網(wǎng)絡(luò)式海洋聲學(xué)層析動力學(xué)狀態(tài)—空間建模與處理
發(fā)布時間：2018-08-20 12:12
【摘要】：海洋內(nèi)部存在著復(fù)雜的運動與變化。了解海水運動的變化規(guī)律對開發(fā)和利用海洋具有重要意義。這需要對海洋進行大面積、長時間的觀測。動力環(huán)境(如溫度場、流場的分布)作為海洋環(huán)境的重要組成部分,其有效測量技術(shù)一直受到關(guān)注。聲波是水下遙測的重要手段，，利用海洋聲學(xué)技術(shù)可以實現(xiàn)大范圍、長時序、動態(tài)、實時的監(jiān)測。由于海洋參數(shù)存在一定的動力學(xué)特征,采用序貫濾波思想跟蹤參數(shù)的變化是一種自然的選擇，而如何建立準(zhǔn)確、自適應(yīng)的參數(shù)演化模型成為問題的關(guān)鍵。因此，論文以二維流速場的序貫跟蹤為例,在分布式水聲網(wǎng)絡(luò)架構(gòu)下,探討海洋環(huán)境測量的狀態(tài)一空間動力學(xué)建模和信號處理。海洋聲學(xué)層析(Ocean Acoustic Tomography,簡稱OAT)技術(shù)從精確測量的聲傳播時間或者其他聲傳播屬性推斷聲場所穿過的海洋狀態(tài),一般采用分布于觀測區(qū)域周邊的若干發(fā)射／接收節(jié)點,適合于觀測區(qū)域內(nèi)部中小尺度過程。沿岸聲學(xué)層析(Coastal Acoustic Tomography,簡稱CAT)作為OAT的一個特例，用于監(jiān)測半封閉海域的聲速或流速的空間分布。由于流速在一定尺度的空間與時間上存在相關(guān)性,論文提出了基于空時演化模型的CAT跟蹤方法,將空間網(wǎng)格流速狀態(tài)的演化方程建模為空時AR模型,且AR系數(shù)根據(jù)狀態(tài)估計值自適應(yīng)更新。研究結(jié)果表明,基于空時演化的CAT跟蹤方法能夠有效抑制測量的抖動誤差。海洋環(huán)境監(jiān)測面臨著分辨力與工作距離、空時尺度與資源之間的矛盾,水聲傳感網(wǎng)絡(luò)(Underwater Acoustic Sensor Network,簡稱UASN)為解決上述矛盾提供了新的思路.UASN由大量分布于觀測區(qū)域內(nèi)部的低功耗小型傳感節(jié)點組成,通過節(jié)點密度獲取分辨力,通過節(jié)點分布獲取覆蓋范圍,通過節(jié)點之間的通信實現(xiàn)協(xié)同工作。UASN參數(shù)場估計可以看作是OAT技術(shù)在分布式網(wǎng)絡(luò)框架下的一種實現(xiàn),我們將應(yīng)用于聲層析問題的UASN稱為分布式聲學(xué)層析網(wǎng)絡(luò)(Distributed Acoustic Tomography Network,簡稱DATN).論文提出一種基于三角形網(wǎng)格離散化的流速場空時跟蹤方法,依據(jù)節(jié)點拓?fù)鋵^(qū)域進行子三角形劃分,以子三角形的流速作為研究對象,根據(jù)距離對子三角形進行分類,距離相近的子三角形屬于同一階,AR系數(shù)相同,將子三角形的流速變化建模為空時AR過程。研究結(jié)果表明,所提出的空時跟蹤方法可提高估計性能,并且在應(yīng)對諸如鏈路失效、突發(fā)誤差等DATN的實際問題時具備較強的寬容性。水下通信資源的限制使得基于DATN的流速場估計的數(shù)據(jù)融合過程頗具挑戰(zhàn)性。分布式處理在相鄰節(jié)點間進行信息交換,處理過程在每個節(jié)點內(nèi)部進行，使估計過程不依賴于任何一個中心,具備較強的環(huán)境寬容性和可擴展性。結(jié)合基于DATN的流速場估計問題的特點,論文提出基于一致新息的分布式流速場估計方法。該方法從Kalman濾波的信息表示形式入手,對平均偽測量向量進行一致新息處理,局部測量值提供新息,節(jié)點之間的信息交換達(dá)成估計一致化。為了提高分布式估計的收斂速度,論文還提出一種基于路徑選擇的一致化加權(quán)矩陣構(gòu)造方法,并給出了所提出的分布式估計方法的無偏性和收斂性證明。研究結(jié)果表明,所提出的分布式流速場估計方法能達(dá)到局部流場估計的一致,且通信量小,收斂速度快,適用于水下高延遲通信環(huán)境。論文的理論與方法通過仿真或?qū)嶒炦M行了驗證。論文的研究工作進一步豐富了OAT技術(shù),通過利用流速場的空時相關(guān)性提高估計精度;發(fā)展了基于DATN的參數(shù)估計方法,為實現(xiàn)大范圍、高分辨流場測量提供新的途徑;同時創(chuàng)新發(fā)展了基于聲學(xué)層析網(wǎng)絡(luò)的分布式估計方法，為水聲傳感網(wǎng)絡(luò)在海洋環(huán)境監(jiān)測中的應(yīng)用奠定理論基礎(chǔ)。
[Abstract]:Understanding the law of sea water movement is of great significance to the development and utilization of the ocean, which requires large-scale and long-term observation of the ocean. Acoustic wave is an important means of underwater telemetry, which can be monitored in a wide range, long time series, dynamic and real-time by using ocean acoustic technology. Because of the dynamic characteristics of ocean parameters, it is a natural choice to track the changes of ocean parameters by using sequential filtering. How to establish an accurate and adaptive parameter evolution model becomes a problem. Therefore, the state-space dynamic modeling and signal processing of ocean environment measurement are discussed in this paper. Ocean Acoustic Tomography (OAT) technique is used to deduce the acoustic propagation time or other acoustic propagation properties from precise measurements. Coastal Acoustic Tomography (CAT), as a special case of OAT, is used to monitor the spatial distribution of sound velocity or current velocity in semi-enclosed sea area. In this paper, a method of CAT tracking based on space-time evolution model is proposed. The evolution equation of velocity state in space grid is modeled as space-time AR model, and the AR coefficient is updated adaptively according to the state estimation. Underwater Acoustic Sensor Network (UASN) provides a new way to solve the above contradiction. UASN consists of a large number of small sensor nodes with low power consumption distributed in the observation area. UASN parameter field estimation can be seen as an implementation of OAT technology in a distributed network framework. We will apply UASN to acoustic tomography problems called Distributed Acoustic Network (DAT). A space-time tracking method of velocity field based on triangular mesh discretization is proposed in this paper. The region is divided into sub-triangles according to node topology. The sub-triangles are classified according to the velocity of sub-triangles. The sub-triangles with similar distances belong to the same order and AR coefficients are phase. Similarly, the velocity variation of the sub-triangle is modeled as a space-time AR process. The results show that the proposed space-time tracking method can improve the estimation performance and is more tolerant in dealing with practical DATN problems such as link failure and burst error. The combination process is challenging. Distributed processing exchanges information between adjacent nodes and processes within each node, so that the estimation process does not depend on any one center and has strong environmental tolerance and scalability. In order to improve the convergence speed of distributed estimation, this paper also proposes a uniform method based on path selection. The results show that the proposed distributed velocity field estimation method can reach the agreement of the local flow field estimation, and has the advantages of small traffic and fast convergence speed. It is suitable for the underwater high-delay communication environment. The research work of this paper further enriches the OAT technology and improves the estimation accuracy by utilizing the spatial-temporal correlation of velocity field; develops the parameter estimation method based on DATN, which provides a new way to realize large-scale and high-resolution flow measurement; and innovates and develops the distributed estimation based on acoustic tomography network. The method lays a theoretical foundation for the application of underwater acoustic sensor network in marine environmental monitoring.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：P733.2
本文編號：2193568
[Abstract]:Understanding the law of sea water movement is of great significance to the development and utilization of the ocean, which requires large-scale and long-term observation of the ocean. Acoustic wave is an important means of underwater telemetry, which can be monitored in a wide range, long time series, dynamic and real-time by using ocean acoustic technology. Because of the dynamic characteristics of ocean parameters, it is a natural choice to track the changes of ocean parameters by using sequential filtering. How to establish an accurate and adaptive parameter evolution model becomes a problem. Therefore, the state-space dynamic modeling and signal processing of ocean environment measurement are discussed in this paper. Ocean Acoustic Tomography (OAT) technique is used to deduce the acoustic propagation time or other acoustic propagation properties from precise measurements. Coastal Acoustic Tomography (CAT), as a special case of OAT, is used to monitor the spatial distribution of sound velocity or current velocity in semi-enclosed sea area. In this paper, a method of CAT tracking based on space-time evolution model is proposed. The evolution equation of velocity state in space grid is modeled as space-time AR model, and the AR coefficient is updated adaptively according to the state estimation. Underwater Acoustic Sensor Network (UASN) provides a new way to solve the above contradiction. UASN consists of a large number of small sensor nodes with low power consumption distributed in the observation area. UASN parameter field estimation can be seen as an implementation of OAT technology in a distributed network framework. We will apply UASN to acoustic tomography problems called Distributed Acoustic Network (DAT). A space-time tracking method of velocity field based on triangular mesh discretization is proposed in this paper. The region is divided into sub-triangles according to node topology. The sub-triangles are classified according to the velocity of sub-triangles. The sub-triangles with similar distances belong to the same order and AR coefficients are phase. Similarly, the velocity variation of the sub-triangle is modeled as a space-time AR process. The results show that the proposed space-time tracking method can improve the estimation performance and is more tolerant in dealing with practical DATN problems such as link failure and burst error. The combination process is challenging. Distributed processing exchanges information between adjacent nodes and processes within each node, so that the estimation process does not depend on any one center and has strong environmental tolerance and scalability. In order to improve the convergence speed of distributed estimation, this paper also proposes a uniform method based on path selection. The results show that the proposed distributed velocity field estimation method can reach the agreement of the local flow field estimation, and has the advantages of small traffic and fast convergence speed. It is suitable for the underwater high-delay communication environment. The research work of this paper further enriches the OAT technology and improves the estimation accuracy by utilizing the spatial-temporal correlation of velocity field; develops the parameter estimation method based on DATN, which provides a new way to realize large-scale and high-resolution flow measurement; and innovates and develops the distributed estimation based on acoustic tomography network. The method lays a theoretical foundation for the application of underwater acoustic sensor network in marine environmental monitoring.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：P733.2
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