scholarly journals A Dynamic Cooperative Scheme with Multiple Antennas for Indoor Mobile Robot Localization

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Chung-Liang Chang ◽  
Bo-Han Wu
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Interference Mitigation ◽  
Cooperative Diversity ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Adaptive Antenna ◽  
Gnss Receiver ◽  
Cooperative Scheme ◽  
Indoor Mobile Robot

This paper proposes a spatial cooperative diversity and decision-making technique to enhance signal detection and indoor mobile robot positioning performance of a global positioning satellite system (GNSS) receiver. Though the adaptive antenna array technique in early research could effectively promote antijamming freedom, overcome time-varying system, and mitigate narrowband and wideband interferences, factors such as the decrease of signal magnitude caused by obstacles (especially in the indoor environment), multipath, and blanking effect caused by the change in antenna direction with the motion of mobile robot can degrade the detection and interference mitigation performance of GNSS receivers. This paper aims to develop a dynamic cooperative scheme to proceed with the switch, selection, combination, and optimization among antennas. In addition, a signal processing experimental platform is also established to receive actually indoor GNSS signals for verification. The proposed scheme is capable of effectively promoting the postcorrelation signal-to-noise ratio (SNR) capability of a GNSS receiver under the indoor environment.

scholarly journals Low-Complexity Spatial-Temporal Filtering Method via Compressive Sensing for Interference Mitigation in a GNSS Receiver

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chung-Liang Chang ◽  
Guo-Shing Huang
Keyword(s):  
Compressive Sensing ◽  
Interference Mitigation ◽  
Low Complexity ◽  
Satellite System ◽  
Minimum Variance ◽  
Graphic User Interface ◽  
Gnss Receiver ◽  
Minimum Variance Distortionless Response ◽  
Wideband Interference ◽  
Global Navigation Satellite

A compressive sensing based array processing method is proposed to lower the complexity, and computation load of array system and to maintain the robust antijam performance in global navigation satellite system (GNSS) receiver. Firstly, the spatial and temporal compressed matrices are multiplied with array signal, which results in a small size array system. Secondly, the 2-dimensional (2D) minimum variance distortionless response (MVDR) beamformer is employed in proposed system to mitigate the narrowband and wideband interference simultaneously. The iterative process is performed to find optimal spatial and temporal gain vector by MVDR approach, which enhances the steering gain of direction of arrival (DOA) of interest. Meanwhile, the null gain is set at DOA of interference. Finally, the simulated navigation signal is generated offline by the graphic user interface tool and employed in the proposed algorithm. The theoretical analysis results using the proposed algorithm are verified based on simulated results.

Improved Weighted Centroid Localization with Quadratic Means for Indoor Mobile Robot Tracking

2015 ◽  
Vol 781 ◽  
pp. 441-444
Author(s):  
Jirapat Sangthong ◽  
Kantaphon Torat ◽  
Sathaporn Promwong
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Indoor Mobile Robot ◽  
Robot Tracking ◽  
Weighted Centroid Localization ◽  
The One ◽  
Range Free

Nowadays, mobile robot tracking is the one of application in wireless sensor networks (WSNs). A one of promising localization algorithm in range-free algorithm is the weighted centroid localization (WCL) algorithm. This work proposed the improved WCL algorithm with quadratic means based on received signal strength (RSS). The ZigBee operated at 2.4 GHz frequency is used to measure in the indoor environment. The final results will be discuss about the comparison of the typically WCL algorithm and the improved WCL algorithm. From the results, the 1-meter-precision of improved WCL is 91.67% and WCL is 83.33%. Moreover, the improved WCL obtained the 16.67% no error of estimated position.

scholarly journals A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1178
Author(s):  
Bo Sun ◽  
Bo Tan ◽  
Wenbo Wang ◽  
Elena Simona Lohan
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Time Estimation ◽  
Satellite System ◽  
Base Station ◽  
Rectangular Array ◽  
Single Station ◽  
5G Network ◽  
Autonomous Machines ◽  
3D Positioning

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.

Study the Effect of Radio Interference of the EHV Transmission Line on GNSS Signals

2013 ◽  
Vol 805-806 ◽  
pp. 851-854
Author(s):  
Zhi Ge Jia ◽  
Zhao Sheng Nie ◽  
Wei Wang ◽  
Xiao Guan ◽  
Di Jin Wang
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Internal Noise ◽  
Field Testing ◽  
Satellite System ◽  
Field Analysis ◽  
Radio Interference ◽  
Gnss Receiver ◽  
Global Navigation Satellite ◽  
Gnss Data

This work describes the field testing process of Global Navigation Satellite System (GNSS) receiver under 220KV, 500KV UHV transmission line and standard calibration field. Analysis for GNSS data results shows that the radio interference generated by EHV transmission lines have no effect on GNSS receiver internal noise levels and valid GNSS observation rate. Within 50 meters of the EHV transmission lines, the multi-path effects (mp1 and mp2 value) significantly exceeded the normal range and becomes larger with the increase of the voltage .outside 50 meters of the EHV transmission line, the multi-path effects have almost no effect on the high-precision GNSS observations.

scholarly journals Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

2018 ◽  
Vol 10 (8) ◽  
pp. 1245 ◽  
Author(s):  
Mehrez Zribi ◽  
Erwan Motte ◽  
Nicolas Baghdadi ◽  
Frédéric Baup ◽  
Sylvia Dayau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Satellite System ◽  
Area Index ◽  
Vegetation Height ◽  
Study Sites ◽  
Global Navigation Satellite ◽  
Vegetation Characteristic ◽  
Agricultural Areas

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

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