Carrier loop architectures for tracking weak GPS signals

Razavi, Alireza; Gebre-Egziabher, Demoz; Akos, Dennis

doi:10.1109/taes.2008.4560215

Cited by 87 publications

(61 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The impact of the coherent integration time on GNSS signal tracking has previously been considered in, for example, Gebre-Egziabher et al (2005), Razavi et al (2008), and Pany et al (2009). There appear to be somewhat conflicting conclusions as to the benefits of increasing the integration time for weak signal processing.…”

Section: Introductionmentioning

confidence: 99%

Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals

2010

View full text Add to dashboard Cite

Carrier phase-based positioning using Global Navigation Satellite System (GNSS) signals can provide centimeter-level accuracy; however, to do so requires robust, continuous tracking of the phase of the received signal. The phase-locked loop is typically the weakest link in GNSS signal processing, with frequent cycle slips and loss of lock occurring at lower signal-to-noise ratios. One way to improve the signal-to-noise ratio is to increase the coherent integration time; however doing so reduces the loop update rate, thereby degrading performance. This paper investigates this trade-off between sensitivity and loop update rate by investigation of the Kalman filter-based tracking loop. It is shown that it is possible to choose an optimal integration time for a given application. A relatively straightforward procedure is given to determine this optimal value. The results are confirmed through real-time kinematic processing of live satellite signals.

show abstract

Section: Introductionmentioning

confidence: 99%

Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals

2010

View full text Add to dashboard Cite

show abstract

“…When there is no scintillation, the output of the carrier phase tracking loop for a receiver with a low-phase-noise OCXO clock on a stationary platform is dominated by the satellite-receiver Doppler frequency and Doppler rate (Razavi et al 2008), which can be adequately represented by a fourth-order polynomial (Peng et al 2010). The remaining high-frequency components of the phase variations are due to RF front end noise and possible RF interferences.…”

Section: Carrier Phase Measurementsmentioning

confidence: 99%

A USRP2-based reconfigurable multi-constellation multi-frequency GNSS software receiver front end

Peng

Morton

2012

GPS Solut

View full text Add to dashboard Cite

We present a multi-constellation multi-band GNSS software receiver front end based on USRP2, a general purpose radio platform. When integrated with appropriate daughter boards, the USRP2 can be used to collect raw intermediate frequency (IF) data covering the entire GNSS family of signals. In this study, C?? classbased software receiver processing functions were developed to process the IF data for GPS L1, L2C, and L5 and GLONASS L1 and L2 signals collected by the USRP2 front end. The front end performance is evaluated against the outputs of a high end custom front end driven by the same local oscillator and two commercial receivers, all using the same real signal sources. The results show that for GPS signals, the USRP2 front end typically generates carrier-to-noise ratio (C/N 0 ) at 1-3 and 1-2 dB below that of the high end front end and a NovAtel receiver, respectively. For GLONASS signals, the USRP2 C/N 0 outputs are comparable to those of a Septentrio receiver. The carrier phase noise from the USRP2 outputs is similar to those of the benchmarking devices. These results demonstrate that the USRP2 is a suitable front end for applications, such as ionosphere scintillation studies.

show abstract

“…The numbers of visible satellites will be lessen when receiver running in city roads or indoor environments, the carrier-to-noise power density ratio of GPS receiver is lower compared with the receiver located at somewhere GPS signal is not obscured, the performance of traditional receiver will be affected [1][2][3][4][5]. Reference [6][7][8][9][10]pointed out that vector tracking loop can combine signal tracking and receiver navigation parameter calculation together, each channel parameter of tracking loops don't have to be set, the information among these tracking loops can communicate with each other, every tracking loop performance would be improved.…”

Section: Introductionmentioning

confidence: 99%

A design method and performance analysis of vector-based tracking loop receiver

Li¹,

Wang²,

Guo³

et al. 2012

2012 IEEE 11th International Conference on Signal Processing

View full text Add to dashboard Cite

GPS signal can't be tracked effectively by traditional scalar tracking loop when receiver works in lower carrier-tonoise power density ratio ( ) environment. Therefore, a vector-based tracking loop receiver design method is presented in this paper. The relationships among measurement noise variance and predicted pseudorange variance are analyzed. Actual pseudoranges and pseudorange-rates errors are considered as statement information, receiver locally generated pseudoranges and pseudorange-rates errors are used as measurement information to build the Extended Kalman Filter (EKF). Vector-based tracking feedback loop is accomplished through calculating line-of-sight vector between the receiver and visible satellites, which is updated with time. Position Dilution of Precision (PDOP) is given through adopting actual satellite ephemeris. The simulation results show that, at the same, not only the vector tracking loop has lower predicted pseudorange variance, but also the performance of positioning error is better compared with scalar tracking loop.

show abstract

Carrier loop architectures for tracking weak GPS signals

Cited by 87 publications

References 4 publications

Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals

Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals

A USRP2-based reconfigurable multi-constellation multi-frequency GNSS software receiver front end

A design method and performance analysis of vector-based tracking loop receiver

Contact Info

Product

Resources

About