【作者】 陈博；

【导师】 俞立；

【作者基本信息】 浙江工业大学 ， 控制理论与控制工程， 2013， 博士

【摘要】 多传感器信息融合是20世纪70年代以来由于军事、国防和高科技领域的迫切需要发展起来的一门新兴边缘学科,多传感器信息融合估计作为该领域的一个重要分支在军事和民用领域有着重要的应用价值。随着网络通讯技术的飞速发展,在多传感器融合系统中引入有线或无线通信网络作为信息传输的枢纽,从而构成了网络化的多传感器融合系统(Networked Multi-Sensor Fusion Systems, NMFSs)。与传统的多传感器融合系统相比,NMFSs以其布线少、成本低、易于扩展和维护等优点,应用范围和作用在不断扩大,目前是一个热点研究课题。然而,通信网络的引入带来了许多新的问题,从而传统的融合估计方法不适用于NMFSs,因此迫切需要提出适用于网络环境的多传感器信息融合估计理论。在这样的背景下,本文基于射影理论、Lyapunov理论、矩阵分析理论和最优加权融合算法,研究了NMFSs中存在的两个重要问题：一是通信带宽和传感器能量受限问题；二是传感器量测的不确定性及随机时延与丢包问题。研究工作主要包括：1.研究了在通信带宽约束下NMFSs的分布式信息融合估计问题。首先提出了一种有结构限定的维数压缩策略来满足有限的通信带宽,并基于最优加权融合估计算法,导出了带宽受限的有限时域分布式Kalman融合估计器；最后给出了一个简单有效的分量传输方案使得融合估计性能在某些条件下是最优的。另一方面,当NMFSs中的噪声是统计特性未知的能量有界信号时,采用对数量化策略将要传输的局部估计信号量化到有限水平以满足有限的通信带宽;然后利用H∞滤波理论和离散系统的有界实引理导出了保证分布式H∞融合估计性能最优的充要条件,并给出了带宽约束条件下的最优加权矩阵和量化参数。以上研究结果分别通过移动目标跟踪系统和数值例子进行了验证。2.研究了在通信带宽和能量受限下NMFSs的分布式Kalman融合估计问题。为了满足有限的通信带宽,每个时刻最多只有局部估计信号的部分分量以随机形式发送到融合中心,每个传感器则间歇性地发送信息到融合中心以达到节能目的。基于最优加权融合估计算法,给出了带宽和能量受限情况下的分布式Kalman融合估计算法。由于所设计的融合估计器性能依赖于传输分量的选择概率,为此导出了一些传输分量的概率选择准则以保证融合估计器的均方差(Mean Square Error, MSE)有界或收敛。最后,通过移动口标跟踪系统验证了所提方法的有效性。3.研究了在通信量约束下NMFSs的分布式混合H2/H∞融合估计问题,其中系统扰动由高斯白噪声与能量有界噪声共同描述。为了缩减每个时刻传感器与融合中心的通信量,提出了有结构限定的随机维数压缩与对数量化相结合的策略。借助于Lyapunov理论和混合H2/H∞滤波方法,导出了关于量化参数与传输分量选择概率的充分条件以保证分布式H2/H∞融合估计器的稳定性。而且,当每个局部估计分量的传输概率预先给定时,给出了在通信量约束下最优加权矩阵和量化参数的设计方法。最后,通过F404航空发动机模型验证了所提方法的有效性。4.研究了NMFSs中存在随机参数扰动、传感器失效、随机观测时延与丢包的融合估计问题。利用新息方法和代数Riccati方程导出了一个与原系统维数相等的集中式鲁棒Kalman融合估计器。与增广方法相比,它可以降低融合中心的计算复杂度,从而满足系统的实时性要求。基于所设计的集中式融合估计算法,利用矩阵满秩分解方法导出了存在上述不确定性的NMFSs的鲁棒降维加权观测融合Kalman估计器,进一步地减轻融合中心的计算负担。而且,导出了一些依赖于时延发生概率和传感器失效率的充分条件以保证估计器的稳定性和最优性,并给出了稳态Kalman融合估计器。最后,通过数值例子验证了所提方法的有效性。5.研究了NMFSs中存在测量数据丢失、随机传输时延与丢包的分布式Kalman融合估计问题。首先,提出了一个新的随机通信模型来描述NMFSs中的随机传输时延和丢包现象；然后利用线性最优加权融合算法,导出了一个递推的分布式Kalman融合估计器。根据矩阵分析理论导出了一些使得融合估计器的MSE有界或者收敛的充分条件,并给出了稳态分布式Kalman融合估计器。最后,通过移动目标跟踪系统验证了所提方法的有效性。更多还原

【Abstract】 Multi-sensor information fusion, which has attracted people’s great attention, is a ris-ing multi-discipline field started from the1970s with the urgent need of the development of military affairs, national defense, wars and high-tech. As one of important issues in in-formation fusion, the multi-sensor fusion estimation problem has been a focus of research because of their wide application in military and civilian fields. With the rapid development of network communication technology, communication network is introduced to connect the distributed sensors and FC, and this class of systems may be called networked multi-sensor fusion systems (NMFSs). Compared with classical multi-sensor fusion systems, the insertion of the communication network in NMFSs can offer many advantages such as flex-ible architectures, simpler installation, easier maintenance and low cost. Therefore, NMFSs have now been one of the hot research topics.Although NMFSs have brought so many advantages, they also bring lots of new prob-lems and difficulties, thus the conventional fusion estimation approaches will not be ap-plicable to the NMFSs. In this case, an important and practical problem is how to design fusion estimation algorithm for the NMFSs. Under this background, based on the projec-tion theory, Lyapunov theory, matrix analysis theory and optimal weighted fusion algo-rithm, this paper is concerned with two important prolems existing in NMFSs:one is the communication bandwidth and sensor energy constraints, the other is the problem of un-certain measurement, random delay and packet dropouts. The main work is summarized as follows:1. The distributed fusion estimation problem is investigated for a class of NMFSs with communication bandwidth constraints. On one hand, a dimensionality reduction strategy with structural limit is proposed to satisfy finite bandwidth, then based on the optimal es-timation fusion algorithm weighted by matrices, a recursively distributed Kalman fusion estimator is derived, and a simple suboptimal judgement criterion is proposed to determine a group of binary variables such that the mean square error (MSE) of the designed estimator is minimum at each time step. On the other hand, when the process and measurement noises in the NMFSs have unknown statistic characteristic but bounded energy, a group of finite-level logarithmic quantizers are introduced to describe the case of bandwidth constraints. By using H∞filtering theory and the discrete-time bounded real lemma, the necessary and sufficient condition is derived such that the performance of the distributed H∞fusion es-timator is optimal. Under this condition, the optimal weighted matrices and quantization parameters are given. The target tracking system and an illustrative example are given to demonstrate the effectiveness of the proposed methods.2. The distributed Kalman fusion estimation problem is investigated for a class of NMFSs with bandwidth and energy constraints. To satisfy the finite communication band-width, at a particular time, only partial components of each local estimate are allowed to be transmitted to the FC in a random way, while each sensor intermittently sends information to the FC for reducing energy consumptions. Then a recursively distributed fusion Kalman estimator is derived in the linear minimum variance sense. Since the performance of the de-signed estimator is dependent on the selecting probability of each component, some criteria for the choice of probabilities are derived such that the MSEs of the designed estimators are bounded or convergent. The steady-state distributed fusion Kalman estimator is also given. Finally, the target tracking system is given to demonstrate the effectiveness of the proposed methods.3. The distributed mixed H2/H∞fusion estimation problem is investigated for a class of NMFSs with limited communication capacity, where the system perturbations are mod-eled by white noise and bounded energy noise. The stochastic dimensionality reduction strategy with structural limit and logarithmic qunatization strategy are simultaneously taken into account for deducing the traffic between the distributed sensors and FC. By resorting to Lyapunov theory and the mixed H2/H∞filtering approach, a sufficient condition, which is dependent on the quantization parameters and the selecting probabilities of the trans-mitted component, is derived such that the distributed mixed H2/H∞fusion estimator is stable. For given the transmitting probabilities of the estimate component, the design ap-proach for the optimal weighted matrices and quantization parameters is presented under the communication capacity constraints. Finally, the F-404aircraft engine model is given to demonstrate the effectiveness of the proposed methods.4. The fusion estimation problem is investigated for a class of NMFSs with sensor fail-ures, stochastic parameter uncertainties, random observation delays and packet dropouts. A novel model is proposed to describe the random observation delays and packet dropouts, and a robust optimal fusion estimator is designed by using the innovation analysis method and algebraic Riccati equation. The dimension of the designed estimator is the same as the original system, which helps reduce computation cost as compared with the augmentation method, thus the designed estimator can satisfy the real-time performance of the system. Moreover, robust reduced-dimension observation fusion Kalman estimators are proposed to further reduce the computation burden. Some sufficient conditions for stability and optimal-ity of the designed fusion estimators are given, and steady-state Kalman fusion estimator is also presented. Simulation results show the effectiveness of the proposed methods.5. The distributed Kalman fusion estimation problem is investigated for a class of NMFSs with missing sensor measurements, random transmission delays and packet dropouts. A novel stochastic model is proposed to describe the transmission delays and packet dropouts, and an optimal distributed Kalman fusion estimator is designed based on the optimal fusion criterion weighted by matrices. Some sufficient conditions are derived such that the MSE of the designed estimator is bounded or convergent. Moreover, steady-state distributed Kalman fusion estimator is also presented. Finally, the target tracking system is given to demonstrate the effectiveness of the proposed methods.更多还原