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Implementation and performance of a GPS/INS tightly coupled assisted PLL architecture using MEMS inertial sensors.

Tawk Y, Tomé P, Botteron C, Stebler Y, Farine PA - Sensors (Basel) (2014)

Bottom Line: The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated.In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors.Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone.

View Article: PubMed Central - PubMed

Affiliation: Polytechnique Fédérale de Lausanne, Institute of Microengineering (IMT), Electronics and Signal Processing Laboratory, Neuchâtel, Switzerland. youssef.tawk@gmail.com.

ABSTRACT
The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated. To improve the navigation performance in such environments, several enhancement methods can be implemented. For instance, external aid provided through coupling with other sensors has proven to contribute substantially to enhancing navigation performance and robustness. Within this context, coupling a very simple GPS receiver with an Inertial Navigation System (INS) based on low-cost micro-electro-mechanical systems (MEMS) inertial sensors is considered in this paper. In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors. In addition, we propose a data monitoring system in charge of checking the quality of the measurement flow in the architecture. The implementation of the TCAPLL is discussed in detail, and its performance under different scenarios is assessed. Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone.

No MeSH data available.


TCAPLL architecture.
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f1-sensors-14-03768: TCAPLL architecture.

Mentions: The TCAPLL architecture is shown in Figure 1 where the four main blocks of the architecture can be ideied as the GPS, the INS the integration filter and the data monitoring system. The measurement processing starts by running the GPS receiver alone and, once the ephemeris and a position, velocity and time (PVT) solution are obtained, the INS can be initialized and synchronized with the GPS time. Next, the position, velocity and attitude (PVA) solution from INS is projected into LOS to obtain INS ranges and Doppler frequencies which are combined with the raw pseudoranges and Doppler measurements from the GPS tracking loops to form the input of the centralized integration filter. The filter directly accepts their differences to compute the error corrections which are used to update the final position, velocity, attitude and time (PVAT) solution and the INS predicted errors, i.e., bias drifts and scale factors. The Doppler frequency predicted by the INS is added to the GPS oscillator frequency drift estimated by the integration filter to form a feed-forward component to assist the GPS PLL tracking loops. Note that the predicted INS Doppler frequency is taken directly from the output of the LOS projection block instead of the integration filter. The reason for this is that the integration filter update frequency is much lower than the INS prediction frequency. Therefore, to keep the GPS tracking loops up to date with the latest Doppler frequency, the INS output is taken and the corresponding INS Doppler is corrected every time the integration filter is updated. As a result, because the PLL tracking loops have an external aiding frequency, the dynamics and the receiver oscillator clock errors do not need to be tracked any more by the PLL loop filter and only the PLL thermal noise and the error of the external aiding component should be accounted for.


Implementation and performance of a GPS/INS tightly coupled assisted PLL architecture using MEMS inertial sensors.

Tawk Y, Tomé P, Botteron C, Stebler Y, Farine PA - Sensors (Basel) (2014)

TCAPLL architecture.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958239&req=5

f1-sensors-14-03768: TCAPLL architecture.
Mentions: The TCAPLL architecture is shown in Figure 1 where the four main blocks of the architecture can be ideied as the GPS, the INS the integration filter and the data monitoring system. The measurement processing starts by running the GPS receiver alone and, once the ephemeris and a position, velocity and time (PVT) solution are obtained, the INS can be initialized and synchronized with the GPS time. Next, the position, velocity and attitude (PVA) solution from INS is projected into LOS to obtain INS ranges and Doppler frequencies which are combined with the raw pseudoranges and Doppler measurements from the GPS tracking loops to form the input of the centralized integration filter. The filter directly accepts their differences to compute the error corrections which are used to update the final position, velocity, attitude and time (PVAT) solution and the INS predicted errors, i.e., bias drifts and scale factors. The Doppler frequency predicted by the INS is added to the GPS oscillator frequency drift estimated by the integration filter to form a feed-forward component to assist the GPS PLL tracking loops. Note that the predicted INS Doppler frequency is taken directly from the output of the LOS projection block instead of the integration filter. The reason for this is that the integration filter update frequency is much lower than the INS prediction frequency. Therefore, to keep the GPS tracking loops up to date with the latest Doppler frequency, the INS output is taken and the corresponding INS Doppler is corrected every time the integration filter is updated. As a result, because the PLL tracking loops have an external aiding frequency, the dynamics and the receiver oscillator clock errors do not need to be tracked any more by the PLL loop filter and only the PLL thermal noise and the error of the external aiding component should be accounted for.

Bottom Line: The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated.In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors.Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone.

View Article: PubMed Central - PubMed

Affiliation: Polytechnique Fédérale de Lausanne, Institute of Microengineering (IMT), Electronics and Signal Processing Laboratory, Neuchâtel, Switzerland. youssef.tawk@gmail.com.

ABSTRACT
The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated. To improve the navigation performance in such environments, several enhancement methods can be implemented. For instance, external aid provided through coupling with other sensors has proven to contribute substantially to enhancing navigation performance and robustness. Within this context, coupling a very simple GPS receiver with an Inertial Navigation System (INS) based on low-cost micro-electro-mechanical systems (MEMS) inertial sensors is considered in this paper. In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors. In addition, we propose a data monitoring system in charge of checking the quality of the measurement flow in the architecture. The implementation of the TCAPLL is discussed in detail, and its performance under different scenarios is assessed. Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone.

No MeSH data available.