Target Localization Based on Bistatic T/R Pair Selection in GNSS-Based Multistatic Radar System

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.

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An Optimization Method of Ambiguity Function Based on Multi-Antenna Constrained and Application in Vehicle Attitude Determination

Micromachines ◽

10.3390/mi13010064 ◽

2021 ◽

Vol 13 (1) ◽

pp. 64

Author(s):

Yinzhi Zhao ◽

Jingui Zou ◽

Peng Zhang ◽

Jiming Guo ◽

Xinzhe Wang ◽

...

Keyword(s):

Attitude Determination ◽

Direct Method ◽

Simple Algorithm ◽

Optimization Method ◽

Satellite System ◽

Ambiguity Function ◽

Baseline Length ◽

Length Difference ◽

Global Navigation Satellite ◽

True Peak

The global navigation satellite system (GNSS)-based multi-antenna attitude determination method has the advantages of a simple algorithm and no error accumulation with time in long endurance operation. However, it is sometimes difficult to simultaneous obtain the fixed solutions of all antennas in vehicle attitude determination. If float or incorrect fixed solutions are used, precision and reliability of attitude cannot be guaranteed. Given this fact, a baseline-constrained ambiguity function method (BCAFM) based on a self-built four GNSS antennas hardware platform is proposed. The coordinates obtained by BCAFM can replace the unreliable real-time kinematic (RTK) float or incorrect fixed solutions, so as to assist the direct method for attitude determination. In the proposed BCAFM, the baseline constraint is applied to improve search efficiency (searching time), and the ambiguity function value (AFV) formula is optimized to enhance the discrimination of true peak. The correctness of the proposed method is verified by vehicle attitude determination results and baseline length difference. Experimental results demonstrate that the function values of error peaks are reduced, and the only true peak can be identified accurately. The valid epoch proportion increases by 14.95% after true peak coordinates are used to replace the GNSS-RTK float or incorrect fixed solutions. The precision of the three attitude angles is 0.54°, 1.46°, and 1.15°, respectively. Meanwhile, the RMS of baseline length difference is 3.8mm.

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A Fast Acquisition Algorithm Based on Division of GNSS Signals

Journal of Navigation ◽

10.1017/s0373463317000984 ◽

2018 ◽

Vol 71 (4) ◽

pp. 933-954 ◽

Cited By ~ 4

Author(s):

Qingxi Zeng ◽

Wenqi Qiu ◽

Pengna Zhang ◽

Xuefen Zhu ◽

Ling Pei

Keyword(s):

Detection Probability ◽

Roc Curves ◽

Satellite System ◽

Sampling Point ◽

Fusion Algorithm ◽

Probability Of False Alarm ◽

Computational Load ◽

Sampling Points ◽

Global Navigation Satellite ◽

Pca Algorithm

The acquisition of signals is a precondition for tracking and solution calculation in software-based Global Navigation Satellite System (GNSS) receivers. The Parallel Code phase Acquisition (PCA) algorithm can simultaneously obtain the correlation results at every sampling point. However, if the number of sampling points that needs processing is large, this method will lead to a heavy computational load. Thus, we improve the process of the PCA algorithm and propose a novel algorithm that divides the signals intoK(Kis a constant) parts to achieve correlation and obtains the correlation results with a fusion algorithm. This algorithm can simultaneously obtain the correlation results for sampling points at an interval ofKpoints. If theKvalue is selected appropriately, the computational load can be decreased by about 50%. Also, the Receiver Operating Characteristic (ROC) curves show that under a certain probability of false alarm, the detection probability of the proposed algorithms is 5% lower than that of the PCA algorithm. Therefore, the proposed algorithm can speed up the acquisition process with a slight decrease in detection probability.

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Constrained ESKF for UAV Positioning in Indoor Corridor Environment Based on IMU and WiFi

Sensors ◽

10.3390/s22010391 ◽

2022 ◽

Vol 22 (1) ◽

pp. 391

Author(s):

Zhonghan Li ◽

Yongbo Zhang

Keyword(s):

Data Fusion ◽

Autonomous Navigation ◽

Low Cost ◽

Optimization Method ◽

Satellite System ◽

Fusion Algorithm ◽

K Nearest Neighbors ◽

Positioning Accuracy ◽

Spatial Features ◽

Global Navigation Satellite

The indoor autonomous navigation of unmanned aerial vehicles (UAVs) is the current research hotspot. Unlike the outdoor broad environment, the indoor environment is unknown and complicated. Global Navigation Satellite System (GNSS) signals are easily blocked and reflected because of complex indoor spatial features, which make it impossible to achieve positioning and navigation indoors relying on GNSS. This article proposes a set of indoor corridor environment positioning methods based on the integration of WiFi and IMU. The zone partition-based Weighted K Nearest Neighbors (WKNN) algorithm is used to achieve higher WiFi-based positioning accuracy. On the basis of the Error-State Kalman Filter (ESKF) algorithm, WiFi-based and IMU-based methods are fused together and realize higher positioning accuracy. The probability-based optimization method is used for further accuracy improvement. After data fusion, the positioning accuracy increased by 51.09% compared to the IMU-based algorithm and by 66.16% compared to the WiFi-based algorithm. After optimization, the positioning accuracy increased by 20.9% compared to the ESKF-based data fusion algorithm. All of the above results prove that methods based on WiFi and IMU (low-cost sensors) are very capable of obtaining high indoor positioning accuracy.

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Response to Variations in River Flowrate by a Spaceborne GNSS-R River Width Estimator

Remote Sensing ◽

10.3390/rs11202450 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2450 ◽

Cited By ~ 2

Author(s):

April Warnock ◽

Christopher Ruf

Keyword(s):

Remote Sensing ◽

Global Navigation Satellite System ◽

Satellite System ◽

Radar System ◽

Bistatic Radar ◽

Navigation Satellite ◽

Navigation Systems ◽

Highly Correlated ◽

Global Navigation Satellite

In recent years, the use of Global Navigation Satellite System-Reflectometry (GNSS-R) for remote sensing of the Earth’s surface has gained momentum as a means to exploit existing spaceborne microwave navigation systems for science-related applications. Here, we explore the potential for using measurements made by a spaceborne GNSS-R bistatic radar system (CYGNSS) during river overpasses to estimate its width, and to use that width as a proxy for river flowrate. We present a case study utilizing CYGNSS data collected in the spring of 2019 during multiple overpasses of the Pascagoula River in southern Mississippi over a range of flowrates. Our results demonstrate that a measure of river width derived from CYGNSS is highly correlated with the observed flowrates. We show that an approximately monotonic relationship exists between river flowrate and a measure of river width which we define as the associated GNSS-R width (AGW). These results suggest the potential for GNSS-R systems to be utilized as a means to estimate river flowrates and widths from space.

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THE OPTIMIZATION METHOD OF FUZZY AUTOMATIC CLASSIFICATION IN THE PROBLEM OF COMBINING THE ASSESSMENTS OF TRAJECTOR MEASUREMENTS IN THE RADAR SYSTEM

Doklady BGUIR ◽

10.35596/1729-7648-2020-18-2-89-95 ◽

2020 ◽

Vol 18 (2) ◽

pp. 89-95

Author(s):

A. V. Khizhniak

Keyword(s):

Measurement Errors ◽

A Priori ◽

Probabilistic Approach ◽

Optimization Methods ◽

Optimization Method ◽

Automatic Classification ◽

Radar System ◽

Mathematical Tool ◽

Technical Complex ◽

Trajectory Measurement

The paper describes the application of the optimization method of fuzzy automatic classification in the problem of combining estimates of trajectory measurements in a radar system. By a radiolocation system the author mean an automated hierarchical technical complex that combines, using communication tools, a set of asynchronously functioning radiolocation tools, as well as central and intermediate points that collect, process and issue trajectory radiolocation information. It must be borne in mind that in conditions of tracking tight groups of air targets, with relatively small intervals and distances, it is not always possible to obtain trajectory information of the required quality. The main reason for this is the difficulty in determining the values of the correlation matrices of errors in estimating the parameters of the state vector of air targets. The task becomes more complicated as the number of intermediate processing points increases when it is brought to the final consumer. The main goal of the article is to increase the accuracy of estimates of trajectory measurements in a radiolocation system. The research is done by means of the mathematical tool of fuzz-set theory, namely, by optimizing fuzzy automatic classification. The article demonstrates that using fuzzy automatic classification under a priori parametrical uncertainty in the law of trajectory measurement errors, when determining weight coefficients, can improve the accuracy of estimates in these conditions up to 30 % compared with methods based on the application of the probabilistic approach. The results obtained allow us to justify the prospects of using optimization methods of fuzzy automatic classification in the tasks of processing trajectory information. In addition, the advantage of the proposed method is its low computational complexity and ease of implementation, which is especially important while maintaining a large number of airborne objects.

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The characteristics of transforming coordinates from the geocentric system WGS-84 for the Mercator projection under low latitudes conditions

Geodesy and Cartography ◽

10.22389/0016-7126-2018-940-10-2-6 ◽

2018 ◽

Vol 940 (10) ◽

pp. 2-6

Author(s):

J.A. Younes ◽

M.G. Mustafin

Keyword(s):

Coordinate System ◽

Satellite System ◽

Programming Algorithm ◽

Low Latitude ◽

Model Calculations ◽

Mercator Projection ◽

Low Latitudes ◽

Rectangular Coordinates ◽

Global Navigation Satellite ◽

Coordination Methods

The issue of calculating the plane rectangular coordinates using the data obtained by the satellite observations during the creation of the geodetic networks is discussed in the article. The peculiarity of these works is in conversion of the coordinates into the Mercator projection, while the plane coordinate system on the base of Gauss-Kruger projection is used in Russia. When using the technology of global navigation satellite system, this task is relevant for any point (area) of the Earth due to a fundamentally different approach in determining the coordinates. The fact is that satellite determinations are much more precise than the ground coordination methods (triangulation and others). In addition, the conversion to the zonal coordinate system is associated with errors; the value at present can prove to be completely critical. The expediency of using the Mercator projection in the topographic and geodetic works production at low latitudes is shown numerically on the basis of model calculations. To convert the coordinates from the geocentric system with the Mercator projection, a programming algorithm which is widely used in Russia was chosen. For its application under low-latitude conditions, the modification of known formulas to be used in Saudi Arabia is implemented.

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Detecting Apples in the Wild: Potential for Harvest Quantity Estimation

Sustainability ◽

10.3390/su13148054 ◽

2021 ◽

Vol 13 (14) ◽

pp. 8054

Author(s):

Artur Janowski ◽

Rafał Kaźmierczak ◽

Cezary Kowalczyk ◽

Jakub Szulwic

Keyword(s):

Image Analysis ◽

Pilot Study ◽

Production Management ◽

Satellite System ◽

Morphological Operations ◽

Computational Performance ◽

Analysis Methods ◽

Manual Counting ◽

In The Wild ◽

Global Navigation Satellite

Knowing the exact number of fruits and trees helps farmers to make better decisions in their orchard production management. The current practice of crop estimation practice often involves manual counting of fruits (before harvesting), which is an extremely time-consuming and costly process. Additionally, this is not practicable for large orchards. Thanks to the changes that have taken place in recent years in the field of image analysis methods and computational performance, it is possible to create solutions for automatic fruit counting based on registered digital images. The pilot study aims to confirm the state of knowledge in the use of three methods (You Only Look Once—YOLO, Viola–Jones—a method based on the synergy of morphological operations of digital imagesand Hough transformation) of image recognition for apple detecting and counting. The study compared the results of three image analysis methods that can be used for counting apple fruits. They were validated, and their results allowed the recommendation of a method based on the YOLO algorithm for the proposed solution. It was based on the use of mass accessible devices (smartphones equipped with a camera with the required accuracy of image acquisition and accurate Global Navigation Satellite System (GNSS) positioning) for orchard owners to count growing apples. In our pilot study, three methods of counting apples were tested to create an automatic system for estimating apple yields in orchards. The test orchard is located at the University of Warmia and Mazury in Olsztyn. The tests were carried out on four trees located in different parts of the orchard. For the tests used, the dataset contained 1102 apple images and 3800 background images without fruits.

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GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation

Journal of Navigation ◽

10.1017/s0373463321000564 ◽

2021 ◽

pp. 1-16

Author(s):

Hong Hu ◽

Xuefeng Xie ◽

Jingxiang Gao ◽

Shuanggen Jin ◽

Peng Jiang

Keyword(s):

Stochastic Model ◽

Least Squares ◽

Stochastic Models ◽

Variance Component ◽

Satellite System ◽

Variance Component Estimation ◽

Short Baseline ◽

Component Estimation ◽

Zero Baseline ◽

Global Navigation Satellite

Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

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Investigation of Pre-Earthquake Ionospheric and Atmospheric Disturbances for Three Large Earthquakes in Mexico

Geosciences ◽

10.3390/geosciences11010016 ◽

2020 ◽

Vol 11 (1) ◽

pp. 16

Author(s):

Christina Oikonomou ◽

Haris Haralambous ◽

Sergey Pulinets ◽

Aakriti Khadka ◽

Shukra R. Paudel ◽

...

Keyword(s):

Chemical Potential ◽

Atmospheric Model ◽

Satellite System ◽

Seismic Events ◽

Electron Content ◽

Total Electron ◽

Atmospheric Disturbances ◽

Global Ionospheric Maps ◽

Global Navigation Satellite ◽

Large Earthquakes

The purpose of the present study is to investigate simultaneously pre-earthquake ionospheric and atmospheric disturbances by the application of different methodologies, with the ultimate aim to detect their possible link with the impending seismic event. Three large earthquakes in Mexico are selected (8.2 Mw, 7.1 Mw and 6.6 Mw during 8 and 19 September 2017 and 21 January 2016 respectively), while ionospheric variations during the entire year 2017 prior to 37 earthquakes are also examined. In particular, Total Electron Content (TEC) retrieved from Global Navigation Satellite System (GNSS) networks and Atmospheric Chemical Potential (ACP) variations extracted from an atmospheric model are analyzed by performing statistical and spectral analysis on TEC measurements with the aid of Global Ionospheric Maps (GIMs), Ionospheric Precursor Mask (IPM) methodology and time series and regional maps of ACP. It is found that both large and short scale ionospheric anomalies occurring from few hours to a few days prior to the seismic events may be linked to the forthcoming events and most of them are nearly concurrent with atmospheric anomalies happening during the same day. This analysis also highlights that even in low-latitude areas it is possible to discern pre-earthquake ionospheric disturbances possibly linked with the imminent seismic events.

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Estimation of fractional cycle bias for GPS/BDS-2/Galileo based on international GNSS monitoring and assessment system observations using the uncombined PPP model

Satellite Navigation ◽

10.1186/s43020-021-00039-x ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Jin Wang ◽

Qin Zhang ◽

Guanwen Huang

Keyword(s):

Estimation Method ◽

Satellite Orbit ◽

Satellite System ◽

Assessment System ◽

Navigation Satellite ◽

Dual Frequency ◽

Fractional Cycle Bias ◽

The Stability ◽

High Consistency ◽

Global Navigation Satellite

AbstractThe Fractional Cycle Bias (FCB) product is crucial for the Ambiguity Resolution (AR) in Precise Point Positioning (PPP). Different from the traditional method using the ionospheric-free ambiguity which is formed by the Wide Lane (WL) and Narrow Lane (NL) combinations, the uncombined PPP model is flexible and effective to generate the FCB products. This study presents the FCB estimation method based on the multi-Global Navigation Satellite System (GNSS) precise satellite orbit and clock corrections from the international GNSS Monitoring and Assessment System (iGMAS) observations using the uncombined PPP model. The dual-frequency raw ambiguities are combined by the integer coefficients (4,− 3) and (1,− 1) to directly estimate the FCBs. The details of FCB estimation are described with the Global Positioning System (GPS), BeiDou-2 Navigation Satellite System (BDS-2) and Galileo Navigation Satellite System (Galileo). For the estimated FCBs, the Root Mean Squares (RMSs) of the posterior residuals are smaller than 0.1 cycles, which indicates a high consistency for the float ambiguities. The stability of the WL FCBs series is better than 0.02 cycles for the three GNSS systems, while the STandard Deviation (STD) of the NL FCBs for BDS-2 is larger than 0.139 cycles. The combined FCBs have better stability than the raw series. With the multi-GNSS FCB products, the PPP AR for GPS/BDS-2/Galileo is demonstrated using the raw observations. For hourly static positioning results, the performance of the PPP AR with the three-system observations is improved by 42.6%, but only 13.1% for kinematic positioning results. The results indicate that precise and reliable positioning can be achieved with the PPP AR of GPS/BDS-2/Galileo, supported by multi-GNSS satellite orbit, clock, and FCB products based on iGMAS.

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