue. In this method, a local linearization is used for solving the nonlinear dynamics based on the extended Kalman filter (EKF), and a particle filter (PF) is used to minimize errors and variances of the nonlinear system. In other words, the PF is combined with the EKF in the form of the extended Kalman particle filter (EKPF). The EKPF method is independent of the initial values and satisfies the limits of the parameters and also the assumption that the hydrodynamic coefficients are constant. Hence, it is shown when the ranges or signs of some parameters are known, the EKPF is a more accurate estimator than the EKF. Moreover, a new simulation is done using the model estimated by the EKPF and the results are compared and validated with the measured data of a new experimental test. It is shown that the obtained model can predict the trajectory path with the total normalized root-mean-square error (NRMSE) of 14% and the surge mean speed with the NRMSE of 5%; and it describes the 6DOF motion of the AUV more accurate than the EKF model. 相似文献
13.
Parameter sensitivity of three Kalman filter schemes for assimilation of water levels in shelf sea models 总被引：2，自引：0，他引：2
In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter. A sensitivity analysis of key parameters in the schemes is undertaken for a setup in an idealised bay. The sensitivity of the resulting root mean square error (RMSE) is shown to be low to moderate. Hence the schemes are robust within an acceptable range and their application even with misspecified parameters is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact of assimilating even very few measurements. 相似文献
14.
It is shown that the performance of a conventional matched filter can be improved if the reference (replica) channel compensates for the distortion by the ocean medium. A model-based matched filter is generated by correlating the received signal with a reference channel that consists of the transmitted signal convolved with the impulse response of the medium. The channel impulse responses are predicted with a broadband propagation model using in situ sound speed measured data and archival bottom loss data. The relative performance of conventional and model-based matched filter processing is compared for large time-bandwidth-product linear-frequency-modulated signals propagating in a dispersive waveguide. From ducted propagation measurements conducted in an area west of Sardinia, the model-based matched filter localizes the depths of both the source and receiving array and the range between them. The peak signal-to-noise ratio for the model-based matched filter is always larger than that of the conventional filter 相似文献
15.
The coupling between a coaxial array of six ferroelectric shells and its fluid environment is computed by an application of N-port theory. Properties of the lowest ("breathing") mode of the shells are determined by using three-dimensional finite elements, and this knowledge is utilized in defining an N-port representation of the array. An N-port representation of the external fluid is obtained by solving the Helmholtz integral equation that relates fluid velocities and pressure on the exterior of the array. The two N-ports are coupled together in a standard circuit-theoretic manner to produce an equation for the electrical driving-point impedance of the loaded projector. Several frequency responses, which illustrate the effects of varying certain parameters are presented. 相似文献
16.
研究了单频GPS精密单点定位的算法,包括单频精密单点定位的回归方程及卡尔曼滤波用于单频精密单点定位,探讨卡尔曼滤波的观测方程和状态方程,给出了状态转移矩阵及系统噪声矩阵.通过算例验证了在1s采样率的情况下,定位达到了分米级的精度. 相似文献
17.
Ecologists have an unprecedented array of bio-logging technologies available to conduct in situ studies of horizontal and vertical movement patterns of marine animals. These tracking data provide key information about foraging, migratory, and other behaviours that can be linked with bio-physical datasets to understand physiological and ecological influences on habitat selection. In most cases, however, the behavioural context is not directly observable and therefore, must be inferred. Animal movement data are complex in structure, entailing a need for stochastic analysis methods. The recent development of state-space modelling approaches for animal movement data provides statistical rigor for inferring hidden behavioural states, relating these states to bio-physical data, and ultimately for predicting the potential impacts of climate change. Despite the widespread utility, and current popularity, of state-space models for analysis of animal tracking data, these tools are not simple and require considerable care in their use. Here we develop a methodological “road map” for ecologists by reviewing currently available state-space implementations. We discuss appropriate use of state-space methods for location and/or behavioural state estimation from different tracking data types. Finally, we outline key areas where the methodology is advancing, and where it needs further development. 相似文献
18.
A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (depth) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile, etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. These models are then generalized to the stochastic case where an approximate Gauss-Markov theory applies. The resulting Gauss-Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves. In particular, a processor is designed that allows in situ recursive estimation of the required velocity functions. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model's fit to the data 相似文献
19.
Different data assimilation methods such as an extended Kalman filter, the optimal interpolation method, and a method based on the Fokker-Planck equation applications are considered. Data from the ARGO drifters are assimilated into the HYCOM shallow water model (University of Miami, USA). Throughout the study, the schemes and methods of parallel computations with an MPI library are used. The results of the computations with assimilations are compared between themselves and with independent observations. The method based on the Fokker-Planck equation and the extended Kalman filter are preferable because they give better results than the optimal interpolation scheme. The various model characteristics of the ocean, such as the heat content fields and others, are analyzed after the data assimilation. 相似文献
20.
The problem of tracking the directions-of-arrival (DOAs) of multiple moving sonar targets with an array of passive sensors is complicated by sensor movement. An algorithm for the joint tracking of source DOAs and sensor positions is presented to address this problem. Initial maximum-likelihood estimates of source DOAs and sensor positions are refined by Kalman filtering. Spatio-temporally correlated array movement is considered. Source angle dynamics are used to achieve correct data association. The new technique is capable of performing well for the difficult cases of sources that cross in angle as well as for fully coherent sources. Computer simulations show that the approach is robust in the presence of array motion modeling uncertainty and effectively reduces dependence on expensive and possibly unreliable hardware 相似文献