Deeply Integrated GPS/Low-Cost IMU for Low CNR Signal Processing: Concept Description and In-Flight Demonstration

Soloviev, Andrey; Gunawardena, Sanjeev; Graas, Frank van

doi:10.1002/j.2161-4296.2008.tb00414.x

Cited by 45 publications

(37 citation statements)

References 5 publications

(16 reference statements)

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“…If the coherent integration time extends beyond the data bit boundary, then the data bits need to be accounted for in some way. A number of approaches have been suggested in the literature for dealing with these unknown modulations (see, for example, Soloviev et al (2008) and references therein), they are not considered further herein.…”

Section: Effect On Measurementsmentioning

confidence: 99%

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

2010

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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.

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Section: Effect On Measurementsmentioning

confidence: 99%

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

2010

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“…Though the Doppler aiding showed smaller carrier phase errors than delta-Doppler aiding, the difference is not much. Several articles developed complicated aiding algorithms and demonstrated superior performances [5], [8]. On the other hand, this paper has shown that even a very simple method (e.g.…”

Section: Resultsmentioning

confidence: 99%

“…If cycle slips occur in several channels, the corresponding smoothing procedures have to be restarted, and would cause a missed approach. An implementation of an inertial sensor will improve the tracking performance if the Doppler frequency caused by aircraft dynamics is compensated by the inertial measurements [3]- [5]. In the present paper we describe a prototype INS-aided GPS receiver for the aircraft navigation complex, that is under development by JAXA, intended in particular to be engaged in approach and landing.…”

Section: Introductionmentioning

confidence: 99%

Development of INS-Aided GPS Tracking Loop and Flight Test Evaluation

Tsujii

Fujiwara

Suganuma

et al. 2011

SICE Journal of Control, Measurement, and System Integration

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: Robust tracking of a GNSS signal in a harsh environment such as a severe ionospheric scintillation is a challenge for the civil aviation. The use of an inertial sensor would improve the tracking performance since the Doppler frequency caused by aircraft dynamics could be compensated by the inertial measurements. In order to evaluate such an aiding, an INS aided GPS tracking loop is developed by using a software receiver, and a preliminary flight test is conducted. A navigation grade INS tightly-coupled with GPS as well as a low-cost MEMS INS loosely-coupled with GPS are installed to provide aiding information. In addition, two GPS front end units with different clock (TCXO and OCXO) are installed to collect digitized IF data. Off-line analyses during aircraft take-off show that the noise band width in tracking loop can be reduced to three hertz by the aiding. Also, the Doppler aiding by a low-cost MEMS INS shows a similar performance with the aiding by a navigation grade INS.

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“…The processing gain associated with the non-coherent integration has been documented in [15]. There are several methods that allow block-based software acquisition algorithms to overcome the impact of the navigation data bit on acquisition [1], [12]. Therefore, we omit the weak signal navigation data issue here to focus on the performance of interference cancellation.…”

Section: Interference Cancellation Algorithm Performance Evaluationmentioning

confidence: 99%

GPS Civil Signal Self-Interference Mitigation During Weak Signal Acquisition

Morton

Miller

Tsui

et al. 2007

IEEE Trans. Signal Process.

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Deeply Integrated GPS/Low-Cost IMU for Low CNR Signal Processing: Concept Description and In-Flight Demonstration

Cited by 45 publications

References 5 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

Development of INS-Aided GPS Tracking Loop and Flight Test Evaluation

GPS Civil Signal Self-Interference Mitigation During Weak Signal Acquisition

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