Radar signals class recognition algorithm synthesis

This paper presents the algorithm of multiple-unit target acquisition against the structurally similar interference and analysis method of its efficiency. Synthesized aperture antenna pattern in some practical situations along with the valid signal reflected from the multiple-unit target has rather powerful interfering signals produced by the reflections from the interfering objects. The algorithm of multiple-unit target acquisition against the multipleunit interference and analysis method of its efficiency have been presented.

Section: Concept Headingsmentioning

confidence: 99%

Signal Detection in Sar Against the Clutter Reflections Background

Dorosinskiy¹

2016

“…Among the tasks of radio astronomy and the remote sensing of the surface, the key role is fulfilled by the optimal or close to the processing of received data with the target of the efficient problem solution realization of the recognition of the observable signal class. The efficient problem solution of the class recognition [1], [2], [3], [4] may be received within the classical theory of multiple-choice check of the statistical hypotheses. According to one of them the vector of received fluctuationsŪ (t) is generated only by noise.…”

Section: Introductionmentioning

confidence: 99%

Synthesis and Analysis of Radar Signal Classification Algorithms

Dorosinskiy¹

2016

In the process of solving a wide range of tasks concerning the Earth surface remote sensing and its state monitoring, the main role is played by the algorithm of the surface image forming and the algorithm of images and their fragments classification as well. From the statistical point of view the solution is based on the maximum-likelihood method. The paper presents analytical equations for likelihood coefficients and the structural scheme of their forming in the solution of radar signal recognition. To analyze the efficiency of the proposed algorithms are found boundary equations for probability calculating of correct signals with the usage of Chernoff-Kailath ratios. This ratios evaluate the upper and lower probability boundaries of correct and incorrect decisions in the case of classification of optional class number from different type surfaces.

“…for all possible boarders between M areas and to select a configuration having the maximum value of eqn (1). Straightforward implementation of this algorithm is impractical due to its enormous computation complexity.…”

Section: Optimal Solutionmentioning

confidence: 99%

“…Along with synthesis of contour recognition algorithms, their analysis is also of large importance. Parameters to be evaluated are: the minimal difference in normalized effective echoing areas, which enables boundaries recognition in low-contrast radar images; influence of a priori uncertainty of surface properties on precision of boundaries recognition [1]. Synthesis of computation-efficient quasi-optimal algorithms and research of their relation to the optimal algorithms also has a big practical value.…”

Section: Introductionmentioning

confidence: 99%

An Algorithm of Boundaries Detection in Low-Contrast Radar Images of the Earth

Dorosinskiy¹,

Lysenko²

2016

Abstract:One of the problems of radar images analysis of the Earth is the detection of boarders between areas with different normalized effective radar cross-sections. In this paper, we propose a computationally effective quasi-optimal algorithm capable for building approximation of such boarders with straight line segments for low-contrast radar images and arbitrary line for high-contrast radar images. To achieve computational efficiency we apply image segmentation and later approximation. Efficiency of the proposed algorithm was examined on a number of computer generated radar image fragments including lowcontrast radar images. Proposed algorithm can be effectively implemented using modern parallel computation systems.