Analysis of non ambiguous BOC signal acquisition performance Acquisition

The Binary Offset Carrier planned for future GNSS signal, including several GALILEO Signals as well as GPS M-code, presents a high degree of spectral separation from conventional signals. It also greatly improves positioning accuracy and enhances multipath rejection. However, with such a modulation, the acquisition process is made more complex. Specific techniques must be employed in order to avoid unacceptable errors. This paper assesses the performance of three method allowing to acquire and track BOC signal unambiguously : The Bump-jumping technique, The "BPSK-like" technique and the subcarrier Phase cancellation technique

A new multipath mitigation method for GNSS receivers based on antenna array

the potential of small antenna array for multipath mitigation in GNSS systems is considered in this paper. To discriminate the different incoming signals (Line of sight and multipaths), a new implementation of the well known SAGE algorithm is proposed. This allows a significant complexity reduction and it is fully compatible with conventional GNSS receivers. Theoretical study thanks to the Cramer Rao Bound derivation and tracking simulation results (in static and dynamic scenarios) show that the proposed method is a very promising approach for the multipath mitigation problem in GNSS receivers

A new tracking approach for multipath mitigation based on antenna array

In Global Navigation Satellites Systems (GNSS), multipaths (MP) are still one of the major error sources. The additional signal replica due to reflection will introduce a bias in conventional Delay Lock Loops (DLL) which will finally cause a strong positioning error. Several techniques, based on Maximum Likelihood estimation (ML), have been developed for multipaths mitigation/estimation such as the Narrow correlator spacing [1] or the Multipath Estimating Delay-Lock-Loop (MEDLL) [2] algorithm. These techniques try to discriminate the MP from the Line Of Sight Signal (LOSS) on the time and frequency domains and thus, short delay multipaths (<0.1Chips) can not be completely mitigated. Antenna array perform a spatial sampling of the wave front what makes possible the discrimination of the sources on the space domain (azimuth and elevation). As the time-delay domain and space domain can be assumed independent, we can expect to mitigate/estimate very short delay MP by using an antenna array. However, we don't want to increase too much the size, the complexity and the cost of the receivers and thus, we focus our study on small arrays with a small number of antennas: typically a square 2x2 array. Consequently, conventional beamforming (space Fast Fourier Transform) is not directive enough to assure the mitigation of the multipaths, and then this first class of solutions was rejected. In order to improve the resolution, adaptive beamformers have also been tested. However, the LOSS and the MP signal are strongly correlated and thus, classical adaptive algorithms [3] are not able to discriminate the sources. These preliminary studies have shown that the mitigation/estimation of multipaths based on the space domain will exhibit limited performances in presence of close sources. Then, in order to propose robust algorithms, we decided to investigate a space-time-frequency estimation of the sources. Space Alternating Generalized Expectation maximisation (SAGE) algorithm [4], which is a low-complexity generalization of the Expectation Maximisation (EM) algorithm, has been considered. The basic concept of the SAGE algorithm is the hidden data space [4]. Instead of estimating the parameters of all impinging waves in parallel in one iteration step as done by the EM algorithm, the SAGE algorithm estimates the parameters of each signal sequentially. Moreover, SAGE algorithm breaks down the multi-dimensional optimization problem into several smaller problems. In [5], it can be seen that SAGE algorithm is efficient for any multipaths configurations (small relative delays, close DOAs) and space-time-frequency approach is clearly outperforming classical time-frequency approaches. Notwithstanding, SAGE algorithm is a post processing algorithm. Thus, it's necessary to memorise in the receiver the incoming signal in order to apply SAGE estimation. For example, if we want to process 10ms of signal with a 10MHz sampling rate, we need to store a matrix of m*105 with m the number of antennas. In such condition, we can understand than SAGE algorithm is hardly implemented in real time. The challenge is then to find a new type of algorithms that reach the efficiency of the SAGE algorithms, but with a reduced complexity in order to enable real time processing. Furthermore, the implementation should be compatible with conventional GNSS tracking loops (DLL and PLL). To cope with these two constraints, we propose to apply the SAGE algorithm on the post-correlated signal. Indeed, the correlation step can be seen as a compression step and thus, the size of the studied signal is strongly reduced. In such a way, SAGE algorithm is able to provide estimates of the relative delay and Doppler of the received signals with respect to the local replicas. Thus, a post correlation implementation of SAGE can be seen as a discriminator for both the DLL and the PLL

Comparison of SAGE and classical multi-antenna algorithms for multipath mitigation in real-world environment

The performance of the Space Alternating Generalized Expectation Maximisation (SAGE) algorithm for multipath mitigation is assessed in this paper. Numerical simulations have already proven the potential of SAGE in navigation context, but practical aspects of the implementation of such a technique in a GNSS receiver are the topic for further investigation. In this paper, we will present the first results of SAGE implementation in a real world environmen

GPS Multipath Detection in the Frequency Domain

Multipath is among the major sources of errors in precise positioning using GPS and continues to be extensively studied. Two Fast Fourier Transform (FFT)-based detectors are presented in this paper as GPS multipath detection techniques. The detectors are formulated as binary hypothesis tests under the assumption that the multipath exists for a sufficient time frame that allows its detection based on the quadrature arm of the coherent Early-minus-Late discriminator (Q EmL) for a scalar tracking loop (STL) or on the quadrature (Q EmL) and/or in-phase arm (I EmL) for a vector tracking loop (VTL), using an observation window of N samples. Performance analysis of the suggested detectors is done on multipath signal data acquired from the multipath environment simulator developed by the German Aerospace Centre (DLR) as well as on multipath data from real GPS signals. Application of the detection tests to correlator outputs of scalar and vector tracking loops shows that they may be used to exclude multipath contaminated satellites from the navigation solution. These detection techniques can be extended to other Global Navigation Satellite Systems (GNSS) such as GLONASS, Galileo and Beidou.Comment: 2016 European Navigation Conference (ENC 2016), May 2016, Helsinki, Finland. Proceedings of the 2016 European Navigation Conference (ENC 2016

Demodulation Performance Assessment of New GNSS Signals in Urban Environments

International audienceSatellite navigation signals demodulation performance ishistorically tested and compared in the Additive WhiteGaussian Noise propagation channel model which wellsimulates the signal reception in open areas. Nowadays,the majority of new applications targets dynamic users inurban environments; therefore the GNSS signalsdemodulation performance has become mandatory to beprovided in urban environments. The GPS L1C signaldemodulation performance in urban environments is thusprovided in this paper. To do that, a new methodologyadapted to provide and assess GNSS signalsdemodulation performance in urban channels has beendeveloped. It counteracts the classic method limitationswhich are the fluctuating received C/N0 in urbanenvironments and the fact that each received message istaken into account in the error rate computation whereasin GNSS it is not necessary. The new methodology thusproposes to provide the demodulation performance for‘favorable’ reception conditions together with statisticalinformation about the occurrence of these favorablereception conditions. To be able to apply this newmethodology and to provide the GPS L1C signaldemodulation performance in urban environments, asimulator SiGMeP (Simulator for GNSS MessagePerformance) has been developed. Two urbanpropagation channel models can be tested: thenarrowband Perez-Fontan/Prieto model and the widebandDLR model. Moreover, the impact of the received signalphase estimation residual errors has been taken intoaccount (ideal estimation is compared with PLL tracking)

GNSS Signal Demodulation Performance in Urban Environments

International audienceSatellite navigation signals demodulation performance is historically tested and compared in the Additive White Gaussian Noise propagation channel model which well simulates open areas. Nowadays, the majority of new applications targets dynamic users in urban environments; therefore the implementation of a simulation tool able to provide realistically GNSS signal demodulation performance in obstructed propagation channels has become mandatory . This paper presents the simulator SiGMeP (Simulator for GNSS Message Performance) which is wanted to provide demodulation performance of any GNSS signals in urban environment , as faithfully of reality as possible . The demodulation performance of GPS L1C/A, GPS L2C, GPS L1C and Galileo E1 OS signals simulated with SiGMeP in the AWGN channel model configuration is firstly showed . Then, the demodulation performance of GPS L1C simulated with SiGMeP in urban environments is presented using the Prieto channel model with two signal carrier phase estimation configurations: perfect signal carrier phase estimation and PLL trackin

A New GNSS Integrity Monitoring Based on Channels Joint Characterization

Many GNSS (Global Navigation Satellites System) applications need high integrity performances. Receiver Autonomous Integrity Monitoring (RAIM), or similar method, is commonly used. Initially developed for aeronautics, RAIM techniques may not be fully adapted for terrestrial navigation, especially in urban environments. Those techniques use basically the pseudoranges to derive an integrity criterion. In this paper, we introduce a new integrity criterion based on the correlation quality of each channel. This quality assessment is computed from the correlation levels for each channel, all based on a single position and speed. Hence, as the so-called Direct Position Estimation (DPE), we exploit the joint behaviour of all channels to detect any incoherence at an upstream step of the processing. This Direct RAIM (D-RAIM) allows detecting possible integrity problems before it can be seen on a classical RAIM scheme that only exploits the outputs of each channel

Optimizing GNSS Navigation Data Message Decoding in Urban Environment

Nowadays, the majority of new GNSS applications targets dynamic users in urban environments; therefore the decoder input in GNSS receivers needs to be adapted to the urban propagation channel to avoid mismatched decoding when using soft input channel decoding. The aim of this paper consists thus in showing that the GNSS signals demodulation performance is significantly improved integrating an advanced soft detection function as decoder input in urban areas. This advanced detection function takes into account some a priori information on the available Channel State Information (CSI). If no CSI is available, one has to blindly adapt the detection function in order to operate close to the perfect CSI case. This will lead to avoid mismatched decoding due to, for example, the consideration by default of the Additive White Gaussian Noise (AWGN) channel for the derivation of soft inputs to be fed to soft input decoders. As a consequence the decoding performance will be improved in urban areas. The expressions of the soft decoder input function adapted for an urban environment is highly dependent on the available CSI at the receiver end. Based on different model of urban propagation channels, several CSI contexts will be considered namely perfect CSI, partial statistical CSI and no CSI. Simulation results will be given related to the GPS L1C demodulation performance with these different advanced detection function expressions in an urban environment. The results presented in this paper are valid for any kind of soft input decoders, such as Viterbi decoding for trellis based codes, the MAP/BCJR decoding for turbo-codes and the Belief Propagation decoding for LDPC codes

New GNSS Signals Demodulation Performance in Urban Environments

Satellite navigation signals demodulation performance is historically tested and compared in the Additive White Gaussian Noise propagation channel model which well simulates the signal reception in open areas. Nowadays, the majority of new applications targets dynamic users in urban environments; therefore the implementation of a simulation tool able to provide realistic GNSS signal demodulation performance in obstructed propagation channels has become mandatory. This paper presents the simulator SiGMeP (Simulator for GNSS Message Performance), which is wanted to provide demodulation performance of any GNSS signals in urban environment, as faithfully of reality as possible. The demodulation performance of GPS L1C simulated with SiGMeP in the AWGN propagation channel model, in the Prieto propagation channel model (narrowband Land Mobile Satellite model in urban configuration) and in the DLR channel model (wideband Land Mobile Satellite model in urban configuration) are computed and compared one to the other. The demodulation performance for both LMS channel models is calculated using a new methodology better adapted to urban environments, and the impact of the received signal phase estimation residual errors has been taken into account (ideal estimation is compared with PLL tracking). Finally, a refined figure of merit used to represent GNSS signals demodulation performance in urban environment is proposed