Optimizing GNSS Navigation Data Message Decoding in Urban Environment

Abstract : Global Navigation Satellite Systems (GNSS) are increasingly present in our everyday life. The interest of new users with further operational needs implies a constant evolution of the current GNSS systems. A significant part of the new applications are found in environments with difficult reception conditions such as urban areas. In these obstructed environments, the received signal is severely impacted by obstacles which generate multipath causing fading of the resulting signal that is detrimental to both the ranging and demodulation capability of the receiver. The principal function of a GNSS system is to provide positioning capabilities allowing a user to calculate its own position. In order to being able to provide the user position, a GNSS receiver needs to access to the useful information transmitted by the GNSS signal, called the navigation message. The navigation message is protected against errors due to the propagation channel thanks to a specific process: Forward Error Correction (FEC). The message is structured in different basic units of information, called codewords. Each codeword, in addition to containing useful information, carries redundant bits. These redundant bits are due to the application of a channel code which has the function of protecting the information bits against errors introduced by the signal propagation channel. Consequently, at the reception, the GNSS navigation message, or more especially the codewords, needs to be decoded by the receiver in order to remove all the coded bits errors to recover the transmitted useful bits. Forward Error Correction is thus essential to the correct exploitation of a GNSS signal. This process is very sensitive to the correct computation of the detection function which will feed the decoder input. Significant improvements are obtained by considering soft detection enabling the use of soft input channel decoders. In this context, the channel decoders need to be fed by soft inputs that are sufficient statistics from the detection point of view. This is usually achieved by computing Log-Likelihood Ratios (LLRs) based on both observation samples and channel parameters. Up until now, the expression of the detection function in GNSS receivers was obtained assuming an Additive White Gaussian Noise (AWGN) propagation channel. However since we are interested by urban applications, the detection function expression should be adapted to the urban propagation channel in order to improve the GNSS signals decoding performance. The aim of this paper is thus to propose an advanced processing algorithm in order to improve the receiver sensibility in fading channels. More specifically we have tried to determine whether the decoder used in classical GNSS receivers with a detection function computed for an AWGN channel model is satisfactory in urban environments, or whether it is worthwhile to integrate an advanced detection function adapted to an urban channel model, in order to improve the GNSS signals decoding performance in urban environments.
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Marion Roudier, Thomas Grelier, Lionel Ries, Charly Poulliat, Marie-Laure Boucheret, et al.. Optimizing GNSS Navigation Data Message Decoding in Urban Environment. IEEE/ION PLANS 2014, Position Location and Navigation Symposium, May 2014, Monterey, United States. pp.581-588, ⟨10.1109/PLANS.2014.6851419⟩. ⟨hal-00989798⟩



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