Measurement and Analysis of RSS Using Bluetooth Mesh Network for Localization Applications

Bluetooth low energy (BLE)-based location service technology has become one of the fastest growing applications for Bluetooth. Received signal strength (RSS) is often used in localization techniques for ranging or location fingerprinting. However, RSS-based localization solutions have poor performance in multipath environments. In this paper, we present a measurement system designed using multiple ESP32 BLE modules and the Bluetooth mesh networking technology, which is capable of exploiting the space, time, and frequency diversities in measurements. To enable channel-aware multi-device RSS measurements, we also designed a communication protocol to associate channel ID information to advertising messages. Based on channel measurement and analysis, we demonstrate that with a six-receiver configuration and space-time-frequency diversity combining, we can significantly reduce the residual linear regression fitting errors in path loss models. Such a reduction leads to more accurately correlating RSS measurements to the distance between the transmitter and receiver devices and thus to achieving improved performance with the RSS-based localization techniques. More importantly, the reduction in the fitting errors is achieved without differentiating the three advertising channels, making it possible to conveniently implement the proposed six-receiver configuration using commercially available BLE devices and the standard Bluetooth mesh networking protocol stack.

Frequency Diversity Gain of a Wideband Radar Signal

Wideband radar has high-range directional resolution, which can effectively reduce the fluctuation of echo and improve the detection probability of a target under the same detection probability requirement. In this paper, a unified wideband radar χ2 distribution target model with more practical significance is innovatively established, on which the probability density function and detection probability function of Swerling 0, Swerling II and Swerling IV targets are analyzed, respectively. A generalized “frequency diversity gain” of wideband radar is proposed and defined based on the contradiction between suppression of fluctuation and accumulation loss, which represents the ratio of Signal-to-Noise Ratio (SNR) gain between broadband signal and reference bandwidth signal under the same condition (when the reference bandwidth is used, the radar target has only one range unit), and the mathematical relation equation of the target detection performance and signal bandwidth (equivalent to the number of distinguishable range elements of the target) is given. A Monte Carlo simulation experiment is designed. Based on the target model established in this paper, the optimal number of target range units corresponding to different detection probability requirements is obtained, which verifies the correctness of the concept proposed in this paper.

Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach

An innovative inverse scattering (IS) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (GPR) data by jointly processing the multi-frequency (MF) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian compressive sensing (MT-BCS) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed MF-MT-BCS strategy also in comparison with competitive state-of-the-art alternatives.

Mobile Image Multi-label Recognition Algorithm Based on PaddlePaddle Platform

As one of the core algorithms of machine vision, the mobile image multi-label recognition algorithm has received extensive attention from researchers in recent years and has been widely used in cutting-edge fields such as deep learning framework paddlepaddle platform, video surveillance, intelligent robots, and unmanned aerial vehicles. However, the existing recognition algorithms are not completely satisfied with the practical application in life and production. Due to the complexity of the platform environment, they can often only propose specific solutions based on existing problems, and there is no universal algorithm that is suitable for all kinds of Complex environment. The purpose of this paper is to study the multi-label recognition algorithm of moving images based on PaddlePaddle platform. This research mainly analyzes and researches the mobile image multi-tag space deployment plan and the multi-tag recognition algorithm, and further improves the tag reading rate and recognition reliability of the mobile image on the PaddlePaddle platform. This research first analyzes several key factors that affect the performance of UHF recognition system, considers the improvement plan of PaddlePaddle platform’s mobile image multi-tag recognition algorithm from the two aspects of space diversity and frequency diversity, and finally determines the multiple The label space diversity scheme, and the introduction of a multi-label optimization recognition algorithm to improve the recognition efficiency of the PaddlePaddle platform’s mobile image multi-label. Experimental data shows that the reading rate can reach 0.907 when identifying 300 tags in the experiment, and when the number of tags is greater than 300, the reading rate is close to 1, which verifies that the algorithm proposed in this paper is used in the multi-tag recognition of moving images on the PaddlePaddle platform.

Abundance, diversity, and distribution of plant-parasitic nematodes in horticultural soils under different management systems in a tomato-producing area in Argentina

Summary Monitoring the diversity and structure of plant-parasitic nematode (PPN) communities together with developing appropriate control strategies can reduce the occurrence of these pathogens and other plant pests in horticultural crops. In this context a study of the abundance, frequency, diversity and distribution of PPN in horticultural soils under glasshouse conditions from the Green Belt of La Plata, Buenos Aires, Argentina, under different management systems was undertaken. Soil samples were collected from three horticultural areas with different tomato crop managements: agroecological crop (AC); organic crop with Brassicaceae soil amendments (OC); intensive conventional crop treated with methyl bromide (MeBr) (IC). The parameters evaluated were: nematode genera richness (G); Shannon-Wiener diversity index () (Hutcheson’s t-test was applied for this index); equitability index (E); abundance; and frequency of genera. ANOSIM and SIMPER statistical analyses were performed to find significant differences between the nematode assemblages from the different sites. A total of 14 genera of PPN were identified among the three crop sites. Members of the feeding habits categories ectoparasites, semi-endoparasites, migratory endoparasites and sedentary endoparasites were observed. Statistical analysis enabled us to characterise each site based on the composition of the nematode assemblages. Helicotylenchus, Tylenchus and Nacobbus were the most frequent and abundant genera. AC and OC showed similar values of richness and diversity; the crop treated with MeBr (IC) showed the lowest diversity of PPN.

Biodiversity of epiphytic periphyton in the leaves of the seagrass bed of Talawaan Bajo Estuary, North Sulawesi, Indonesia

Ogi NLIM, Herawati EY, Risjani Y, Mahmudi M. 2021. Biodiversity of epiphytic periphyton in the leaves of the seagrass bed of Talawaan Bajo Estuary, North Sulawesi, Indonesia. Biodiversitas 22: 4857-4864. This study aimed to analyze the diversity of epiphytic periphyton on the leaves of the seagrass bed of Talawaan Bajo estuary North Sulawesi Indonesia. The study was performed in three sampling points by using the line transect method with 50x50 cm2. The sampling points were located in front of the residential area, the mangrove forest, and in budo Cape. Seagrass and periphyton communities were analyzed for species density, relative frequency, diversity, evenness, and dominance index. Water quality and heavy metal Hg were also measured. The results showed that Cymodocea rotundata was the dominant seagrass based on species density and frequency distribution. Periphyton composition on the leaf of C. rotundata consisted of Bacillariophyceae (16 genera), Cyanophyceae (3 genera), Chlorophyceae (9 genera), Dinophyceae (1 genus), and Rhodophyceae (1 genus). The water quality, such as phosphate, current, nitrate, dissolved oxygen, and Hg content in the water, contributed to changing the environmental condition of Talawaan Bajo waters. Therefore, the efforts to manage coastal resource conservation in the Talawaan Bajo estuary require more concern from the government and stakeholders of Talawaan Bajo.

Tracking a Low-Angle Isolated Target via an Elevation-Angle Estimation Algorithm Based on Extended Kalman Filter with an Array Antenna

In a low-angle tracking situation, estimating the elevation angle is challenging due to the entrance of the multipath signals in the antenna’s main lobe. In this article, we propose two methods based on the extended Kalman filter (EKF) and frequency diversity (FD) process to estimate the elevation angle of a low-angle isolated target. In the first case, a simple weighting of the per-frequency estimates is obtained (termed WFD). Differently, in the second case, a matrix-based elaboration of the per-frequency estimates is proposed (termed MFD). The proposed methods are completely independent of prior knowledge of geometrical information and the physical parameters. The simulation results show that both methods have excellent performance and guarantee accurate elevation angle estimation in different multipath environments and even in very-low SNR conditions. Hence, they are both suitable for low-peak-power radars.

Structure of Seagrass Community in the Karapyak Beach, Pangandaran Regency, West Java

Karapyak Beach is one of the beaches that has a variety of abundant marine ecosystems. One of the marine ecosystems is seagrass. This study aims to identify the structure of seagrass communities in Karapyak waters based on seagrass species, species density, species frequency, diversity, and uniformity. This research was conducted in February – April 2021. The method used is a survey method with direct observation at each predetermined station using a square transect measuring 1 x 1 m2. While the determination of stations and observation points is done by purposive sampling method. The research location is divided into three stations, each station is divided into five substations (plots), and a 50 m transect line is made perpendicular to the shoreline. Furthermore, the results showed four types of seagrass found in the waters of Karapyak Beach, namely Cymodocea rotundata, Thalassia hemprichii, Halodule pinifolia, Halodule uninervis. The density of seagrass at station I was in the medium category, namely 125 individuals/m2, with a cover percentage of 86%. Then the lowest seagrass density was found at the second station, which was 104 individuals/m2 including the unhealthy category with a cover percentage of 58%. While the highest density score was shown at the third station, namely 144 individuals/m2 with a closing percentage of 94%.