Parallel Frequency Acquisition Algorithm for BeiDou Software Receiver Based on Coherent Downsampling

The time it takes to acquire a satellite signal is one of the most important parameters for a Global Navigation Satellite System (GNSS) receiver. The Parallel Frequency space search acquisition Algorithm (PFA) runs faster than the Parallel Code phase search acquisition Algorithm (PCA) when the approximate phase of Pseudo-Random Noise (PRN) code and the approximate value of a Doppler shift are known. However, a large amount of data is needed to be dealt with by the Fast Fourier Transform (FFT) in a traditional PFA algorithm because it processes a narrow-band signal with the initial sampling frequency after the PRN code is stripped. In order to reduce the computational complexity of the traditional PFA algorithm, a down-conversion module and a downsampling module were added to the traditional PFA in the work reported here. Experiments demonstrated that this method not only succeeded in acquiring BeiDou B1I signals, but also the time for acquirement was reduced by at least 80% with the modified PFA algorithm compared with the traditional PFA algorithm. The loss in Signal-to-Noise Ratio (SNR) did not exceed 0·5 dB when the number of coherent points was less than 500.

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

Remote Sensing ◽

10.3390/rs10081245 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1245 ◽

Cited By ~ 15

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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FFT Splitting for Improved FPGA-Based Acquisition of GNSS Signals

International Journal of Navigation and Observation ◽

10.1155/2015/765898 ◽

2015 ◽

Vol 2015 ◽

pp. 1-12 ◽

Cited By ~ 3

Author(s):

Jérôme Leclère ◽

Cyril Botteron ◽

René Jr. Landry ◽

Pierre-André Farine

Keyword(s):

Processing Time ◽

Satellite System ◽

Fpga Implementation ◽

Probability Of Detection ◽

Navigation Satellite ◽

Code Search ◽

Parallel Code ◽

Memory Reduction ◽

Straightforward Solution ◽

Global Navigation Satellite

With modern global navigation satellite system (GNSS) signals, the FFT-based parallel code search acquisition must handle the frequent sign transitions due to the data or the secondary code. There is a straightforward solution to this problem, which consists in doubling the length of the FFTs, leading to a significant increase of the complexity. The authors already proposed a method to reduce the complexity without impairing the probability of detection. In particular, this led to a 50% memory reduction for an FPGA implementation. In this paper, the authors propose another approach, namely, the splitting of a large FFT into three or five smaller FFTs, providing better performances and higher flexibility. For an FPGA implementation, compared to the previously proposed approach, at the expense of a slight increase of the logic and multiplier resources, the splitting into three and five allows, respectively, a reduction of 40% and 64% of the memory, and of 25% and 37.5% of the processing time. Moreover, with the splitting into three FFTs, the algorithm is applicable for sampling frequencies up to 24.576 MHz for L5 band signals, against 21.846 MHz with the previously proposed algorithm. The algorithm is applied here to the GPS L5 and Galileo E5a, E5b, and E1 signals.

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High-rate altimetry in SNR-based GNSS-R: Proof-of-concept of a synthetic vertical array

10.36227/techrxiv.14186930 ◽

2021 ◽

Author(s):

Mauricio Kenji Yamawaki ◽

Felipe Geremia-Nievinski ◽

João Francisco Monico

Keyword(s):

Sea Level ◽

Signal To Noise Ratio ◽

Satellite System ◽

High Rate ◽

Proof Of Concept ◽

Radio Waves ◽

Vertical Array ◽

Remote Sensing Technique ◽

Single Antenna ◽

Global Navigation Satellite

Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a promising remote sensing technique for coastal sea level monitoring. The GNSS-R based on signal-to-noise ratio (SNR) observations employs a single antenna and a conventional receiver. It performs best for low elevation satellites, where direct and reflected radio waves are very similar in polarization and direction of arrival. One of the disadvantages of SNR-based GNSS-R for sea level altimetry is its low temporal resolution, which is of the order of one hour for each independent satellite pass. Here we present a proof-of-concept based on a synthetic vertical array. It exploits the mechanical movement of a single antenna at high rate (about 1 Hz). SNR observations can then be fit to a known modulation, of the order of the antenna sweeping rate. We demonstrate that centimetric altimetry precision can be achieved in a 5-minute session. [©2021 IEEE]

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Investigation of the Occurrence of Nighttime Topside Ionospheric Irregularities in Low-Latitude and Equatorial Regions Using CYGNSS Satellites

Sensors ◽

10.3390/s20030708 ◽

2020 ◽

Vol 20 (3) ◽

pp. 708 ◽

Cited By ~ 1

Author(s):

Liang Huang ◽

Yi Liu ◽

Qiong Tang ◽

Guanyi Chen ◽

Zhuangkai Wang ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Global Analysis ◽

Satellite System ◽

Ionospheric Irregularities ◽

Wave Number ◽

Significant Finding ◽

Low Latitude ◽

Zonal Wave Number ◽

Global Navigation Satellite ◽

Maximum Occurrence

By using multi-satellite observations of the L1 signal-to-noise ratio (SNR) from the Cyclone Global Navigation Satellite System (CYGNSS) taken in 2017, we present the occurrence of nighttime topside ionospheric irregularities in low-latitude and equatorial regions. The most significant finding of this study is the existence of longitudinal structures with a wavenumber 4 pattern in the topside irregularities. This suggests that lower atmospheric waves, especially a daytime diurnal eastward-propagating zonal wave number-3 nonmigrating tide (DE3), might play an important role in the generation of topside plasma bubbles during the low solar minimum. Observations of scintillation events indicate that the maximum occurrence of nighttime topside ionospheric irregularities occurs on the magnetic equator during the equinoxes. The current work, which could be regarded as an important update of the previous investigations, would be readily for the further global analysis of the topside ionospheric irregularities.

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Experimental results of multipath behavior for GPS L1-L2 and Galileo E1-E5b in static and kinematic scenarios

Journal of Applied Geodesy ◽

10.1515/jag-2019-0010 ◽

2019 ◽

Vol 13 (4) ◽

pp. 279-289 ◽

Cited By ~ 1

Author(s):

Alexandra Avram ◽

Volker Schwieger ◽

Noha El Gemayel

Keyword(s):

Signal To Noise Ratio ◽

Measurement Data ◽

Absolute Error ◽

Autonomous Driving ◽

Satellite System ◽

Natural Environments ◽

Navigation Systems ◽

Global Navigation Satellite ◽

The Impact ◽

Measurement Campaigns

Abstract Current trends like Autonomous Driving (AD) increase the need for a precise, reliable, and continuous position at high velocities. In both natural and man-made environments, Global Navigation Satellite System (GNSS) signals suffer challenges such as multipath, attenuation, or loss-of-lock. As Highway Assist and Highway Pilot are AD next steps, multipath knowledge is necessary for this typical user-case and kinematic situations. This paper presents a multipath performance analysis for GPS and Galileo satellites in static, slow, and high kinematic scenarios. The data is provided from car test-drives in both controlled and unrestricted, near-natural environments. The Code-Minus-Carrier (CMC) and cycle-slip implementations are validated with measurement data from consecutive days. Multipath statistical models based on satellite elevation are evaluated for the three investigated scenarios. Static models derived from the car setup measurements for GPS L1, L2 and Galileo E1 and E5b show a good agreement with a state-of-the-art model as well as the enhanced Galileo signals performance. Slow kinematic multipath results in a controlled environment showed an improvement for both navigation systems compared to the static measurements at the same place. This result is confirmed by static and slow kinematic multipath simulations with the same GNSS receiver. Post-processing analysis on highway measurements revealed a bigger multipath bias, compared to the open-sky static and slow kinematic measurement campaigns. Although less critical as urban or rural, this indicates the presence of multipath in this kind of environment as well. The impact of different parameters, including receiver architecture and Signal-to-noise ratio (SNR) are analyzed and discussed. Differential position (DGNSS) based on code is computed for each epoch and compared against GNSS/INS integrated position for all three measurement campaigns. The most significant 3D absolute error occurs where the greatest multipath envelope is found.

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3-D coherency filtering

Geophysics ◽

10.1190/1.1444232 ◽

1997 ◽

Vol 62 (4) ◽

pp. 1310-1314 ◽

Cited By ~ 1

Author(s):

Qing Li ◽

Kris Vasudevan ◽

Frederick A. Cook

Keyword(s):

Seismic Data ◽

Seismic Event ◽

Signal To Noise Ratio ◽

Random Noise ◽

Three Dimensions ◽

Coherent Noise ◽

Coherent Signal ◽

Frequency Space ◽

Time Space ◽

Incoherent Noise

Coherency filtering is a tool used commonly in 2-D seismic processing to isolate desired events from noisy data. It assumes that phase‐coherent signal can be separated from background incoherent noise on the basis of coherency estimates, and coherent noise from coherent signal on the basis of different dips. It is achieved by searching for the maximum coherence direction for each data point of a seismic event and enhancing the event along this direction through stacking; it suppresses the incoherent events along other directions. Foundations for a 2-D coherency filtering algorithm were laid out by several researchers (Neidell and Taner, 1971; McMechan, 1983; Leven and Roy‐Chowdhury, 1984; Kong et al., 1985; Milkereit and Spencer, 1989). Milkereit and Spencer (1989) have applied 2-D coherency filtering successfully to 2-D deep crustal seismic data for the improvement of visualization and interpretation. Work on random noise attenuation using frequency‐space or time‐space prediction filters both in two or three dimensions to increase the signal‐to‐noise ratio of the data can be found in geophysical literature (Canales, 1984; Hornbostel, 1991; Abma and Claerbout, 1995).

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A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography

Sensors ◽

10.3390/s18082526 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2526 ◽

Cited By ~ 8

Author(s):

Fei Yang ◽

Jiming Guo ◽

Junbo Shi ◽

Lv Zhou ◽

Yi Xu ◽

...

Keyword(s):

Water Vapor ◽

Precipitable Water ◽

Absolute Error ◽

Satellite System ◽

Observation Data ◽

Radiosonde Station ◽

Satellite Signal ◽

Comparative Results ◽

Global Navigation Satellite ◽

Vapor Distribution

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately.

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THERMAL IR IMAGING: IMAGE QUALITY AND ORTHOPHOTO GENERATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-413-2018 ◽

2018 ◽

Vol XLII-1 ◽

pp. 413-420 ◽

Cited By ~ 3

Author(s):

A. Sledz ◽

J. Unger ◽

C. Heipke

Keyword(s):

Image Quality ◽

Signal To Noise Ratio ◽

Automatic Generation ◽

Satellite System ◽

Night Time ◽

World Coordinate System ◽

Image Capturing ◽

Aerial Vehicle ◽

Rgb Images ◽

Global Navigation Satellite

<p><strong>Abstract.</strong> This paper deals with two aspects of photogrammetric processing of thermal images: image quality and 3D reconstruction quality. The first aspect of the paper relates to the influence of day light on Thermal InfraRed (TIR) images captured by an Unmanned Aerial Vehicle (UAV). Environmental factors such as ambient temperature and lack of sun light affect TIR image quality. We acquire image sequences of the same object during day and night and compare the generated orthophotos according to different metrics like contrast and signal-to-noise ratio (SNR). Our experiments show that performing TIR image acquisition during night time provides a better thermal contrast, regardless of whether we compute contrast over the whole image or over small patches. The second aspect investigated in this work is the potential of using TIR images for photogrammetric tasks such as the automatic generation of Digital Surface Models (DSM) and orthophotos. Due to the low geometrical resolution of a TIR camera and the low image quality in terms of contrast and noise compared to RGB images, the TIR DSM suffers from reconstruction errors and an orthophoto generated using the TIR DSM and TIR images is visibly influenced by those errors. We therefore include measurements of the UAVs positions during image capturing provided by a Global Navigation Satellite System (GNSS) receiver to retrieve position and orientation of TIR and RGB images in the same world coordinate system. To generate an orthophoto from TIR images, they are projected onto the DSM reconstructed from RGB images. This procedure leads to a TIR orthophoto of much higher quality in terms of geometrical correctness.</p>

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Moving Target Detection in Multi-Static GNSS-Based Passive Radar Based on Multi-Bernoulli Filter

Remote Sensing ◽

10.3390/rs12213495 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3495

Author(s):

HongCheng Zeng ◽

Jie Chen ◽

PengBo Wang ◽

Wei Liu ◽

XinKai Zhou ◽

...

Keyword(s):

Target Detection ◽

Sequential Monte Carlo ◽

Signal To Noise Ratio ◽

Power Level ◽

Estimation Method ◽

Satellite System ◽

Moving Target ◽

Passive Radar ◽

Moving Target Detection ◽

Global Navigation Satellite

Over the past few years, the global navigation satellite system (GNSS)-based passive radar (GBPR) has attracted more and more attention and has developed very quickly. However, the low power level of GNSS signal limits its application. To enhance the ability of moving target detection, a multi-static GBPR (MsGBPR) system is considered in this paper, and a modified iterated-corrector multi-Bernoulli (ICMB) filter is also proposed. The likelihood ratio model of the MsGBPR with range-Doppler map is first presented. Then, a signal-to-noise ratio (SNR) online estimation method is proposed, which can estimate the fluctuating and unknown map SNR effectively. After that, a modified ICMB filter and its sequential Monte Carlo (SMC) implementation are proposed, which can update all measurements from multi-transmitters in the optimum order (ascending order). Moreover, based on the proposed method, a moving target detecting framework using MsGBPR data is also presented. Finally, performance of the proposed method is demonstrated by numerical simulations and preliminary experimental results, and it is shown that the position and velocity of the moving target can be estimated accurately.

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Comparison of L1 and L5 Bands GNSS Signals Acquisition

Sensors ◽

10.3390/s18092779 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2779 ◽

Cited By ~ 3

Author(s):

Jérôme Leclère ◽

René Landry Jr. ◽

Cyril Botteron

Keyword(s):

Global Positioning System ◽

Satellite System ◽

Positioning System ◽

Global Positioning ◽

Accurate Comparison ◽

The Common ◽

Parallel Code ◽

L5 Signal ◽

Global Navigation Satellite ◽

Pilot Channel

Nowadays, civil Global Navigation Satellite System (GNSS) signals are available in both L1 and L5 bands. A receiver does not need to acquire independently the signals in both bands coming from a same satellite, since their carrier Doppler and code delay are closely related. Therefore, the question of which one to acquire first rises naturally. Although the common thought would tell the L1 band signals which are narrowband, an accurate comparison has never been done, and the decision is not as easy as it seems. Indeed, L5 band signals have several advantages such as stronger power, lower carrier Doppler, or a pilot channel, unlike the Global Positioning System (GPS) L1 C/A signal. The goal of this paper is therefore to compare the acquisition of L1 and L5 bands signals (GPS L1 C/A and L5, Galileo E1 and E5a/b) to determine which one is more complex and by which factor, in terms of processing time and memory, considering hardware receivers and the parallel code search. The results show that overall the L5 band signals are more complex to acquire, but it depends strongly on the conditions. The E5 signal is always more complex to acquire than E1, while the L5 signal can have a complexity close to the L1 C/A in some cases. Moreover, precise assistance providing accurate Doppler could significantly reduce the L5 complexity below the L1 complexity.

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