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Item type:Item, Access status: Open Access , UWB Indoor Localization Based on XGBoost NLOS Identification and DS-TWR Ranging(Radioengineering Society, 2026-06) Xu, X. Yao Z.; Liu, G.Indoor environments present significant challenges for ultra-wideband (UWB) localization due to ranging errors and non-line-of-sight (NLOS) propagation. This paper proposes a robust UWB indoor localization framework that integrates double-sided two-way ranging (DS-TWR), XGBoost-based NLOS identification, residual-weighted localization, and Kalman filter (KF). The main contribution of this work is the unified use of NLOS identification in both ranging correction and localization fusion, significantly improving localization accuracy in complex environments. Experimental results demonstrate improvements in ranging accuracy of up to 53.7% and 47.22% under human-body and wooden-board occlusions. In dynamic experiments, the proposed method outperforms conventional UWB localization, KF, and weighted least squares methods with positioning accuracy improvements of 38.64%, 28.95%, and 12.9%, respectively. These results confirm the framework’s effectiveness in mitigating NLOS impact and enhancing UWB localization robustness.Item type:Item, Access status: Open Access , Mid-Air Hand Rehabilitation Evaluation and Virtual Training System(Radioengineering Society, 2026-06) Zhou, R.; Lai, P.; Chen, L.; Hu, Z.; Qian, L.This paper presents the design of a mid-air hand rehabilitation evaluation and virtual training system based on Leap Motion and gesture recognition algorithms. The system aims to provide a scientifically-grounded and accessible home-based rehabilitation solution for patients with hand injuries. It employs a spatio-temporal attention-enhanced multi-scale residual graph convolutional network algorithm for gesture recognition. Following this, specific joint angles are calculated and 14 representative gesture scores are derived. Weights are assigned to each scoring item via ridge regression to achieve a quantitative assessment. The rehabilitation training module comprises two modes: interactive turn-based games and music rhythm games, designed to train hand movement and dexterity. The system was subsequently tested to evaluate the performance of both the assessment function and the two training games. Results show an average gesture recognition accuracy of 94.86%. Furthermore, the reliability scores for both training games exceeded 90%. These findings demonstrate that the system achieves good accuracy in gesture recognition and effective assessment of hand rehabilitation progress.Item type:Item, Access status: Open Access , DSSZ-SM: A Simplified Chirp Coding Scheme with Inherent Clock Synchronization(Radioengineering Society, 2026-06) Kirasamuthranon, L.; Koseeyaporn, J.; Wardkein, P.This study proposes a novel double-slope chirp symbol, termed double–slope start zero stop minimum (DSSZ–SM), for efficient data communication. Unlike conventional chirp coding, which often involves complex generation and synchronization, the DSSZ–SM provides a simpler structure with inherent clock synchronization using a PWM-based generator. System performance is evaluated through analysis and simulations over additive white Gaussian noise (AWGN) and Rayleigh fading channels. Two asynchronous decoding methods, with and without an integrator, are compared. Results show that the non-integrator approach achieves lower error rates under both channel conditions. The proposed DSSZ–SM offers a simplified and robust alternative for efficient data communication.Item type:Item, Access status: Open Access , Study on the Influence of Channel’s Non-Ideal Characteristic on Pseudo-Code Measurement Bias for GNSS Receiver(Radioengineering Society, 2026-06) Wang, Y. D.; Fan, X.; Lu, M. M.GNSS has been widely used in civilian and military areas due to its high precision. However, the channel’s non-ideal characteristic may introduce pseudo-code measurement bias to degrade positioning precision. There are few theoretical analyses for interpreting why the channel’s non-ideal characteristic may introduce pseudo-code measurement bias and what kind of channels will not introduce pseudo-code measurement bias. We have conducted a systematical study on the above issues. Firstly, we established an analysis model for interpreting the channel’ non-ideal characteristic’s influence on pseudo-code measurement bias. Based on the analysis model, we proposed four sufficient conditions for unbiased pseudo-code measurement. Secondly, we applied the analysis model to typical channels, i.e. sine type group delay channel, frequency-domain anti-jamming channel and space-domain anti-jamming channel, to evaluate the channel’s influence on pseudo-code measurement bias. Finally, we conducted simulations to evaluate the theoretical analysis’ correctness. Results show that these typical channels do not introduce pseudo-code measurement bias, which are consistent with theoretical analysis. As a result, the correctness of the proposed four sufficient conditions is verified so that the proposed four sufficient conditions can be used to guide the design of unbiased pseudo-code measurement channel.Item type:Item, Access status: Open Access , Ternary Data Categorization for Evaluating the Impact of Data Transforms on Image Compressibility(Radioengineering Society, 2026-04) Samofalov, A.; Polak, L.In our increasingly digital world, data compression remains an important research topic. One way to improve the compression ratio is to use data transform techniques to increase further compressibility of input data for specific compression algorithms. This paper introduces a novel ternary data categorization in order to evaluate the impact of data transform techniques on input data. The categorization is described and explained in detail. Then, three transforms used for testing are described: Burrows-Wheeler and Move-to-Front transforms (BWT and MTF), as well as shifting summation. These transforms are applied to the eight true color images from the Kodak and Kaggle image sets. The findings derived from the ternary graphs and statistical measures indicate that combining BWT and MTF transforms yields the best results for this test on the selected image data. The shifting summation approach opens up possibilities for further research, particularly in searching for data patterns.