Implementation of a GNSS Receiver Signal Tracking Module

To improve the tracking performance of GNSS receiver in signal-attenuated environments, phase lock loop (PLL) and delay lock loop (DLL) assisted with Inertial Navigation System (INS) measurements are considered. Combining inertial navigation principles with signal processing, this paper proposes a simplified but efficient mathematical model of INS-assisted second-order tracking loops. Compared with unaided GNSS receiver, the tracking behavior of INS-assisted receiver is quantitatively analyzed, and the kind of INS suitable to guarantee the tracking condition is determined. The results indicate that an INS with 1 deg/h gyro drift is necessary to support PLL, and MEMS inertial sensor with 100 deg/h gyro drift is sufficient to aid DLL to keep favored tracking ability.

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GNSS Receiver Signal Tracking

Position, Navigation, and Timing Technologies in the 21st Century ◽

10.1002/9781119458449.ch15 ◽

2020 ◽

pp. 339-375 ◽

Cited By ~ 1

Author(s):

Y.T. Jade Morton ◽

R. Yang ◽

B. Breitsch

Keyword(s):

Signal Tracking ◽

Gnss Receiver

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Design of GPU Based Non-coherent Signal Tracking Module for Real-time GNSS SDR

E3S Web of Conferences ◽

10.1051/e3sconf/20199403013 ◽

2019 ◽

Vol 94 ◽

pp. 03013

Author(s):

Jong-Il Park ◽

Kwi Woo Park ◽

Chansik Park

Keyword(s):

Real Time ◽

Coherent Signal ◽

Signal Tracking ◽

The Real ◽

Notebook Computer ◽

Computational Performance ◽

Memory Bottleneck ◽

Tracking Module

In this paper, we design and implement GPU-based non-coherent GPS signal tracking module for real-time SDR. When using CPU and GPU simultaneously, the signal tracking module should be designed considering the memory bottleneck between the two processors. The basic non-coherent module, which accumulates the 1msec correlation value 20 times, is changed to accumulate M(20/N) times of Nmsec units. From the experiments using real GPS signals, the computational performance of N=20 is improved by 80% compared to N=1. Therefore, the implemented SDR using notebook computer can tracks more channels simultaneously in the real time.

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Signal Tracking Performance Improvement of Spaceborne GNSS Receiver, GPS-12

2019 European Navigation Conference (ENC) ◽

10.1109/euronav.2019.8714134 ◽

2019 ◽

Author(s):

Eun-hyouek Kim ◽

Hyeun-pil Jin ◽

Soon-chun Lee ◽

In-yong Park ◽

Amer Mohammad Al Sayegh

Keyword(s):

Performance Improvement ◽

Tracking Performance ◽

Signal Tracking ◽

Gnss Receiver

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The impact of ionospheric scintillation on the GNSS receiver signal tracking performance and measurement accuracy

2011 XXXth URSI General Assembly and Scientific Symposium ◽

10.1109/ursigass.2011.6123719 ◽

2011 ◽

Cited By ~ 2

Author(s):

Zeynep G. Elmas ◽

Marcio Aquino ◽

Biagio Forte

Keyword(s):

Measurement Accuracy ◽

Tracking Performance ◽

Ionospheric Scintillation ◽

Signal Tracking ◽

Gnss Receiver ◽

The Impact

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Design and Implementation of GPS L2C Signal Tracking Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.981.392 ◽

2014 ◽

Vol 981 ◽

pp. 392-397 ◽

Cited By ~ 2

Author(s):

Xue Fen Zhu ◽

Fei Shen ◽

Yang Yang ◽

Dong Rui Yang ◽

Xi Yuan Chen

Keyword(s):

Signal To Noise Ratio ◽

Code Rate ◽

Tracking Algorithm ◽

Center Frequency ◽

Tracking Loop ◽

Signal Tracking ◽

Code Tracking ◽

L2c Signal ◽

Time Division ◽

Tracking Module

The study of GPS L2C signal tracking algorithm aims to realize signal tracking in poor environment. The main topic includes L2C signal tracking principle and the performance of real signal tracking. The structure and applied background of the signal is stated in the introduction at first. The characteristic of time division multiplexing of CM code and CL code makes this tracking method utilize half of received energy inevitably. Then, as compositions of L2C signal tracking algorithm, the data demodulation, the code tracking and the carrier tracking module are showed their details in the paper, including the structure of the DLL tracking loop, the Costas carrier tracking loop and some necessary computational principles. Finally, compare happens on real excellent and poor signal-to-noise ratio environments by setting suitable parameters including the sampling frequency, the center frequency and the pseudo code rate to prove the effectiveness of tracking algorithm.

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