Optimization of Indoor Bluetooth Ranging Model Based on RSSI

Because the received signal strength indication (RSSI) ranging technology has problems with line-of-sight and multipath effects in indoor environments, the actual received RSSI value is unstable. In order to reduce the influence of RSSI value volatility on ranging accuracy, according to the fluctuation characteristics of the signal itself, a combined filtering method of Gaussian, median and mean is proposed to process the collected RSSI values, and the least squares method is used to fit and optimize the ranging parameter. Experiments show that using the RSSI intensity value processed by the combined filtering method to establish a model to achieve ranging, the maximum absolute error is about 2 m, and the absolute average error is about 0.763 m. The accuracy of the ranging has been significantly improved, and the ranging model has been optimized.

Research on the Monocular Ranging Method of the Leading Vehicle in Multi-weather

In order to improve the accuracy of the monocular distance measurement of the vehicle in front under sunny, cloudy, rainy, snowy, and foggy weather, an improved pixel-mapping monocular distance measurement method is proposed. This method is based on eight-connected domains to detect the front vehicle, obtain the line pixels of the target vehicle in the image, and fit the image line pixels to the corresponding real longitudinal distance function, and combine the fitted function with the internal and external parameters of the camera. An improved pixel-mapping monocular ranging model is obtained. Set up a test environment under different weather to verify the feasibility of the algorithm. The results show that in the four environments, the detectable distances are within 70m, 60m, 30m, and 40m respectively; the error of the improved pixel-mapping monocular ranging method is reduced by 0.6% on average compared with before the improvement, up to 0.92% ; The improved algorithm ranging errors under the four weathers are 1.8513%, 2.6987%, 4.0137%, and 2.5795% respectively, which achieves the purpose of improving the accuracy of the monocular distance measurement of the vehicle in front under multiple weather conditions.

Simultaneous Time-Varying Vibration and Nonlinearity Compensation for One-Period Triangular-FMCW Lidar Signal

Frequency modulation continuous wave (FMCW) Lidar inevitably suffers from vibration and nonlinear frequency modulation, which influences the ranging and imaging results. In this paper, we analyze the impact of vibration error coupled with nonlinearity error on ranging for FMCW Lidar, and propose a purely theoretical approach that simultaneously compensates for time-varying vibration and nonlinearity in one-period triangular FMCW (T-FMCW) signals. We first extract the localized characteristics of dechirp signals in time-frequency domain by using a second-order synchro-squeezing transform (second-order SST), and establish an instantaneous ranging model based on second-order SST which can characterize the local distributions of time-varying errors. Second, we estimate the nonlinearity error by using time-frequency information of an auxiliary channel and then preliminarily eliminate the error from the instantaneous measurement range. Finally, we construct a particle filtering (PF) model for T-FMCW using the instantaneous ranging model to compensate for the time-varying vibration error and the residual nonlinearity error, and calculate the range of target by using triangular symmetry relations of T-FMCW. Experimental tests prove that the proposed method can accurately estimate the range of target by compensating for the time-varying vibration and the nonlinearity errors simultaneously in one-period T-FMCW signal.

Towards an Integral Therapeutic Protocol for Breast Cancer Based upon the New H+-Centered Anticancer Paradigm of the Late Post-Warburg Era

A brand new approach to the understanding of breast cancer (BC) is urgently needed. In this contribution, the etiology, pathogenesis, and treatment of this disease is approached from the new pH-centric anticancer paradigm. Only this unitarian perspective, based upon the hydrogen ion (H+) dynamics of cancer, allows for the understanding and integration of the many dualisms, confusions, and paradoxes of the disease. The new H+-related, wide-ranging model can embrace, from a unique perspective, the many aspects of the disease and, at the same time, therapeutically interfere with most, if not all, of the hallmarks of cancer known to date. The pH-related armamentarium available for the treatment of BC reviewed here may be beneficial for all types and stages of the disease. In this vein, we have attempted a megasynthesis of traditional and new knowledge in the different areas of breast cancer research and treatment based upon the wide-ranging approach afforded by the hydrogen ion dynamics of cancer. The concerted utilization of the pH-related drugs that are available nowadays for the treatment of breast cancer is advanced.

Edmund Gibson’s 1695 Britannia and Late-Seventeenth-Century British Antiquarian Scholarship

Drawing on the evidence of correspondence and draft papers preserved primarily in the Bodleian Library, Oxford, this essay gives a detailed account of the genesis and editing of one of seventeenth-century British antiquarianism’s foremost works: the revised version of William Camden’s Britannia, published in 1695. It pays particular attention to Edmund Gibson’s role as editor of the project and demonstrates the diversity of kinds of antiquarian scholarship to be found within the book (showing that William Camden offered a wide-ranging model for antiquarian practice). The article then situates the Britannia within the context of the religio-political divisions provoked by the Glorious Revolution, showing how Edmund Gibson attempted to navigate those divisions. It concludes by assessing the 1695 Britannia’s place within the history of antiquarian scholarship.

Self-Adaptive Dynamic Ranging Model-Based Real-Time Hybrid Algorithm for Accurate Indoor Localization

The reliability of location information still maintains a crucial impact on restricting the development of location based services in indoor environment. However, in wireless local area network, received signal strength indicator (RSSI) is prone to be interfered by indoor complex environment, resulting in low accuracy and instability of real-time positioning. Here, the new self-adaptive dynamic ranging model-based real-time hybrid algorithm was proposed to realize accurate and undisturbed localization in indoor scenes. A self-adaptive dynamic ranging model was initially constructed to update the environmental parameters and correct the ranging values of mobile terminals in real time. Based on this model, a hybrid KNN algorithm and a hybrid Bayesian algorithm were severally presented. Location fingerprint database and real-time RSSI data of test points were then obtained through data acquisition. Finally, the acquired data was further used to verify the two hybrid algorithms proposed, and compared with the results of several conventional algorithms. As a result, the stability and accuracy of dual hybrid algorithms were better than those of the traditional ones. The range of average location error of both hybrid algorithms maintained 1.26-1.38 m, which was significantly lower than the error level of 2-5 m under the current WLAN environment. This newly proposed hybrid algorithm could effectively improve the stability and accuracy of indoor localization with real-time positioning algorithm, providing a promising solution for RSSI-based indoor positioning system.