The computation load of traditional navigation data estimation algorithms for weak GNSS signal tracking increases exponentially with respect to the number of data bits needed to be estimated. To Keywords: GNSS weak signal tracking, navigation data bits estimation, dynamic programming IntroductionWith the further widening application of radio satellite navigation, GNSS receiver is facing a more and more demanding work environment: In the coverage of the urban canyons and vegetation, the sattelite signal will be attenuated by more than a dozen or even dozens dBs compared to the open sky condition [1]; In the presence of strong interference, even if the antijaming treatment is performed in the front-end processing, it will still result in signal power antenuation obviously [2]. Improving the track sensitivity will result in a higher rate of successful positioning under weak signal conditions, so the robustness of receiver is enhanced. Frequency discriminator performs a key role in the process of tracking the frequency of the signal carrier, so its performance have large impact for improving track sensitivity [3] [4]. By using the correlation value sequence come from the prompt correlator, frequency discriminator can estimate the frequency track deviation which is the signal's carrier frequency minus the local replica carrier's frequency. As a frequency estimator, in order to obtain high estimation precision, the duration of data used for single frequency discrimination operation should be extended [5]. Without the auxiliary ways to access the navigation data in advance, the the discriminator needs to estimate the combination of navigation data bits to achieve coherent accumulation. The modern GNSS signals have a pilot and data component transimited on the same carrier, and on the pilot component no data modulation is present. Although the frequency deviation can be estimated by the pilot component only with no need of data estimation, a discriminator jointly use the correlation value of pilot and data component will get a better performance [6].So the navigation data estimation algorithm has great significance for design of frequency discriminator under weak signal condition. Many Literatures have researched the data estimation algorithm. Literature [7] adopts the Viterbi algorithm of dynamic programming philosophy to implement navigation data estimation, but this method needs to estimate the signal amplitude, and its effectiveness is limited by trace back depth parameter of the algorithm. Literature [8] estimate the bit combination based on the maximum energy criterion, and for every 5 adjacent bits, it adopts an exhaustive search method. Literature [9] combines the fast Fourier transform (FFT) with the exhaustive search of navigation data message together, and the FFTs needed by frequency discrimination is reduced by using the characteristics of navigation data only takes the vaule of +1 and -1.

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This paper describes a GNSS simulator signal generation method based on GPU acceleration. Mathematical simulations of the satellite constellation and receiver carriers enable simulation control software (SCS) to periodically send the parameters of the visible satellites to users. Furthermore, the SCS calculates simulated digital IF signals by calling multiple parallel threads on the GPU. To improve the parallel computing speed, the data structure is designed to facilitate quick access to the pseudocode data. We propose an optimal CUDA implementation for calculating the sampling data according to the characteristics of the GNSS signals. Simulations demonstrate the effectiveness of the proposed method.