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1.
We consider the problem of building structure estimation using microwave ray tomography. A Bayesian formulation is developed, and a Markov chain Monte Carlo (MCMC) procedure is used to sample the posterior distribution, which is based on a data likelihood defined in terms of a residual misfit between observed and predicted waveforms. To accelerate model optimization, a simulated annealing approach is combined with the MCMC, using specific model moves to explore each component of the model space. Our approach is applicable to data acquired in the frequency or time domain and for monostatic or bistatic acquisition modes. Experimental data for a multi-wall laboratory test structure were acquired using a horn antenna connected to a vector network analyzer and used to validate both the forward model and the inversion approach. Although, in true remote sensing problems for building structure, the model order is usually unknown, in this initial study, the actual inversion experiment is performed in a reduced-dimension model space for which a subset of the variables are taken as known or fixed. Generalization to the variable-dimension problem can be achieved by using reversible jump MCMC sampling procedures.  相似文献   

2.
For linear state space model, the covariance matrix setting errors of process and measurement noise deteriorate the estimation performance of Rauch–Tung–Striebel (RTS) smoother. To address this problem, the Markov Chain Monte Carlo is utilized to sample the state vector and noise covariance matrices simultaneously in this study. The Gibbs sampler is adopted and the corresponding adaptive RTS smoother is designed. Simulation results confirm the performance of proposed smoother.  相似文献   

3.
For state estimation of high accuracy, prior knowledge of measurement noise is necessary. In this paper, a method for solving the joint state estimation problem of jump Markov nonlinear systems (JMNSs) without knowing the measurement noise covariance is developed. By using the Inverse-Gamma distribution to describe the dynamics of measurement noise covariance, the joint conditional posterior distribution of the state variable and measurement noise covariance is approximated by a product of separable variational Bayesian (VB) marginals. In the newly constructed approach, the interacting multiple model (IMM) algorithm, as well as the particle-based approximation strategy, is employed to handle the computationally intractable problem and the nonlinear characteristics of systems, respectively. An interesting feature of the proposed method is that the distribution of states is spanned by a set of particles with weights, while the counterpart of measurement noise covariance is obtained analytically. Moreover, the number of particles is fixed under each mode, indicating a reasonable computational cost. Simulation results based on a numerical example and a tunnel diode circuit (TDC) system are presented to demonstrate that the proposed method can estimate the measurement noise covariance well and provide satisfied state estimation when the statistics of the measurement are unavailable.  相似文献   

4.
In this paper, the state estimation problem for discrete-time networked systems with communication constraints and random packet dropouts is considered. The communication constraint is that, at each sampling instant, there is at most one of the various transmission nodes in the networked systems is allowed to access a shared communication channel, and then the received data are transmitted to a remote estimator to perform the estimation task. The channel accessing process of those transmission nodes is determined by a finite-state discrete-time Markov chain, and random packet dropouts in remote data transmission are modeled by a Bernoulli distributed white sequence. Using Bayes’ rule and some results developed in this study, two state estimation algorithms are proposed in the sense of minimum mean-square error. The first algorithm is optimal, which can exactly compute the minimum mean-square error estimate of system state. The second algorithm is a suboptimal algorithm obtained under a lot of Gaussian hypotheses. The proposed suboptimal algorithm is recursive and has time-independent complexity. Computer simulations are carried out to illustrate the performance of the proposed algorithms.  相似文献   

5.
This paper proposes an optimal three-dimensional (3-D) spatial-temporal cooperative guidance (STCG) law for intercepting a maneuvering target with impact angle and time constraints. The guidance problem is studied to achieve spatial cooperation for multi-directional attack in the normal channel and temporal cooperation for simultaneous interception in the tangential channel, respectively. Firstly, the 3-D optimal impact-angle-control guidance (OIACG) is introduced to formulate spatial interception geometry. Based on this law, the relative trajectory length is analytically derived and an accurate time-to-go predictor is formulated against maneuvering targets. In the tangential channel, an optimal temporal cooperative guidance is proposed by leveraging high-dimensional Schwarz inequality method. The proposed algorithm is believed to outperform the existing nonlinear cooperative guidance laws due to its optimality with specific performance index for minimizing the control expenditure. The convergence properties of the proposed STCG law are provided to facilitate its practical implementation. Comparison simulations and application under the realistic pursuer model and target estimation are performed to demonstrate the effectiveness and robustness of the proposed cooperative method.  相似文献   

6.
Gaussian Chirplet Model (GCM) is commonly used for signal analysis in many fields including ultrasound, radar, sonar, seismology, and biomedicine. The symmetric envelope of GCM is often inadequate in representing real echo envelopes which are more likely to be asymmetric. In our previous work we introduced the Asymmetric Gaussian Chirplet Model (AGCM) that generalizes the GCM. In this paper, an efficient successive parameter estimation algorithm is proposed utilizing echo envelope and instantaneous phase obtained via analytical signal representation. The initial parameters obtained via successive estimation are fine-tuned with a fast Gauss–Newton algorithm developed for the AGCM to achieve Maximum Likelihood Estimation (MLE) of model parameters. The performance of parameter estimation algorithm is formally verified employing Monte-Carlo simulations and Cramer–Rao Lower Bounds. Parameter estimation is shown to be minimum variance and unbiased for SNR levels 10 dB and higher. Furthermore, AGCM has been tested on real ultrasound echoes measured from planar targets. AGCM provides better echo fits than the GCM due to its more flexible envelope.  相似文献   

7.
In this paper, the distributed adaptive fault estimation issue using practical fixed-time design is investigated for attitude synchronization control systems. A distributed fault estimation observer is proposed based on the fixed-time technique. Meanwhile, a novel fixed-time adaptive fault estimation algorithm is also constructed to guarantee convergence rate and improve estimation rapidity. The fault estimation error is uniformly ultimately bounded and is practically fixed-time stable, which converges to the neighborhood of the origin in a fixed time. Finally, simulation results of an attitude synchronization control system are presented to verify the effectiveness of proposed techniques.  相似文献   

8.
In this paper, identification of discrete-time power spectra of multi-input/multi-output (MIMO) systems in innovation models from output-only time-domain measurements is considered.A hybrid identification algorithm unifying mixed norm minimization with subspace estimation method is proposed. The proposed algorithm first estimates a covariance matrix from measurements. A significant dimension reduction is achieved in this step. Next, a regularized nuclear norm optimization problem is solved to enforce sparsity on the selection of most parsimonious model structure. A modification of the covariance estimates in the proposed algorithm generates yet another algorithm capable of handling data records with sequentially and intermittently missing values. The new and the modified identification algorithms are tested on a numerical study and a real-life application example concerned with the estimation of joint power spectral density (PSD) of parallel road tracks.  相似文献   

9.
The dissipative synchronization problem of delayed Markov jump switched neural networks (MJSNNs) under state-dependent switching by the event-triggered gain-scheduling control scheme is studied in this paper. By the introduction of a Markov jump model, which is used to depict the random variation wherein the connection of MJSNNs, the issues we study can take more generality. Via constructing suitable Lyapunov–Krasovskii functionals (LKFs) and applying some matrix inequality scaling methods, sufficient conditions for dissipative synchronization of delayed MJSNN are established. According to such criteria, the event-triggered gain-scheduling control scheme is adopted to design a controller with less terminal communication costs. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.  相似文献   

10.
Robust identification of the linear parameter varying (LPV) finite impulse response (FIR) model with time-varying time delays is considered in this paper. A robust observation model based on Laplace distribution is established to deal with the output data contaminated with the outliers, which are commonly existed in modern industries. A Markov chain model is utilized to model the correlation between the time delays as they do not simply change randomly in reality. A transition probability matrix and an initial probability distribution vector are used to govern the switching mechanism of the time delays. Since it is difficult to optimize the complex log likelihood function directly, the derivations of the proposed algorithm are performed under the framework of Expectation-Maximization (EM) algorithm. A numerical example and a chemical process are utilized to verify the effectiveness of the proposed approach.  相似文献   

11.
In this paper, the identification of the Wiener–Hammerstein systems with unknown orders linear subsystems and backlash is investigated by using the modified multi-innovation stochastic gradient identification algorithm. In this scheme, in order to facilitate subsequent parameter identification, the orders of linear subsystems are firstly determined by using the determinant ratio approach. To address the multi-innovation length problem in the conventional multi-innovation least squares algorithm, the innovation updating is decomposed into sub-innovations updating through the usage of multi-step updating technique. In the identification procedure, by reframing two auxiliary models, the unknown internal variables are replaced by using the outputs of the corresponding auxiliary model. Furthermore, the convergence analysis of the proposed algorithm has shown that the parameter estimation error can converge to zero. Simulation examples are provided to validate the efficiency of the proposed algorithm.  相似文献   

12.
Identification of autoregressive models with exogenous input (ARX) is a classical problem in system identification. This article considers the errors-in-variables (EIV) ARX model identification problem, where input measurements are also corrupted with noise. The recently proposed Dynamic Iterative Principal Components Analysis (DIPCA) technique solves the EIV identification problem but is only applicable to white measurement errors. We propose a novel identification algorithm based on a modified DIPCA approach for identifying the EIV-ARX model for single-input, single-output (SISO) systems where the output measurements are corrupted with coloured noise consistent with the ARX model. Most of the existing methods assume important parameters like input-output orders, delay, or noise-variances to be known. This work’s novelty lies in the joint estimation of error variances, process order, delay, and model parameters. The central idea used to obtain all these parameters in a theoretically rigorous manner is based on transforming the lagged measurements using the appropriate error covariance matrix, which is obtained using estimated error variances and model parameters. Simulation studies on two systems are presented to demonstrate the efficacy of the proposed algorithm.  相似文献   

13.
针对采用改进DNF(denoise-and -forward)方案的Two-way中继系统,提出一种满足匹配性的调制映射方案,进一步提高了DNF方案的BER(bit error rate)性能,并给出BER的计算方法.仿真结果验证了BER计算方法的正确性,以及满足匹配性的调制映射方案的有效性.  相似文献   

14.
In this paper, we study a distributed state estimation problem for Markov jump systems (MJS) over sensor networks, in which each sensor node connects with each other through wireless networks with communication delays. We assume that each sensor node maintains a buffer to store delayed data transmitted from neighbor nodes. A distributed multiple model filter is designed by using the interacting multiple model methods (IMM) and a recursive delays compensation method. In order to ensure the stability, two stability conditions are derived for boundedness of estimation errors and boundedness of error covariance. Finally, the effectiveness of the proposed methods is illustrated by simulations and experiments of maneuvering target tracking.  相似文献   

15.
In this paper, the stability of networked control systems (NCSs) with communication constraints at both channels is investigated. A Conventional Round-Robin Scheduling (CRRS) is applied to deal with the communication constraints issue for its simple structure. Furthermore, a Dynamic Round-Robin Scheduling (DRRS), which can preserve the controllability and the detectability of the systems, is considered. For the unreliable communication channels, two independent homogeneous Markov chains are selected to model the packet dropouts phenomenon in the sensor-to-controller (S/C) channel and the controller-to-actuator (C/A) channel. According to the periodic property of the Round-Robin Scheduling (RRS), an auxiliary system with augmented Markov chain is established by the lifting technique to facilitate the stability analysis of the closed-loop system. A necessary and sufficient condition of the exponential mean-square stability for the NCSs is derived. Two illustrative examples are shown to demonstrate the effectiveness of the proposed stability analysis method.  相似文献   

16.
在基于802.16j的无线中继网络中,考虑路由和调度的联合优化问题,最小化系统总调度时间. 首先采用线性规划的方法建立路由,进行链路业务速率分配,然后基于平移和交换思想提出一种链路调度算法. 理论分析证明所提算法的性能在最坏情况下,不会超过最优性能的1.5倍. 仿真结果表明,所提算法的平均性能非常接近最优性能.  相似文献   

17.
隐马尔科夫模型在很多方面已有广泛应用.讨论了一类更为一般的模型,这类模型由Wojciech Pieczynski首次提出,并且给出了在图像识别中的应用.这里首次给出在离散观测和离散状态下该模型的精确数学描述,其中包括建模、状态估计和参数估计,这些算法都是首次被提出的.  相似文献   

18.
在MB-OFDM超宽带系统中,针对《无线高速率超宽带物理层和媒体访问控制规范》国家标准中MAC层数据结构,提出了一种卡尔曼滤波改进的反馈信道估计算法。该算法是在卡尔曼滤波之前加入一个多级LS算法的预估价。与传统卡尔曼滤波比较,该方法提高了卡尔曼滤波的收敛速度,简化了卡尔曼滤波的迭代过程,最小均方误差性能和误码率性能也略有提升。  相似文献   

19.
Two auxiliary model based recursive identification algorithms, a generalized extended stochastic gradient algorithm and a recursive generalized extended least squares algorithm, are developed for multivariable Box–Jenkins systems. The basic idea is to use the auxiliary models to estimate the unknown noise-free outputs of the system and to replace the unmeasurable terms in the information vectors with their estimates. We prove that the estimation errors given by the proposed algorithms converge to zero under the persistent excitation condition. Finally, an example is provided to show the effectiveness of the proposed algorithms.  相似文献   

20.
In this paper, we consider the discrete memory-less three-way degraded broadcast channel (3WDBC). The main contribution of this paper is in characterizing the capacity region of the discrete memoryless 3WDBC. To end up with this goal, we first develop the achievable region. Then, an outer bound to the capacity region is also derived. Next, the achievable region is shown to meet the outer bound such that the capacity is achieved. After that, the 3WDBC is shown to encompass many well-known multi-user networks such as (i) broadcast channel, (ii) multiple access channel, (iii) two-way channel, and (iv) relay channel. Further, the achievable capacity region is then extended to the additive Gaussian noise channel. Specifically, superposition encoding is employed at each user such that a given user can appropriately allocate its power to broadcast to the other two users. In this direction, two design criteria are theoretically presented and numerically investigated to show the range that the power allocation factor at each user may have.  相似文献   

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