RD Algorithm Research Articles

Improved ISAL Imaging Based on RD Algorithm and Image Translation Network Cascade

Improved ISAL Imaging Based on RD Algorithm and Image Translation Network Cascade

Гибридная модель эффективного представления данных в беспроводных транспортных сетях с динамической топологией VANET

At the moment, traffic information systems require the aggregation of big data to provide recommendations to vehicles in the current conditions, which leads to an increase in user comfort. The main tool for improving the level of safety was timely informing traffic participants about the current situation on the road, weather conditions, etc. In this case, if the network object is subjected to an attack and the data is replaced during transmission, then the disclosure of confidential information, the creation of emergency si¬tuations, etc. is possible throughout the visibility zone of the VANET segment. In this regard, the most urgent issue is ensuring security, including when transmitting traffic, and conducting an additional analysis of big data about anomalies and ongoing unauthorized actions. Aim. To develop a hybrid model for the efficient placement of source and intermediate data in wireless transport networks with a dynamic VANET topology, which represents a structural representation of a software-configurable network and edge computing tools, with the ability to optimally analyze data from network nodes and identify anomalies. Methods. The considered Edge computing approach consists in locating computing capacities in geogra¬phically distributed computing devices closer to end users. Software-configurable SDN networks transfer part of the control and physical transmission functions from routing and switches, reducing the load. Within the framework of this study, an RD algorithm has been developed – a protocol for transmitting and processing intermediate data. To carry out clustering of vehicles on a network segment, the DBSCAN unsupervised learning method was used. Preliminary analysis of abnormal traffic was carried out on the basis of RNN neural network models with short-term memory. Results. The developed hybrid model of efficient placement of initial and intermediate data makes it possible to react faster to unauthorized actions. Conclusion. The results obtained in the course of the study confirm the need to implement and scale a hybrid model with boundary calculations in practice.

Review and analysis for the Red Deer Algorithm.

In this paper, the Red Deer algorithm (RDA), a recent population-based meta-heuristic algorithm, is thoroughly reviewed. The RD algorithm combines the survival of the fittest principle from the evolutionary algorithms and the productivity and richness of heuristic search techniques. Different variants and hybrids of this algorithm are presented and investigated. All the applications that were solved with this algorithm are presented. It is crucial to analyze the performance of this algorithm, therefore, the paper sheds light on the algorithm unique features and weaknesses covering the applications that are primarily suitable for it. The conclusions are presented, and further recommendations are suggested based on the review and analysis covered. The readers of this paper will have an understanding of the RD algorithm and its variants and, consequently, decide how suitable this algorithm is for their own business, research, or industrial applications.

An Improved RD Algorithm for Maneuvering Bistatic Forward-Looking SAR Imaging with a Fixed Transmitter.

In order to improve the azimuth resolution beyond what monostatic synthetic aperture radar (SAR) can achieve in the forward-looking area, an asymmetric configuration bistatic SAR system and its imaging algorithm are proposed in this paper. The transmitter is mounted on a fixed platform in side-looking mode while the receiver moves along a nonlinear trajectory in forward-looking mode. Due to the high velocity and acceleration of the maneuvering platform in both along-track and height direction, the traditional algorithms are no longer applicable. In this paper, a new algorithm based on the high precise 2-D frequency spectrum is proposed, which takes high-order Taylor series expansion terms of the slant range into consideration. The proposed algorithm compensates high-order range-azimuth coupling terms to guarantee the focus accuracy in SAR imaging. The simulation results and error analysis validate the effectiveness of the proposed algorithm and the correctness of our analysis.

The Evaluation and Contrast of SAR Noise Jamming Effect Based on the RD and CS Algorithm

该文针对RD与CS两种成像算法的差异，首先分析了两种算法在压制性噪声干扰环境下信号与噪声干扰的成像处理增益，推导出两种算法的信号-干扰功率比(信干比)处理增益公式并进行了分析。理论分析结果表明，在采样率仅略大于信号带宽条件下，RD和CS成像算法的信干比处理增益基本一致；在过采样条件下，RD算法由于两维匹配处理从而获得比CS算法大的信干比处理增益，但如果对过采样信号进行滤波处理后，CS算法的信干比处理增益与RD算法一致。最后，采用对计算机仿真数据和真实数据进行处理的方法验证了该文的理论分析和结论。

Surface-Tracing-Based LASAR 3-D Imaging Method via Multiresolution Approximation

This paper concerns the surface-tracing-based (STB) linear-array synthetic-aperture-radar (LASAR) 3-D imaging technique. The basic idea of this technique is to consider the 3-D SAR imaging problem as tracing a surface in the low height-resolution level. The STB 3-D imaging technique first initiates a low-resolution digital elevation map (DEM) using 3-D backprojection (BP) algorithm, predicts a higher resolution DEM from the known elevation using multivariate-interpolation technique, searches from the predicted elevation and obtains a higher resolution DEM, then repeats the prediction and searching recursively and obtains the fine-resolution DEM finally. By converting the 3-D LASAR imaging problem to a 2-D surface-tracing problem, the STB 3-D imaging technique can reduce the computational complexity by one order. The computational cost of STB 3-D imaging technique is analyzed, and we find out that the computational cost of STB 3-D LASAR imaging technique is determined by the surface prediction error and the fluctuation of ground. In particular, for normal distribution, when one of the earlier two factors is small, the computational cost is proportional to the other factor approximately. Finally, a new STB 3-D BP algorithm that implements the surface-prediction operation via multiresolution-approximation (MRA) technique (named as MRA 3-D BP algorithm) is presented. By operating the interpolation in frequency domain, the computational cost of MRA algorithm for sparse LASAR is near to that of RD algorithm for full-element LASAR.