Reducing Front-End Bandwidth May Improve Digital GNSS Receiver Performance

Curran, James T.; Borio, Daniele; Lachapelle, Gérard; Murphy, Colin C.

doi:10.1109/tsp.2009.2037860

Cited by 15 publications

(16 citation statements)

References 12 publications

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“…Also, the filtering and quantization performed by the frontend are not taken into account. See Curran et al (2010) for more details about that topic. Finally, the noise term is not considered since the focus of this research is on the correlation properties.…”

Section: Signals Definitionsmentioning

confidence: 99%

Study on the cross-correlation of GNSS signals and typical approximations

Foucras

Leclère²,

Botteron³

et al. 2016

GPS Solut

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In global navigation satellite system (GNSS) receivers, the first signal processing stage is the acquisition, which consists of detecting the received GNSS signals and determining the associated code delay and Doppler frequency by means of correlations with a code and a carrier replicas. These codes, as part of the GNSS signal, were chosen to have very good correlation properties without considering the effect of a potential received Doppler frequency. In the literature, it is often admitted that the maximum GPS L1 C/A code cross-correlation is about −24 dB. We show that this maximum can be as high as −19.2 dB when considering a Doppler frequency in a typical range of [−5, 5] kHz. We also show the positive impact of the coherent integration time on the cross-correlation, and that even a satellite with Doppler outside the frequency search space of a receiver impacts the crosscorrelation. In addition, the expression of the correlation is often provided in the continuous time domain while its implementation is typically made in the discrete domain. It is then legitimate to ask the validity of this approximation. Therefore, the purpose of this research is twofold. First, we discuss typical approximations and evaluate their regions of validity. Second, we provide characteristic values such as maximums and quantiles of the auto and cross-correlation of the GPS L1 C/A and Galileo E1 OS codes in presence of Doppler, for frequency ranges up to 50 kHz, and for different integration times.

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Section: Signals Definitionsmentioning

confidence: 99%

Study on the cross-correlation of GNSS signals and typical approximations

Foucras

Leclère²,

Botteron³

et al. 2016

GPS Solut

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show abstract

“…In this second-order FLL, the overall frequency transfer function, ( ), can be expressed in terms of the loop filter, ( ), the numerically controlled oscillator, ( ), and the discriminator function, ( ), obtaining [7,8] …”

Section: Loop Performancementioning

confidence: 99%

“…Θ( ) and B( ) are the transformations of ( ) and ( ). For the third-order PLL, the loop transfer function is [2,8] …”

Section: Loop Performancementioning

confidence: 99%

See 1 more Smart Citation

High Dynamic Optimized Carrier Loop Improvement for Tracking Doppler Rates

Fereidountabar

Cardarilli

2015

Journal of Electrical and Computer Engineering

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Mathematical analysis and optimization of a carrier tracking loop are presented. Due to fast changing of the carrier frequency in some satellite systems, such as Low Earth Orbit (LEO) or Global Positioning System (GPS), or some planes like Unmanned Aerial Vehicles (UAVs), high dynamic tracking loops play a very important role. In this paper an optimized tracking loop consisting of a third-order Phase Locked Loop (PLL) assisted by a second-order Frequency Locked Loop (FLL) for UAVs is proposed and discussed. Based on this structure an optimal loop has been designed. The main advantages of this approach are the reduction of the computation complexity and smaller phase error. The paper shows the simulation results, comparing them with a previous work.

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“…The effective noise model of 1-bit quantization and its effect on the time-delay estimation in a GNSS receiver was discussed in [2]. Adjustments in the front-end of a digital GNSS receiver were suggested in [3,4]. By redesigning the front-end filter and quantizer, or by increasing the sampling frequency, the effective signal-to-noise ratio (SNR) after quantization can be improved.…”

Section: Introductionmentioning

confidence: 99%