Abstract
To ensure the effective functioning of the correlation-extreme navigation systems (CENSs), a method is developed to localize a reference object (RO) in a current image (CI) with several bright objects. The peculiarity of the method consists in converting the CI to a binary unit by determining the average value of the background and setting it for the threshold of the image quantization, which in turn determines the amount of probabilities of errors of the first and second kinds as well as entails assigning the objects of the viewing surface (VS) and the backgrounds to two classes: the RO and the background. The CI model is represented by the brightness values of the corresponding objects and backgrounds of the VS in the differentiation elements. In the model of the current image, the RO has the highest brightness. Other objects that are similar in brightness and commensurate with the RO are categorized as false. The reference image (RI) is set by the contrast mark and the geometrical shape of the object, and it is binary. An algorism has been developed for localizing the RO in an image by searching for a fragment of a binary CI with a maximum value of units that coincides with the RI. The peculiarity of the algorithm consists in adapting the application procedure for the threshold conversion of a CI with an unknown value of the signal-noise ratio. A method has been developed to clarify the maximum value of the DF and to determine the coordinates of the RO in the field of the CI matrix. The method consists in the summation of the number of units of different sections and finding the highest value of the DF. The highest value of the DF coincides with the full match between the CI and the RI. An analytical expression has been obtained for the estimation of the probability of localizing the RO. The expression establishes dependence of the probability of localizing the RO on the parameters that are specified in the stages of solving the problem of localizing the RO, which are the identification, the multi-threshold selection, and the specification of the maximum DF. By modeling the process of forming the DF, numerical estimates have been obtained for the probability of localizing the RO. The research results indicate the feasibility of using the proposed method in a CENS in relation to a VS with several bright objects.
Highlights
Correlation-extreme navigation systems (CENSs) of aircraft are auxiliary navigation systems
The errors found by comparing the current image (CI) and the reference image (RI) to locate the sought-for object are used to correct the errors of the inertial navigation system that accumulate during the flight of the aircraft
Despite the actively conducted studies to develop methods for the formation of a unimodal decision function (DF), it is not known how to solve the problem of localizing ROs in current viewing surface (VS) images with high object density when several objects that are close in brightness and shape to the reference object are present in the image
Summary
Correlation-extreme navigation systems (CENSs) of aircraft are auxiliary navigation systems. They are designed to correct (snap) the trajectory of an aircraft in preliminarily selected points. The accuracy of determining the coordinates of the groundbased reference objects, which are the navigation reference points, does not always correspond to what is required. This happens due to the ambiguity in detecting and selecting the reference object (RO) under conditions of high object density and, as a consequence, the inability to form a unimodal decision function (DF) of the aircraft control crew. The need to take into account the above factors further emphasizes the relevance of research to develop methods for the formation of a unimodal DF system
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