A direct RF sampling method refers to a technique that directly converts a passband signal to an intermediate band or a baseband without using a mixer. This method is less complicated than an existing RF receiver because a mixer is not used. It uses digital processing after sampling, and thus can flexibly process signals in a number of bands using software. In this process, it is important to select an appropriate sampling frequency so that a number of signals can be converted to an intermediate band that is easy to process. In this study, going beyond previously studied direct RF sampling frequency selection methods, conditions that need to be additionally considered during receiver design were examined, and the structure of a direct RF sampling receiver that satisfies these conditions was suggested.

A graphic processing unit (GPU) can perform the same calculation on multiple data (SIMD: single instruction multiple data) using hundreds of to thousands of special purpose processors for graphic processing. Thus, high efficiency is expected when GPU is used for the generation and correlation of satellite navigation signals, which perform generation and processing by applying the same calculation procedure to tens of millions of discrete signal samples per second. In this study, the structure of a GPU-based GNSS simulator for the generation and processing of satellite navigation signals was designed, developed, and verified. To verify the developed satellite navigation signal generator, generated signals were applied to the OEM-V3 receiver of Novatel Inc., and the measured values were examined. To verify the satellite navigation signal processor, the performance was examined by collecting and processing actual GNSS intermediate frequency signals. The results of the verification indicated that satellite navigation signals could be generated and processed in real time using two GPUs.

When an incoming Global Positioning System (GPS) signal is acquired, pull-in search performs a finer search of the Doppler frequency of the incoming signal so that phase lock loop can be quickly stabilized and the receiver can produce an accurate pseudo-range measurement. However, increasing the accuracy of the Doppler frequency estimation often involves a higher computational cost for weaker GPS signals, which delays the position fix. In this paper, we show that the Doppler frequency detectable by a long coherent auto-correlation can be accurately estimated using a complex-weighted sum of consecutive short coherent auto-correlation outputs with a different Doppler frequency hypothesis, and by exploiting this we propose a noise resistant, low-cost and highly accurate Doppler frequency and phase estimation technique based on a reverse directional application of the finite rate of innovation (FRI) technique. We provide a performance and computational complexity analysis to show the feasibility of the proposed technique and compare the performance to conventional techniques using numerous Monte Carlo simulations.

In CDGPS, ambiguity resolution is determined by the performance of a floating solution, and thus, the performance needs to be improved. In the case of precise positioning at a stationary position, the batch method using multiple measurements is used for the accuracy improvement of a position. The position accuracy performance of a floating solution is outstanding, but it has a problem of high computation cost because all measurements are used. In this study, to improve the floating solution performance of the initial static user in CDGPS, a floating solution method using a recursive filter was implemented. A recursive filter estimates the position solution of the current epoch using the position solution of up to the previous epoch and the pseudorange measurement of the current epoch. The computation cost of the floating solution method using a recursive filter was found to be similar to that of the epoch-by-epoch method. Also, based on actual GPS signals, the floating solution performance was found to be similar to that of the batch method. The floating solution using a recursive filter could significantly improve the performance of the prompt initial position and ambiguity resolution of the initial static user.

The real-time kinematic (RTK) is one of precise positioning methods using Global Positioning System (GPS) data. In the long baseline GPS RTK, the ionospheric and tropospheric delays are critical factors for the positioning accuracy. In this paper we present RTK algorithms for long baselines more than 100 km with estimating tropospheric delays. The state vector is estimated by the extended Kalman filter. We show the experimental results of GPS RTK for various baselines (162.10, 393.37, 582.29, and 1283.57 km) by using the Korea Astronomy and Space Science Institute GPS data and one International GNSS Service (IGS) reference station located in Japan. As a result, we present that long baseline GPS RTK can provide the accurate positioning for users less than few centimeters.