Parametric message passing-based relative navigation in joint tactical information distribution system

Relative navigation is a key feature in the joint tactical information distribution system（JTIDS）.A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First of all,the joint posterior distribution of all the terminals＇ positions is represented by factor graph.Because of the nonlinearity between the positions and time-of-arrival（TOA） measurement,messages cannot be obtained in closed forms by directly using the sum-product algorithm on factor graph.To this end,the Euclidean norm is approximated by Taylor expansion.Then,all the messages on the factor graph can be derived in Gaussian forms,which enables the terminals to transmit means and covariances.Finally,the impact of major error sources on the navigation performance are evaluated by Monte Carlo simulations,e.g.,range measurement noise,priors of position uncertainty and velocity noise.Results show that the proposed algorithm outperforms the extended Kalman filter and cooperative extended Kalman filter in both static and mobile scenarios of the JTIDS.

Topology and Position Aware Overlay Network Construction Protocol for Augmentation Information of Satellite Navigation System

It is an effective method to broadcast the augmentation information of satellite navigation system using GEO technology.However,it becomes difficult to receive GEO signal in some special situation,for example in cities or canyons,in which the signal will be sheltered by big buildings or mountains.In order to solve this problem,an Internet-based broadcast network has been proposed to utilize the infrastructure of the Internet to broadcast the augmentation information of satellite navigation system,which is based on application-layer multicast protocols.In this paper,a topology and position aware overlay network construction protocol is proposed to build the network for augmentation information of satellite navigation system.Simulation results show that the new algorithm is able to achieve better performance in terms of delay,depth and degree utilization.

Evaluating effectiveness of four-parameter compound tactons for conveying urban navigation information

To guide pedestrians to navigate in a strange city and reduce the cognitive overload suffered when walking, thermal change direction, vibration stimulation direction, intensity variation and body location are employed to construct four-parameter compound tactons.They are mapped to four different types of navigation message： route attribute, intersection type, distance and heading direction. One psychological experiment was conducted. The derived confusion matrices were used to investigate recognition rates and information transfer for compound tactons,and non-parameter tests were employed to analyze the effect of each parameter on the number of correct responses.Experimental results show that the overall identification rate for four-parameter tactons is 88.72% by using different tactile parameters,and 19.64 icons can be identified reliably in all 32 tactile icons according to the information transfer value. Thermal changes can be an effective supplement to vibrotactile icons. This suggests that compound tactons will be a promising method of conveying complex information when navigating in a virtual or real urban environment.

Production of High-Resolution Remote Sensing Images for Navigation Information Infrastructures

This paper introduces the image fusion approach of multi-resolutionanalysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral imagesfrom high-resolution panchromatic image and low-resolution multi-spectral images for navigationinformation infrastructure. The mathematical model of image fusion is derived according to theprinciple of remote sensing image formation. It shows that the pixel values of a high-resolutionmulti-spectral images are determined by the pixel values of the approximation of a high-resolutionpanchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixelvalae computation the M-band wavelet theory and the a trous algorithm are then used. In order toevaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 mpanchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusionapproach gives promising fusion results and it can be used to produce the high-resolution remotesensing images required for navigation information infrastructures.

Ship performance and navigation data compression and communication under autoencoder system architecture

Modern vessels are designed to collect,store and communicate large quantities of ship performance and navigation information through complex onboard data handling processes.That data should be transferred to shore based data centers for further analysis and storage.However,the associated transfer cost in large-scale data sets is a major challenge for the shipping industry,today.The same cost relates to the amount of data that are transferring through various communication networks(i.e.satellites and wireless networks),i.e.between vessels and shore based data centers.Hence,this study proposes to use an autoencoder system architecture(i.e.a deep learning approach)to compress ship performance and navigation parameters(i.e.reduce the number of parameters)and transfer through the respective communication networks as reduced data sets.The data compression is done under the linear version of an autoencoder that consists of principal component analysis(PCA),where the respective principal components(PCs)represent the structure of the data set.The compressed data set is expanded by the same data structure(i.e.an autoencoder system architecture)at the respective data center requiring further analyses and storage.A data set of ship performance and navigation parameters in a selected vessel is analyzed(i.e.data compression and expansion)through an autoencoder system architecture and the results are presented in this study.Furthermore,the respective input and output values of the autoencoder are also compared as statistical distributions and sample number series to evaluate its performance.