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A new simulation and processing methodology based on open source tools to produce high fidelity synthetic aperture radar (SAR) simulations of ground vehicles of varying types, as well as analysis of an applied automatic target recognition (ATR) technique is presented in this Letter. This work is based around the RaySAR open‐source model and the outputs have been configured for both monostatic and bistatic geometries. Input CAD models of various military and civilian vehicles are used to produce the SAR imagery. This output imagery was then used to train a tiny you only look once convolutional neural network (CNN) classifier. The classification success of the CNN applied was showed to produce significantly accurate results and the whole pipeline of processing enabled rapid evaluation of potential ATR methods against targets of choice. [ABSTRACT FROM AUTHOR]

In this study, a framework to super resolve and recognise the long range captured iris polar images is proposed. The proposed framework consists of best frame selection algorithm, modified diamond search algorithm, Gaussian process regression (GPR) based and enhanced iterated back projection (EIBP)‐based super‐resolution approach, fuzzy entropy‐based feature selector and neural network (NN) classifier. The framework uses linear kernel co‐variance function in local patch‐based GPR and EIBP algorithms and it super resolves the iris images depending on the contents of the patches, without an external dataset. NN classifier classifies the iris images by using features extracted using discrete cosine transform domain based no‐reference image quality assessment model, Gray level co‐occurrence matrix, Hu seven moments and statistical features. The framework is tested using CASIA long range iris database by comparing and analysing the peak signal‐to‐noise ratio, structural similarity index matrix and visual information fidelity in pixel domain of proposed algorithms with Yang and Nguyen framework. The results demonstrate that the proposed framework is well suited for recognition of iris images captured at a long distance. [ABSTRACT FROM AUTHOR]

A method to infer the terrain of unobserved fields as well as navigation paths using vibrations from vehicle–terrain interactions is presented. The relationships between adjacent terrain grids and robot paths are modelled by Markov random field (MRF) for inferring the classes of unobserved field. In order to approximate the complex likelihood of vibration features as a tractable distribution, a variational auto‐encoder is adopted. By projecting intractable features to the latent space, an approximated likelihood that gives similar performance to a neural network classifier is obtained. Then the numerical maximum a posterior inference for MRF is obtained. The result of inferred terrain maps are compared with that from the feature likelihood as a Gaussian‐mixture model. [ABSTRACT FROM AUTHOR]

For a class of discrete‐time multi‐variable systems with time‐varying parametric uncertainty, the parameter identification method and switching control architecture are developed in this study to implement smooth switching control. Specifically, the identification algorithm based on the least geometric mean squares is derived for the multi‐variable system. In addition, the switching control system, with model reference control technique as the basis of control design for each local model, is proposed to achieve satisfactory control performance, especially to eliminate the oscillations at the switching boundaries which can be attributed to the difference in the input–output dynamics between the pre‐ and post‐switching closed‐loop subsystems. Furthermore, the switching strategy based on neural network classifier is put forward for the accurate switching among a set of model reference controllers which are correspondingly designed for the identified subsystems. Finally, the feasibility and effectiveness of the proposed identification and control schemes are verified by numerical simulations, which show that the desirable identification and control performances are guaranteed under the proposed schemes. Moreover, the advantage of the presented switching control system in terms of smooth switching is validated through comparison with other kinds of control schemes. [ABSTRACT FROM AUTHOR]