• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.1-9
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• 2023

The problem of classifying a non-line-of-sight (NLOS) signal in a multipath channel is important to improve global navigation satellite system (GNSS) positioning accuracy in urban areas. Conventional deep learning-based NLOS signal classifiers use GNSS satellite measurements such as the carrier-to-noise-density ratio (CN_0), pseudorange, and elevation angle as inputs. However, there is a computational inefficiency with use of these measurements and the NLOS signal features expressed by the measurements are limited. In this paper, we propose a Convolutional Neural Network (CNN)-based NLOS signal classifier that receives successive Auto-correlation function (ACF) outputs according to a time-series, which is the most primitive output of GNSS signal processing. We compared the proposed classifier to other DL-based NLOS signal classifiers such as a multi-layer perceptron (MLP) and Gated Recurrent Unit (GRU) to show the superiority of the proposed classifier. The results show the proposed classifier does not require the navigation data extraction stage to classify the NLOS signals, and it has been verified that it has the best detection performance among all compared classifiers, with an accuracy of up to 97%.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.11-21
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• 2022

Fast Fourier transform (FFT)-based parallel acquisition techniques with reduced computational complexity have been widely used for the acquisition of binary phase shift keying (BPSK) global positioning system (GPS) signals. In this paper, we propose a low computational FFT-based fine acquisition technique, for binary offset carrier (BOC) modulated BPSK signals, that depending on the subcarrier-to-code chip rate ratio (SCR) selectively utilizes the computationally efficient frequency-domain realization of the BPSK-like technique and two-dimensional compressed correlator (BOC-TDCC) technique in the first stage in order to achieve a fast coarse acquisition and accomplishes a fine acquisition in the second stage. It is analyzed and demonstrated that the proposed technique requires much smaller mean fine acquisition computation (MFAC) than the conventional FFT-based BOC acquisition techniques. The proposed technique is one of the first techniques that achieves a fast FFT-based fine acquisition of BOC signals with a slight loss of detection probability. Therefore, the proposed technique is beneficial for the receivers to make a quick position fix when there are plenty of strong (i.e., line-of-sight) GNSS satellites to be searched.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.399-408
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• 2023

In this paper, we propose a solution that enables continuous indoor/outdoor positioning of smartphone users through the integration of Pedestrian Dead Reckoning (PDR) and GPS/WiFi signals. Considering that accurate step detection affects the accuracy of PDR, we propose a Deep Neural Network (DNN)-based technology to distinguish between walking and non-walking signals such as walking in place. Furthermore, in order to integrate PDR with GPS and WiFi signals, a technique is used to select a proper measurement by distinguishing between indoor/outdoor environments based on GPS Dilution of Precision (DOP) information. In addition, we propose a technology to adaptively change the measurement error covariance matrix by detecting measurement outliers that mainly occur in the indoor/outdoor transition section through a residual-based χ² test. It is verified through experiments on a testbed that these technologies significantly improve the performance of PDR and PDR/GPS/WiFi fingerprinting-based integrated pedestrian navigation.

• ETRI Journal
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• v.44 no.2
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• pp.300-312
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• 2022

Recently, public safety services have attracted significant attention for their ability to protect people from crimes. Rapid detection of dangerous situations (that is, abnormal situations where someone may be harmed or killed) is required in public safety services to reduce the time required to respond to such situations. This study proposes a novel danger detection technology based on multimodal data, which includes data from multiple sensors (for example, accelerometer, gyroscope, heart rate, air pressure, and global positioning system sensors), and multilog data, which includes contextual logs of humans and places (for example, contextual logs of human activities and crime-ridden districts) over time. To recognize human activity (for example, walk, sit, and punch), the proposed technology uses multimodal data analysis with an attitude heading reference system and long short-term memory. The proposed technology also includes multilog data analysis for detecting whether recognized activities of humans are dangerous. The proposed danger detection technology will benefit public safety services by improving danger detection capabilities.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.23-27
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• 2012

Recently, devices like Personal Privacy Devices (PPD) are being employed to avoid the detection of one's location by GPS, and most PPD transmits swept CW signals. However, signals transmitted from PPD may interfere a precise location system based on GPS. Accordingly, in order to reduce interferences by PPD, a technique to locate an interferer is needed. In order to locate an interferer AOA method and TDOA method are generally used, TDOA method is known to be more accurate than AOA method. Unfortunately, TDOA method has a problem of ambiguity in obtaining measurements of swept CW interference. Thus, this paper design a localization algorithm based on TDOA method that can accurately locate an interferer transmitting swept CW signals by resolving problem of ambiguity. In addition, feasibility of the designed algorithm has been verified by simulation results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.197-205
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• 2000

Productivity of container cranes and gantry cranes is influenced by the performance of crane hardware and cycle time. Cycle time in container handling is influenced by the path of containers and relative positioning of containers. So we have to minimize the sway of containers and spreaders to minimize relative positioning time. And sway minimization is influenced by the skill of workers in manual gantry cranes. In this paper, we will survey some anti-sway systems. Each system has some merits and some shortages. And we will show our choice and its experimental equipment which is under construction.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.1
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• pp.9-15
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• 2017

In this paper, results of a jammer detection and localization system operation are given. The system consists of receiver stations, a central tracking station, and a monitoring station and it was developed by our institute in 2014. Through real-time tests, it is confirmed that the developed system has an ability to estimate the location of interference sources with an accuracy of 50 m (CEP) even they was 10 km away. After verification, this system was installed in Incheon International Airport and operating results are being monitored by the airport and our institute continuously. In this year, there were some events that jamming signals were received from North Korea, so the data were analyzed and given here.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.139-146
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• 2018

In recent years, a satellite navigation signal authentication technique has been introduced to determine the spoofing of commercial C/A code using the cross-correlation mode of GPS P(Y) code received at two receivers. This paper discusses the technical considerations in the implementation and application of authentication system simulator hardware to achieve the above technique. The configuration of the simulator consists of authentication system and user receiver. The synchronization of GPS signals received at two devices, data transmission and reception, and codeless correlation of P(Y) code were implemented. The simulation test result verified that spoofing detection using P(Y) codeless correlation could be achieved.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.64-70
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• 1999

A new multi-beam optical system is presented on the grounds of tri-positioning systems in this paper. The system has been developed to improve the data transfer rate for the optical disk system. The actuating system is composed of a tracking and focusing actuating system basically and a newly developed beam rotating actuator. The beam rotating actuator is employed in a multi-beam optical system to trace more than one track simultaneously. The multi-beam optics is established through the optical simulation and several experimental trials. The differential phase tracking method is used in the tracking error signal detection based on the only one beam spot. We also analyze the characteristics of multi-beam optical system. The experimental result shows that the multi-beam positioning system has performance adequate to the multi-beam optical disk system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.183-185
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• 2010

There are many error sources in GPS signal propagation because the signals do not propagate in vacuum. The GPS observations should be preprocessed before they are used for positioning. The cycle slip and outlier detection algorithms are tested in this study in RINEX level using various linear combinations of the observables. The elbourne-Wubbena (M-W) linear combination has an advantage of long wavelength with low noise, and the geometry-free and ionosphere-free linear combinations are used as well to clean the measurements.