Low power, reduced complexity filtering and improved tracking accuracy for GNSS

Cetinsel Sevket 2014. Low power, reduced complexity filtering and improved tracking accuracy for GNSS. PhD thesis University of Westminster Faculty of Science and Technology https://doi.org/10.34737/970w5

TitleLow power, reduced complexity filtering and improved tracking accuracy for GNSS
TypePhD thesis
AuthorsCetinsel Sevket
Abstract

This thesis addresses the power consumption problems resulting from the advent of multiple GNSS satellite systems which create the need for receivers supporting multi-frequency, multi-constellation GNSS systems. Such a multi-mode receiver requires a substantial amount of signal processing power which translates to increased hardware complexity and higher power dissipation which reduces the battery life of a mobile platform. During the course of the work undertaken, a power analysis tool was developed in order to be able to estimate the hardware utilisation as well as the power consumption of a digital system. By using the power estimation tool developed, it was established that most of the power was dissipated after the Analog to Digital Converter (ADC)by the filters associated with the decimation process. The power dissipation and the hardware complexity of the decimator can be reduced substantially by using a minimum-phase Infinite Impulse Response (IIR) filter. For Global Positioning System (GPS) civilian signals, the use of IIR filters does not deleteriously affect the positional accuracy. However, in the case where an IIR filter was deployed in a GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS) receiver, the pseudorange measurements of the receiver varied by up to 200 metres. The work undertaken proposes various methods that overcomes the pseudorange measurement variation and reports on the results that are on par with linear-phase Finite Impulse Response (FIR) filters. The work also proposes a modified tracking loop that is capable of tracking very low Doppler frequencies without decreasing the tracking performance.

Year2014
File
PublisherUniversity of Westminster
Digital Object Identifier (DOI)https://doi.org/10.34737/970w5

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