本文選題：無線傳感器網(wǎng)絡 + 卡爾曼濾波��； 參考：《浙江大學》2016年博士論文

【摘要】：無線傳感器網(wǎng)絡是21世紀以來最重要的技術(shù)之一,其廣泛應用極大提高了人類認知和改造世界的能力。無線傳感器網(wǎng)絡有著分布式的特性,傳感器節(jié)點是網(wǎng)絡的基本單元,其計算、存儲和通信能力極其有限。如何合理調(diào)度節(jié)點資源,實現(xiàn)優(yōu)化配置,構(gòu)成功能強大的網(wǎng)絡,是傳感器管理的核心。本文將結(jié)合遠程網(wǎng)絡監(jiān)測系統(tǒng),研究傳感器的協(xié)同狀態(tài)估計和傳輸時序規(guī)劃,討論如何利用傳感器的局部通信,優(yōu)化測量信息的融合,實現(xiàn)本地狀態(tài)估計;以及如何規(guī)劃數(shù)據(jù)傳輸時序,確保遠程狀態(tài)估計滿足給定精度指標。遠程監(jiān)測系統(tǒng)中存在諸多監(jiān)測進程,集中式的處理方式涉及海量數(shù)據(jù)的傳輸,影響了系統(tǒng)的整體效率。本文研究相對感測網(wǎng)絡的分布式估計問題,以去除冗余信息、減少數(shù)據(jù)傳輸。網(wǎng)絡中所有節(jié)點都能測量其自身與鄰居所對應的進程之間的相對狀態(tài),錨定節(jié)點能額外測量進程的絕對狀態(tài)。本文利用雙向圖對網(wǎng)絡拓撲進行建模,通過構(gòu)造最優(yōu)估計器以論述連通圖是全局狀態(tài)估計的基礎條件,設計了兩種類似卡爾曼濾波器的次優(yōu)估計器和一種平均一致的次優(yōu)估計器,實現(xiàn)了進程全局狀態(tài)的傳感器本地估計。無線傳感器網(wǎng)絡的通信能力有限,為了避免通信沖突并降低系統(tǒng)能耗,本文研究了并行卡爾曼濾波器的時序規(guī)劃問題。在單信道通信限制條件下,規(guī)劃傳感器的傳輸序列,使所有進程在遠程中心的狀態(tài)估計時刻滿足給定精度。系統(tǒng)中,進程、傳感器和遠程估計器是一一對應的。本文定義并計算了實時傳輸截止期限,將基于協(xié)方差的時序規(guī)劃問題變?yōu)槿蝿障奁诎才艈栴};在此基礎上,設計了基于傳輸周期的離線規(guī)劃方法和基于滑動窗口的在線調(diào)整方法,以適應傳輸失敗和進程估計閾值的變化。系統(tǒng)中存在大量進程時,單信道通信不能保證數(shù)據(jù)及時傳輸。針對這一問題,本文研究了自適應的多信道傳輸規(guī)劃方法,在保障估計精度的同時減少信道占用數(shù)量。本文論證了一種準確計算進程傳輸周期的夾擠算法;為適應多信道傳輸,改進了一種基于緩存的離線規(guī)劃算法,并設計了相應的在線調(diào)整算法;多信道算法簡化了調(diào)整過程中的計算,提高了空閑信道利用效率,縮短了系統(tǒng)變動后的調(diào)整時間,更適應分布式網(wǎng)絡。對于提出的各種算法設計,本文在相應章節(jié)中給出了具體的理論分析,并通過仿真實驗進行了驗證。
[Abstract]:Wireless sensor network (WSN) is one of the most important technologies in the 21st century. Its wide application has greatly improved the ability of human beings to recognize and transform the world. Wireless sensor networks have distributed characteristics. Sensor nodes are the basic unit of the network, and their computing, storage and communication capabilities are extremely limited. It is the core of sensor management that how to reasonably schedule node resources, realize optimal configuration and form a powerful network. In this paper, based on the remote network monitoring system, the cooperative state estimation and transmission timing planning of sensors are studied, and how to use the local communication of sensors to optimize the fusion of measurement information to realize local state estimation is discussed. And how to plan the time series of data transmission to ensure that the remote state estimation meets the given precision index. There are many monitoring processes in the remote monitoring system. The centralized processing involves the transmission of massive data, which affects the overall efficiency of the system. In this paper, the distributed estimation problem of relative sensing network is studied to remove redundant information and reduce data transmission. All nodes in the network can measure the relative states between themselves and their neighbors, and anchoring nodes can measure the absolute states of the processes. In this paper, a bidirectional graph is used to model the network topology, and an optimal estimator is constructed to show that the connected graph is the basic condition of global state estimation. Two suboptimal estimators similar to Kalman filter and a suboptimal estimator with uniform average are designed to realize the local sensor estimation of the global state of the process. Wireless sensor networks have limited communication capability. In order to avoid communication conflicts and reduce system energy consumption, the parallel Kalman filter timing planning problem is studied in this paper. Under the condition of single channel communication limitation, the transmission sequence of sensors is planned so that all processes meet the given precision at the state estimation of remote center. In the system, processes, sensors and remote estimators are one-to-one correspondence. In this paper, the deadline for real-time transmission is defined and calculated, which turns the covariance-based time series programming problem into a task deadline scheduling problem. The off-line planning method based on transmission period and the on-line adjustment method based on sliding window are designed to adapt to the change of transmission failure and process estimation threshold. When there are a large number of processes in the system, single channel communication can not guarantee the timely transmission of data. To solve this problem, an adaptive multi-channel transmission planning method is proposed in this paper, which not only guarantees the estimation accuracy but also reduces the amount of channel occupancy. In this paper, an algorithm for accurately calculating the process transmission cycle is demonstrated, and an off-line planning algorithm based on cache is improved to adapt to multi-channel transmission, and the corresponding on-line adjustment algorithm is designed. Multi-channel algorithm simplifies the calculation in the adjustment process, improves the efficiency of idle channel utilization, shortens the adjusting time after system change, and is more suitable for distributed networks. For the various algorithms proposed in this paper, the specific theoretical analysis is given in the corresponding chapters, and verified by simulation experiments.
【學位授予單位】：浙江大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TP212.9;TN929.5

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本文編號：1851704