Due to the Global Navigation Satellite System (GNSS) modernization, the recently launched GNSS satellites transmit signals at various frequency bands of L1, L2 and L5. Considering the Korea Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. In this paper, we introduce a multi-constellation (GPS/Galileo/BeiDou) multi-band (L1/L2/L5) SDR by utilizing Ettus USRP N210. The signal reception module of the developed SDR includes down-conversion, analog-to-digital conversion, signal acquisition, and tracking. The down-conversion module is designed based on the super-heterodyne method fitted for MHz sampling. The signal acquisition module performs PRN code generation and FFT operation and the signal tracking module implements delay/phase/frequency locked loops only by software. In general, it is difficult to sample entire main lobe components of L5 band signals due to their higher chipping rate compared with L1 and L2 band signals. Experiment result shows that it is possible to acquire and track the under-sampled signals by the developed SDR.

A series of numerical experiments with measurements observed at continuously operating reference stations (CORS) of the international GNSS services (IGS) and the national geographical information institute of Korea (NGII) have been intensively carried out to evaluate the quality of pseudo-ranges and carrier-phases of GPS L2C signal obtained by various receiver types, benign and harsh operational environment. In this analysis, some quality measures, such as signal-to-noise ratio (SNR), the magnitude of multipath, and the number of cycle slips, the pseudo-range and carrier phase obtaining rate were computed and compared. The SNR analysis revealed an impressive result that the trend in the SNR of C/A and the L2C comparably depends upon type of receivers. The result of multipath analysis also showed clearly different tendency depending on the receiver types. The reason for this inconsistent tendency was seemed to be that the different multipath mitigation algorithm built-in each receiver. The number of L2C cycle slip was less than P2(Y), and L2C measurements obtaining rate was higher than that of P2(Y) in three receiver types. In the harsh observational environment, L2C quality was not only superior to P2(Y) in all aspects such as SNR, multipath magnitude, the number of cycle slips, and measurement obtaining rate, but also it could maintain a level of quality equivalent to C/A. According to the results of this analysis, it's expected that improved positioning performance like accuracy and continuity can be got through the use of L2C instead of existing P2(Y).

In order to develop a Korea Positioning System (KPS) as part of key national infrastructure, independent navigation signal design is essential. The designed signal candidates must coexist with existing or planned GNSS signals within the limited frequency band. This requires a RF compatibility assessment, which can be performed using the Spectral Separation Coefficient (SSC) and Effective Carrier to Noise Density Ratio (Effective C/N0), for navigation signals. Thus, in this paper, the analysis of RF compatibility between the designed signal candidates and the existing GNSS signals is carried out based on analytical and numerical techniques.

Recently, many studies have considered the effect of atmospheric pressure loading (APL) on precise global navigation satellite system (GNSS) data processing. The APL deforms the Earth's crust. It can often exceed 10 mm in radial displacement. In this study, we analyze the APL effect on Multi-GNSS kinematic precise point positioning (PPP). In addition, observations received at two GNSS reference stations (DAEJ and SUWN) in South Korea were processed. The absolute position changes for the two stations were compared to before and after applying the APL effects from January 1 to February 29, 2020. The crust of South Korea was most affected by the APL in the up direction. With the APL model, the difference in daily position changes was mostly within 4 mm in the radial direction. On the other hand, the horizontal components (east-west and north-south) were relatively less affected than the radial component.

The position accuracy of the stand-alone Regional Navigation Satellite System (RNSS) users is more than tens of meters because of various error sources in satellite navigation signals. This paper focuses on wide-area differential (WAD) positioning technique, which is already applied in Global Navigation Satellite System (GNSS), in order to improve the position accuracy of RNSS users. According to the simulation results in the very narrow ground network in regional area, the horizontal position error of stand-alone RNSS is about RMS 11.6 m, and that of RNSS with WAD technique, named the WAD-RNSS, is about RMS 2.5 m. The accuracy performance has improved by about 78%.

Most existing studies on the wide-area differential global positioning system (WADGPS) used standard positioning service (SPS) receivers in their observation reference stations which provide the central control station global positioning system (GPS) measurements to generate augmentation data. In the present study, it is considered to apply a precise positioning service (PPS) receiver to an observation reference station which is located in the threatened jamming area. Therefore, the reference station network consists of a PPS receiver based observation reference station and SPS receiver based observation reference stations. In this case, to maintain correction performance P1C1 differential code bias (DCB) should be compensated. In this paper, P1C1 DCB estimation algorithm was applied to the PPS/WADGPS system and performance test results using measurements in the Korean Peninsula were presented.

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

In this paper, we propose a signal propagation modeling technique for generating a positioning fingerprint DB based on Long Term Evolution (LTE) signals. When a DB is created based on the location-based signal information collected in an urban area, gaps in the DB due to uncollected areas occur. The spatial interpolation method for filling the gaps has limitations. In addition, the existing gap filling technique through signal propagation modeling does not reflect the signal attenuation characteristics according to directions occurring in urban areas by considering only the signal attenuation characteristics according to distance. To solve this problem, this paper proposes a Deep Neural Network (DNN)-based signal propagation functionalization technique that considers distance and direction together. To verify the performance of this technique, an experiment was conducted in Seocho-gu, Seoul. Based on the acquired signals, signal propagation characteristics were modeled for each method, and Root Mean Squared Errors (RMSE) was calculated using the verification data to perform comparative analysis. As a result, it was shown that the proposed technique is improved by about 4.284 dBm compared to the existing signal propagation model. Through this, it can be confirmed that the DNN-based signal propagation model proposed in this paper is excellent in performance, and it is expected that the positioning performance will be improved based on the fingerprint DB generated through it.

The need for precise location data is growing across numerous markets, and so is the number of affordable high-precision GPS receivers. In this paper, we validated the performance of RTAP2U, a low-cost high-precision RTK receiver that was recently released. Two positioning modes were tested: static and driving. The static test conducted Zero-Baseline Single-RTK and Network-RTK survey for 57 hours and 51 hours, respectively. For the driving test, Network-RTK survey was conducted using VRS services provided by NGII based on Trimble PIVOT and Geo++ GNSMART. The static test showed about 1 cm horizontal and vertical accuracies, which is very stable considering the test duration longer than 50 hours. The integer ambiguity FIX rate marked a solid 100%. The driving test result also reached a 100% FIX rate. Horizontal and vertical accuracies were better than 2 cm and 3 cm, respectively. Researchers can refer to this paper when considering affordable high-precision GPS receivers as an option.