Disorder Information Network Integration And Ship Integrated Navigation

Multisensor fusion system based on Wireless Sensor Networks (WSN) will suffer many network constraints when it is collecting and processing the information from local sensors, such as limited communication bandwidth and energy, limited storage and computation of network nodes, dynamic network topology and routing protocol and so on. Accordingly, the traditional information fusion theory and technologies can not be satisfied with the increasing practical engineering requirement. Synchronously, multisensor information fusion based on WSN, for short network fusion, must be faced with many new difficult problems and challenges.The corporate effect of the network constraints is that the properties of cause and effect, constant and sequence are easily destroyed. If the package drop is considered to unlimited delay, the effect to the fusion system from the network constraints jointly results in the random delay of local sensor information. And the randomicity of transmission delay must make that the local information sampled orderly arrive in the fusion center out-of-sequence, namely the latter information may arrive earlier and the earlier information arrive latter, and it is called to Out-Of-Sequence Information (OOSI). Consequently, the final result is that the traditional information fusion based on ordered information can not be used effectively for the OOSI case and the OOSI estimate fusion algorithm design has been one of the most important researches in the network fusion. At present, the "Out-of- Sequence" Measurements update method named as OOSM, which is advocated by Y. Bar-Shalom etc., only solved the partial OOSI estimate fusion cases. Thereby, because it is primary phase for the research of OOSM method and possesses many insuperable shortcomings induced by its centralized fusion character, it makes that plentiful key academic and technical issues should be further researched.Currently, the research for the shipping safety is paid more attention and one of the main contents is to monitor the shipping and provide the early warning for active collision avoidance and other marine dangers. Then the principal key issue to realize above functions is the more accurate and reliable navigation and positioning for ships. The traditional ship integrated navigation positioning methods are mostly to fuse optimally the information from the navigation subsystems on the ships. Accordingly, many problems, for example the information heterogeneous and uncertainty characteristics, the system networks property and excessive dependency for GPS, make the implementation and reliability of the traditional integrated navigation positioning methods in the practical systems reduced. In fact, marine shipping network system is a scale wireless Ad hoc sensor network and each network node communicates each other by multihop and broadcasting matter and the result is that each ship in the network can receive the other ship's information. So, the accuracy and reliability of the traditional integrated navigation positioning methods for ship node can be improved by effectively fusing the positioning information from other ships. Because the navigation system of each marine ship works asynchronously and the communication between two ships is often finished by the wireless network, additionally the slipway's information transmission by short message and the delayed total data alignment for ship AIS equipment can not finish some data transmission during the stated time, they can result in the uncertain delay for the information communication between random two ships. Therefore, the key to realize above function is to effectively use other ship's information to improve the navigation positioning estimate of target ship node in the marine shipping network.So, it has important theoretic significance and extensive application foreground to develop the research of network fusion based on OOSI and its application in the ship integrated navigation. In the view of this, the dissertation lays stress on the research for the design of OOSI network fusion algorithms and the ship integrated navigation method under the marine shipping network, and its main contributions and innovations are listed as follows:1) Establish the relatively perfect OOSM estimate fusion frame for multisensor asynchronous sampling system. Aiming at the limitation for the current OOSM update achievements, by use of the pseudo-measurement and the traditional Kalman filtering based on noise correlation, it roundly develops the design of out-of-sequence measurements estimate fusion algorithms for the single sensor system, multisensor synchronous system and a kind of asynchronous sampling system with random delay. Sequentially, one universal frame of OOSM fusion algorithms is established.2) The "Out-Of-Sequence" Estimates (OOSE) method is proposed to treat with OOSI estimate fusion. In view of many insurmountable shortcomings existed in the OOSM produced by its centralized fusion property, the OOSE method is presented to solve these OOSM shortcomings under the distributed fusion frame. Ultimately, a unified OOSE fusion frame for general asynchronous sampling system with random delay is finished. Synchronously, the combination of OOSM and OOSE is discussed deeply for a kind of special asynchronous sampling system with tree form. This research accords with the idea that the traditional centralized and distributed fusion methods can be jointly used.3) The novel ship relative navigation positioning method is presented by introducing the network fusion theory. For the characters of information abundance in the marine shipping network and the uncertainty of ship integrated navigation positioning subsystem, we presents to use other ship's information to improve the accuracy, stability and reliably of the active integrated navigation positioning estimate of target ship. Synchronously, the established OOSM and OOSE methods are both applied to deal with the relative navigation positioning of ship network node with transmission delay.